Health & Medical

AI in Drug Discovery: How New Medicines Are Found

By Eri-Tech Global Ltd · Published November 3, 2026 · Last updated November 3, 2026 · 9 min read

Scientists in lab coats work with test tubes in a modern laboratory.

AI in drug discovery is the use of computer models to help researchers find and shape new medicines. It does not replace the laboratory or the clinic. It works at the early stages, where researchers sort through far more biological data and chemical options than any team could check by hand.

A new medicine starts with a question about disease: which protein, gene, or pathway could be changed to help a patient? Once that target is chosen, researchers look for a molecule that acts on it in the right way, then test that molecule in the laboratory and, much later, in people.

This article explains that process in plain terms: what AI does well, where it still needs human checks, and what regulators in the United States and Europe now expect when AI is part of medicine development.

What drug discovery looked like before AI

Before AI tools became common, drug discovery followed a long, step-by-step path. Researchers first studied a disease to find a target, often a protein whose activity could be changed to improve health. Then they screened thousands of compounds, looking for the first "hits" — molecules that showed some effect on that target in laboratory tests.

The best hits were then refined into "leads." That refining step, called lead optimisation, adjusts a molecule to improve how strongly it binds to its target, how selective it is, and how it behaves in the body. Candidates that survived this work moved into preclinical testing, meaning laboratory and animal studies, and only then into clinical trials in people.

A recent review of AI in cancer drug development describes this full journey as taking 12 to 15 years, with most candidates failing along the way.

Computer-aided drug design already existed before modern AI. In the 1990s, researchers used computer models of drug-target interactions to guide laboratory work, rather than relying on trial and error alone. AI builds on that approach by learning patterns from large sets of biological and chemical data.

Finding a target: where a new medicine starts

Target identification is the first decision in drug discovery, and it shapes everything that follows. A target is a molecule or pathway in the body whose activity a medicine could change for a benefit. Choosing the wrong target can waste years, so researchers check many kinds of evidence before they commit.

AI helps here by pulling together different types of biological data. Genomic data shows which genes are changed in a disease. Transcriptomic data shows which genes are switched on. Proteomic and epigenomic data add information about proteins and how genes are regulated. The review of AI in cancer drug development describes models that read these combined data sets, rank disease-linked genes, and flag proteins that look most promising.

Protein shape matters because a protein's function depends on how its chain of amino acids folds into a three-dimensional form. If researchers know that shape, they can judge whether a molecule could fit and act on it. In 2020, Demis Hassabis and John Jumper presented AlphaFold2, an AI model that predicts protein structures from amino acid sequences. The Nobel Prize in Chemistry 2024 went to Hassabis and Jumper for protein structure prediction, with the other half of the prize going to David Baker for computational protein design.

The Nobel press release states that AlphaFold2 has been used to predict the structure of virtually all the 200 million proteins researchers have identified, and that it has been used by more than two million people from 190 countries. That shared library gives researchers a starting map, but a predicted shape still needs laboratory checks.

AI can also read published research, trial records, and patent data to find links between diseases, genes, and medicines that a single team might miss. The review gives the example of PandaOmics, a platform that combines multi-omics data with text mining to rank possible targets. These rankings are suggestions for researchers to test, not decisions made by the model alone.

Screening and designing molecules with AI

Once a target is chosen, researchers need molecules that might act on it. Two AI approaches help here. Virtual screening ranks existing chemical libraries by predicting which molecules are most likely to bind to the target. De novo design goes further: generative models propose entirely new molecular structures with chosen properties, rather than picking from a list that already exists.

The review describes how deep learning models predict drug-target interactions, screen millions of compounds, and optimise molecular features. One set of predictions covers ADMET properties: absorption, distribution, metabolism, excretion, and toxicity. In plain terms, that means how a substance enters the body, where it travels, how it is broken down, how it leaves, and whether it may cause harm. Predicting these properties early helps researchers set aside molecules that look unlikely to work as medicines.

Generative models can also propose changes to a lead molecule that might improve binding or reduce a predicted safety problem. Each proposal is then tested in the laboratory.

The review reports that more than 150 AI-designed small-molecule programmes were in preclinical development, with several already reaching clinical trials. That figure shows how far the field has moved from pure computer work into real testing. It does not mean those programmes will all succeed. Preclinical work and trials still remove most candidates, whether or not AI helped design them.

Scientist wearing a lab coat uses a microscope and pipette for research. — A scientist uses a microscope and pipette for research.

Why lab tests and clinical trials still come first

A computer prediction is only as good as the data behind it. The review lists the same limits that regulators raise: data quality, models that are hard to explain, computing demands, and questions about ethics and regulation. If training data are incomplete or biased, a model can favour the wrong targets or miss safety problems. If a model cannot explain its reasoning, researchers cannot easily check why it preferred one molecule over another.

That is why the testing stages after discovery have not changed in purpose. Preclinical work checks a candidate in cells and in animal studies before any person receives it. Then clinical trials test it in people, in phases that each answer a different question. The National Institutes of Health describes four phases. Phase I trials give an experimental treatment to a small group of 20 to 80 people for the first time, to judge safety and side effects. Phase II trials involve 100 to 300 people, to test effectiveness and to keep checking safety. Phase III trials involve 1,000 to 3,000 people, to confirm effectiveness, watch side effects, and compare the treatment with standard treatments. Phase IV trials take place after a medicine is approved, to track safety and best use over a longer period.

AI can also help inside trials, for example by helping researchers sort patient groups or plan studies, but it does not remove the need for these phases. Only trials, followed by regulator review, can show how a medicine acts in a large and varied group of people.

Readers should therefore treat news about AI medicines by their stage. A molecule found by a model, a candidate in animal studies, a candidate in a Phase I trial, and an approved medicine are four very different things, even if a headline treats them alike.

Detailed view of lab glassware with tubes and clamps in a laboratory setting. — Lab glassware with tubes and clamps in a laboratory.

What regulators now expect from AI in drug development

Regulators have moved from watching AI to setting out what they expect. The US Food and Drug Administration (FDA) says its Center for Drug Evaluation and Research has seen a large rise in drug application submissions that use AI components, across nonclinical, clinical, postmarketing, and manufacturing work. Its page on AI in drug development states that the agency's experience covers more than 500 submissions with AI components from 2016 to 2023.

The FDA published a discussion paper on AI and machine learning in drug development in May 2023, and a draft guidance in January 2025 on using AI to support regulatory decisions about a medicine's safety, effectiveness, or quality. The draft guidance asks sponsors to define the context of use, meaning the exact job the AI output is meant to do, and to show evidence matched to that job. The FDA also set up a CDER AI Council in 2024 to coordinate its AI work.

In Europe, the European Medicines Agency (EMA) adopted a reflection paper on AI in the medicinal product lifecycle in September 2024. The paper covers the full lifecycle, from drug discovery to the period after authorisation, and sets out considerations to help developers use AI in a safe and effective way. The EMA's overview page adds that the agency and the FDA have jointly identified ten principles for good AI practice in drug development, covering evidence generation and monitoring from early research through clinical trials, manufacturing, and safety monitoring.

The common thread is risk-based checking: the higher the patient risk or regulatory impact of an AI output, the stronger the evidence expected. Developers must document the training data, testing, ongoing performance checks, and where a person stays in charge of the final decision.

Frequently asked questions

Does AI design medicines on its own?

No. AI proposes targets and molecules and ranks options, but researchers choose which ideas to test, run the laboratory work, and judge the results. A model output is a suggestion that must survive experiments, trials, and regulator review before it can become a medicine.

Has AI already produced a medicine that patients can use?

AI-designed candidates have reached clinical trials, and more than 150 small-molecule programmes were reported in preclinical development in a recent review. Reaching a trial is not the same as approval. A medicine reaches patients only after trials show it is safe and effective and a regulator approves it.

Can AI make drug development faster?

It can speed up the early stages, by sorting targets and compounds faster than manual checks alone. The full path still includes laboratory testing, trials in people, and regulator review, so early speed does not remove the later stages or guarantee success.

AI in drug discovery is best understood as a better search tool for the hardest early questions: which target to pursue, which molecules deserve laboratory time, and which properties to check first. Its value shows when it helps researchers drop weak ideas early.

If you would like help turning a clear process into a simple system, explore our services or get in touch through our contact page.

This article is for general information and is not medical advice. Please speak to a qualified healthcare professional about your own situation.

What to watch next

Watch for the FDA's final guidance on AI in regulatory decision-making, for further EMA guidance following its reflection paper, and for trial results from AI-designed candidates now in clinical testing. Those three developments will show whether early AI gains hold up where it matters most: in people, under regulator review.

Sources

FDA — Artificial Intelligence for Drug Development — date checked: 2026-11-03 — https://www.fda.gov/about-fda/center-drug-evaluation-and-research-cder/artificial-intelligence-drug-development
European Medicines Agency — Use of Artificial Intelligence (AI) in the medicinal product lifecycle — date checked: 2026-11-03 — https://www.ema.europa.eu/en/scientific-guidelines/use-artificial-intelligence-ai-medicinal-product-lifecycle
European Medicines Agency — Artificial intelligence — date checked: 2026-11-03 — https://www.ema.europa.eu/en/about-us/how-we-work/data-regulation-big-data-other-sources/artificial-intelligence
Nature (npj Precision Oncology) — AI accelerate the identification of druggable targets by 3D structures of proteins and compounds — date checked: 2026-11-03 — https://www.nature.com/articles/s41698-026-01310-7
National Institutes of Health — Glossary of Common Terms — date checked: 2026-11-03 — https://www.nih.gov/health-information/nih-clinical-research-trials-you/glossary-common-terms
Nobel Prize — Press release: The Nobel Prize in Chemistry 2024 — date checked: 2026-11-03 — https://www.nobelprize.org/prizes/chemistry/2024/press-release/

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Health & Medical

Small Business Cash Flow: A Plain Guide to Money In and Out",slug:"small-business-cash-flow-explained",category:"Business",date:"2026-11-03",updated:"2026-11-03",primaryKeyword:"small business cash flow",metaDescription:"Small business cash flow is about timing: when money arrives and when bills fall due. Learn the three cash types, a simple forecast, and how to close gaps.",alt:"A smartphone showing a calculator app rests on top of financial documents.",image:"8962444",excerpt:"Small business cash flow is about timing: when money arrives and when bills fall due. Learn the three cash types, a simple forecast, and how to close gaps.",sections:[["What small business cash flow actually means","Small business cash flow is the movement of money into and out of a business, and the timing of that movement. Sales, customer payments, wages, rent, supplier bills, loan payments and tax bills all land on different dates, and the gaps between those dates decide whether a business can pay its bills on time.","That timing is why a business can look healthy on paper and still struggle in a given week. The United States Small Business Administration puts the point plainly: even profitable businesses can fail if they do not have the right amount of cash available at the right time.","This article explains cash flow in plain terms: what it is, how it differs from profit, the three parts of a cash flow statement, how to build a simple forecast, and what to do first when a customer pays late. It is general information, not advice about any one business.","Cash flow is a record of cash in and cash out over a set period. Cash in includes money customers pay, and cash out includes money paid to suppliers, staff, landlords and lenders. When cash in is larger than cash out for a period, the business has positive cash flow for that period. When cash out is larger, it has negative cash flow for that period.","The Small Business Administration describes a cash flow statement as a document showing the timing of all cash going in and out of the business over a particular period. Two businesses can have the same sales in a month and very different cash positions at the end of it, if one is paid at once and the other waits sixty days for its invoices to be settled.","Cash flow also sits beside two other core documents. Chase for Business explains that an income statement shows profitability, but not cash balances, while a balance sheet summarises assets, liabilities and equity at a single point in time, but does not track cash flow. The cash flow statement fills the gap: it tracks cash actually moving."],["Why profit on paper is not cash in the bank","Profit is calculated when revenue is earned and expenses are incurred, even if no cash has changed hands yet. Cash flow is calculated when cash changes hands. That single difference explains most cash flow surprises, and it is worth working through with an example.","Imagine a design studio invoices a client for work completed in November, with payment due in January. The income statement for November records the sale. The bank account in November does not change, because the client has not paid yet. In the same month, the studio still pays November wages, rent and software costs in cash. The business can therefore report a profit for November and still end November short of cash.","Chase for Business gives the same warning in plainer form: a business with a backlog of unpaid invoices might be profitable on paper but not have enough cash on hand to pay its bills. Regular checks catch that pattern early, before a missed payment damages a supplier relationship or leads to late fees. Profit answers the question, did the business earn more than it spent in that period, on paper. Cash flow answers a different question, did cash arrive in time to meet the bills that fell due."],["The three parts of a cash flow statement","Every cash flow statement is divided into three sections: operating, investing and financing, as described by Chase for Business, Capital One and NetSuite.","Operating activities cover the day-to-day running of the business: cash in from customers, and cash out to suppliers, staff, rent, utilities and tax. NetSuite describes operating cash flow as generally the best measure of whether a company is generating cash from its core business.","Investing activities cover longer-term assets. Buying equipment, a vehicle or a second location is an investing cash outflow, and selling an asset is an investing cash inflow. A business that buys a large piece of equipment will often show negative investing cash flow in that period, and that is not, on its own, a warning sign.","Financing activities cover how the business is funded: a loan received or money put in by an owner is a cash inflow, while loan repayments, interest payments and dividends paid out are cash outflows. A loan can make total cash flow look positive in the month it arrives, which is why Chase for Business warns owners to look below the surface: a positive total driven by borrowing is not the same as one driven by customers paying.","A short worked example from Chase for Business shows how the three parts add up. In its fictional bakery example for one quarter, operating activities produced 8,000 dollars, investing activities used 13,000 dollars for a new oven and a mixer upgrade, and financing activities added 10,000 dollars from a loan after a loan payment, giving a net increase of 5,000 dollars. Add the three sections for the change in cash, then add that change to the opening balance for the closing balance.","
$\"A$
Small business essentials: a calculator, calendar, coins, and letter tiles.
"],["How to build a simple cash flow forecast","A cash flow statement looks backward at cash that has already moved. A forecast looks forward. NetSuite defines cash flow forecasting as estimating the amount of cash coming in and leaving a business over a specific coming period, so the business can see whether its obligations can be met.","Capital One describes a cash flow projection in the same way, and notes that projections typically cover twelve months, but can also be built weekly, monthly or quarterly. NetSuite adds that short-term forecasting often covers the next thirty to sixty days, medium-term forecasting often runs to a rolling twelve months, and longer-term forecasting looks beyond a year, with accuracy falling as the horizon gets longer.","A simple forecast needs only five lines per period, and a spreadsheet is enough to start. First, write the opening balance, which equals the closing balance of the previous period. Second, list expected cash in, using the dates customers actually pay, not the dates invoices were sent. Third, list expected cash out, using the dates bills actually fall due, including wages, rent, supplier payments, loan payments and tax. Fourth, subtract cash out from cash in to get net cash flow. Fifth, add net cash flow to the opening balance to get the closing balance.","Capital One states the two formulas in plain form. Net cash flow equals cash inflows minus cash outflows. Closing balance equals opening balance plus net cash flow. Two habits make a forecast useful rather than decorative: forecast by payment behaviour, not by hope, and update the forecast often.","
$\"A$
A professional woman calculates finances at a desk with charts and a calculator.
"],["When a customer pays late","Late payment is the most common way a sound forecast breaks. The work is done, the invoice is sent, and the cash arrives weeks after the wages and supplier bills it was meant to cover. The first step is a check of the terms themselves: what payment date was agreed, what date was printed on the invoice, and whether the invoice was sent on the day the work was completed rather than at the end of the month.","For business-to-business work in the United Kingdom, GOV.UK states that statutory interest on a late payment is 8 percent plus the Bank of England base rate, and that a business cannot claim statutory interest if its contract sets a different rate of interest. GOV.UK also states that a business should send a new invoice if it decides to add interest to the money it is owed.","GOV.UK gives a worked example. If a business were owed 1,000 pounds and the Bank of England base rate were 0.5 percent, the annual statutory interest would be 85 pounds, which is 1,000 pounds multiplied by 8.5 percent. Dividing 85 pounds by 365 gives daily interest of 23 pence, and after fifty days that would be 11 pounds 50 pence. Those figures use the example rate in the guidance, not a current rate, so any real claim must use the base rate that applies to the period in question.","The same guidance framework also sets fixed sums for debt recovery costs, depending on the size of the debt, and confirms business-to-business payment periods are normally expected to be within sixty days, with public authorities normally expected to pay within thirty days. Beyond any legal step, invoice on completion, state the payment date clearly, chase on the day after the due date, and keep a short list of which customers pay on time and which regularly pay much later."],["Frequently asked questions","
Is cash flow the same as profit?
No. Profit is revenue minus expenses for a period, recorded when sales are earned and costs are incurred. Cash flow is money actually received and paid in that period. A business can be profitable on paper and short of cash, if customers have not paid yet.
How often should a small business check its cash flow?
Weekly is a practical rhythm, with a monthly forecast alongside it. A weekly check catches a shortfall while there is still time to chase an invoice or talk to a supplier, and a monthly forecast shows the pattern across a quarter, including tax dates and seasonal stock buying.
Does negative cash flow always mean a business is in trouble?
Not always, and the reason matters more than the sign. Negative cash flow from buying equipment, or in the early months of a new business, can be planned and temporary, as Chase for Business notes for early-stage businesses. Negative operating cash flow that continues month after month is a different pattern, and it needs a closer look at pricing, payment terms, and spending.
"],["What to watch next","Watch payment behaviour over the next two quarters, customer by customer, rather than as a single average, which can hide the one large customer whose late payment causes most of the strain. Also watch the dates that repeat: tax payments, rent reviews, and seasonal stock buying."]],author:"Eri-Tech Global Ltd",metaTitle:"Small Business Cash Flow: A Plain Guide to Money In and Out",takeaways:["Cash flow is about timing, not just totals: money is counted when it arrives or leaves the bank account, not when a sale is recorded.","Profit and cash can point in different directions in the same month, because a sale invoiced today may not be paid for weeks while wages and rent fall due now.","A cash flow statement has three parts: operating, investing and financing, and each part answers a different question about where cash came from or went.","A simple forecast, updated often, turns a surprise into a date you can see coming: opening balance, plus money in, minus money out, gives the closing balance."]},{title:"AI in Education: Tutors, Teachers, and the Human Check",slug:"ai-in-education-explained",category:"Technology",date:"2026-11-03",updated:"2026-11-03",primaryKeyword:"AI in education",metaDescription:"AI in education can tutor, plan lessons and draft feedback, but it can also mislead. Learn where it helps, where it fails, and how schools stay in charge.",alt:"A professor gestures toward adult students seated at desks with laptops in a university classroom.",image:"8197534",excerpt:"AI in education can tutor, plan lessons and draft feedback, but it can also mislead. Learn where it helps, where it fails, and how schools stay in charge.",sections:[["What AI in education actually means","AI in education is no longer a trial running in a few wealthy schools. Chatbots answer homework questions, teachers draft lesson plans with AI help, and tutoring tools talk a student through a maths problem one step at a time. The tools arrived fast, and in many schools they arrived before the rules did.","That gap matters, because education is not like shopping or streaming. A wrong suggestion in a shop costs a little time. A wrong answer in a lesson can settle in a student's mind as fact, and a system that writes a student's essay can hide the very learning a teacher needs to see.","This article explains where AI helps in schools and colleges, where it misleads, and what the main guidance from UNESCO, the OECD and the United States Department of Education actually says. The short version: AI works best as a helper that a teacher directs, not as a replacement for teaching, practice, or judgement.","AI in education covers three different kinds of tool, and mixing them up causes most of the confusion. The first is a general chatbot: a tool trained on vast amounts of text that can draft, summarise, translate and answer questions on almost any topic. It is flexible, but it was not built for teaching, and it will answer with confidence even when it is wrong.","The second is a tutoring system built for one subject. These tools have been used in maths and reading for years, and newer versions use chat-style conversation to guide a student step by step instead of handing over a finished answer. The OECD's Digital Education Outlook 2026 notes that tools of this kind, designed with a clear teaching purpose, show more promise than general tools used without a plan.","The third works behind the scenes for teachers and schools: drafting lesson materials, adapting a text to a different reading level, drafting feedback, and helping with marking. Andreas Schleicher, the OECD's Director of Education and Skills, writes that in the best case this help buys teachers time for relationships, richer feedback, and the judgement no machine can copy."],["Where AI helps teachers most","The clearest gains so far are on the teacher's side of the desk. Lesson planning is the example teachers cite most often. In the OECD's TALIS survey of lower secondary teachers in 2024, 57% agreed that AI helps them write or improve lesson plans. A teacher can ask for a first draft of a worksheet or a set of practice questions, then edit the result into something that fits their class.","Feedback is a second gain. Drafting comments on a set of essays takes hours, and AI can produce a first draft of that feedback, which the teacher then corrects. The same applies to adapting materials: a text can be simplified for a student still building reading skill, or extended for one ready for harder work. UNESCO's Global Education Monitoring Report 2023, as described by UNESCO, points to personal support of this kind as especially valuable for students with disabilities and for students living in remote areas.","Teacher training is a newer gain. Early OECD trials found new teachers who practised with simulated students came out better prepared and more confident, though more research is needed across different settings.","None of this removes the teacher's duty to check. England's Department for Education guidance, described in a written parliamentary answer in December 2025, says schools must check AI output for accuracy, and must not put personal or sensitive pupil information into public AI tools without a proper data protection route."],["Where AI helps learners, and where it misleads","For students, the honest picture has two halves. On one side, a good tutoring tool can do what a busy classroom often cannot: wait patiently, explain the same idea a second way, and ask a follow-up question instead of giving the answer.","On the other side, the OECD's warning is plain. When AI removes the effort that learning needs, students finish tasks faster and produce better-looking work, but their understanding is less firmly built. Researchers call the habit that follows \"metacognitive laziness\": the student stops checking their own thinking, because the machine seems to have done it. Studies reviewed by the OECD found that students who studied with a general AI tool produced higher-quality responses, yet their exam performance did not show the gain, and in some cases got worse once the tool was removed.","That result should change how homework and assessment are set. If a task can be completed by pasting a question into a chatbot, the task measures access to the tool, not learning. Teachers are responding by asking for working shown, drafts kept, and oral explanations.","Age matters here too. Schleicher argues that a six-year-old and a sixteen-year-old tapping the same screen are not having the same experience, and younger learners need stronger filters and more guidance. UNESCO's 2023 guidance proposed an age limit of 13 for independent use of generative AI tools in education, alongside data protection rules.","
$\"Two$
Two students study together with books and laptops in a library.
"],["The rules schools are writing now","Schools did not start with rules. In a UNESCO survey carried out in May 2023 among more than 450 schools and universities, fewer than 10% had institutional policies or formal guidance on generative AI.","Since then, the guidance has converged on a small set of shared ideas. UNESCO published its first global guidance on generative AI in education and research in September 2023, built around a human-centred approach: protect data privacy, set age limits, and keep human agency, so AI does not take away chances to build thinking and social skills.","The United States Department of Education took a similar line in May 2023, in a report called Artificial Intelligence and the Future of Teaching and Learning. It said plainly that the people it consulted wanted AI that supports teachers and rejected visions of AI that replace teachers. Its recommendations included keeping humans in the loop, strengthening trust, and involving educators in decisions.","England's Department for Education guidance follows the same pattern: AI should add to teaching, not weaken human oversight, and schools must take care with pupil-facing AI.","A school writing its own policy today does not need to invent this from scratch. It needs to answer, in writing, where AI may be used, where it may not, who checks the output, and what data must never be entered."],["How to use AI for learning without losing the learning","Start with the goal, not the tool. Before opening a chatbot, write down what the student should be able to do afterwards without help. If the goal is to understand fractions, a tool that walks through examples and then asks the student to solve one alone fits.","Second, treat every AI answer as a draft to check. Read it against a textbook, a class note, or a trusted source, and look for invented facts and confident errors. Students who learn this habit early gain a skill that matters far beyond school, because AI output will keep sounding confident whether it is right or not.","Third, keep the hard parts human. Discuss ideas with classmates, explain an answer out loud, and do some work by hand. The OECD's phrase for the risk is worth remembering: when the machine does the thinking for you, the learning does not happen.","Fourth, protect privacy as a habit. Do not paste names, photos, or school records into a public chatbot, and do not let a tool keep a record of a child's conversations without asking what it stores and why.","Finally, build AI literacy as a subject in its own right: the ability to engage with AI, question it, and manage it with critical thinking. A student who can say when to use AI, when to put it aside, and how to check its work is better prepared than one who can only prompt it quickly.","
$\"A$
A student works at a desk with a laptop, books and a notebook.
"],["Frequently asked questions","
Should students be allowed to use AI for homework?
It depends on what the homework is for. If the task is meant to build a skill, such as solving problems or writing clearly, doing it through AI defeats the purpose. If the task is to research, brainstorm, or check understanding, AI can help, as long as the student still does the thinking and the final work is their own.
Will AI replace teachers?
The guidance from UNESCO, the OECD and the United States Department of Education all point the same way: no. AI can draft materials, give practice, and handle routine work, but teaching also involves judgement, relationships, and knowing a particular student. The reports describe AI as a helper for teachers, with humans kept in charge of decisions, especially high-stakes ones.
What should a school check before adopting an AI tool?
Four things: whether the tool was built for education or is a general chatbot; what student data it collects, stores, and trains on; whether its output can be checked and corrected by a teacher; and whether it fits the age of the students who will use it. A tool that fails any of those checks should wait until the school has answers, however popular it is.
"],["What to watch next","Watch whether education-specific tools, built with teachers and tested in classrooms, pull ahead of general chatbots in the next round of trials. The trials so far are early, and the results need to hold across different countries and subjects.","Also watch how age rules and data rules develop. As more countries write AI rules for schools, the question will be whether those rules stay practical for a busy teacher, or become paperwork that schools work around."]],author:"Eri-Tech Global Ltd",metaTitle:"AI in Education: Tutors, Teachers, and the Human Check",takeaways:["AI in education works best when a teacher sets the goal first: tools built for learning, used with a clear purpose, help more than general chatbots used without a plan.","A finished answer is not proof of learning: studies reviewed by the OECD found that students using general AI tools produced better work, yet did worse when the AI was taken away, such as in exams.","Teachers are already using AI, and they are worried too: in 2024, 37% of lower secondary teachers in the OECD's TALIS survey said they used AI in their work, while 72% feared students could pass off AI work as their own.","The guardrails are now clear and shared across countries: keep a human in charge, protect student data, check every AI output, and teach students to judge what AI produces."]},{title:"Streaming Recommendations Explained: How Picks Appear",slug:"streaming-recommendations-explained",category:"Entertainment",date:"2026-11-02",updated:"2026-11-02",primaryKeyword:"streaming recommendations",metaDescription:"Streaming recommendations shape what you see first on Netflix and Spotify. Learn how viewing, listening and taste signals work, and how to take control.",alt:"A couple relaxes on a sofa with popcorn, watching television at home.",image:"6336665",excerpt:"Streaming recommendations shape what you see first on Netflix and Spotify. Learn how viewing, listening and taste signals work, and how to take control.",sections:[["What a streaming recommendation actually is","Streaming recommendations are the suggestions that fill your home screen when you open a video or music app. Instead of showing every title in the catalogue in the same order, the service makes a guess about what you are most likely to play next, and puts those titles where you will see them first.","That guess is not magic, and it is not a fixed list. It is built from what you have watched or listened to before, what people with similar tastes have chosen, and details about each title, such as its genre, cast, or release year.","This article explains how the main systems work, using Netflix for video and Spotify for music as the clearest public examples. You will learn which signals matter most, why two people see different screens, and what you can do when the suggestions stop matching your taste.","A recommendation is a ranked guess. When you open a streaming app, the service has far more titles than you could browse in an evening, so it has to choose an order. The titles at the top of the screen and at the start of each row are the ones its models rank highest for your profile at that moment.","Netflix describes this work as a set of models rather than a single formula. Different models handle different parts of the job, such as predicting which titles you will like, choosing which rows to show, and ranking the titles inside each row. In March 2025, Netflix described a foundation model for recommendations: one large model trained on hundreds of billions of interactions, which smaller features can draw on.","The older ideas still sit underneath. Collaborative filtering looks for members who watch in similar ways to you and suggests what they enjoyed. Content-based filtering looks at the titles themselves — genre, cast, release year, mood — and suggests similar ones. Netflix mixes both, which is why a brand-new show with no viewing history can still reach the right home screens: at first it leans on its details, and as people watch it, viewing data takes over.","That mix also helps lesser-known titles find the viewers most likely to enjoy them. The flip side is the cold-start problem: a title with no early audience gives the system little behaviour to learn from, and the same applies to a brand-new user."],["The four signals services use most","Netflix lists four groups of inputs, as reported by Simplilearn and Stratoflow. The first is your own activity: your viewing history and how you rated other titles. Finishing a series, stopping a film after ten minutes, and giving a thumbs up or thumbs down all send different signals.","The second is other members with similar tastes and preferences. If many people who watched the same documentaries as you later enjoyed a particular drama, the system may suggest that drama to you, even if you have never searched for it. This is the \"people who liked that also liked this\" pattern, applied at very large scale.","The third is information about each title: genre, categories, actors, release year, and similar details. Title details let the system connect a new release to titles you already liked, and they help it group titles into rows with a theme, such as suspenseful films or witty dramas.","The fourth is context: the time of day you watch, the languages you prefer, the devices you use, and how long you watched a title. Netflix says its system does not use demographic details such as age or gender, so two members of very different ages who watch the same kinds of shows can receive similar suggestions.","Search is a separate route into the same catalogue. Netflix executives wrote in 2015 that recommendations influenced about 80 percent of hours streamed, with the rest coming from search. That figure is old, so treat it as a historical snapshot, not a current measure. The practical point is simpler: if you only follow the home screen, you only see what the system already expects you to like."],["Why two people see different home screens","Open the same app on two accounts and the screens will differ in four ways. Netflix personalises which rows appear and in what order, which titles sit in each row, the order of titles inside each row, and, for many titles, the artwork shown. The strongest matches tend to sit in the top rows and at the start of each row, because that is where viewers look first.","Artwork is the most visible example. Netflix creates several images for many titles and uses machine learning to choose which one to show each member. Simplilearn gives the example Netflix itself used for Good Will Hunting: a viewer who watches many romantic films might see an image of Matt Damon and Minnie Driver, while a viewer who watches many comedies might see Robin Williams. The film is the same; the picture that introduces it is not.","Rows themselves come from different jobs. Stratoflow lists the kinds Netflix described in its 2015 paper: a ranker for genre rows, a ranker for the best picks from the whole catalogue, a Trending Now row, a Continue Watching row, and similarity rows that power \"Because You Watched\" suggestions. A page step then picks and orders the rows, balancing relevance with variety, because one account often serves a whole household in different moods."],["Music picks work a little differently","Music recommendations follow the same basic pattern — past listening, similar listeners, and track details — but the unit is smaller. A song lasts minutes, not hours, so a service can learn from many more plays, skips, and saves in a single week. That makes playlists a natural home for music suggestions.","Spotify's Discover Weekly is the best-known example. It first appeared in July 2015 as a playlist that appears each Monday in every Spotify user's account. Fast Company reported that it analyses a person's listening history, with a focus on what they played recently, then compares that with the playlisting behaviour of others. Scanning millions of playlists, it finds tracks commonly listed alongside music the listener already knows, and groups them into a new personal playlist.","The result is built to feel familiar: a playlist, not a new screen to learn. Matthew Ogle, the Discover Weekly product owner at the time, told Fast Company that the team removed much of the work of discovery by putting suggestions in a format listeners already used.","Spotify has since added a more direct control. In September 2026, Spotify rolled out Taste Profile in beta to Premium listeners aged 18 and older in the United States, after earlier testing in New Zealand. It shows Spotify's brief interpretation of your taste across music, podcasts, and audiobooks, and lets you ask for changes in plain words, such as more of a genre or more variety. Your notes act as guidance for the Home feed, not strict rules: Spotify says Taste Profile cannot follow an artist for you, and cannot apply absolute rules such as \"always show\" or \"never show\". Changes typically appear within a few hours.","
$\"A$
A young person listens to music with headphones and a phone.
"],["How to steer your own recommendations","Start with profiles. Suggestions, ratings, and viewing activity belong to a profile, not to a whole subscription. If several people share one profile, their tastes mix, and the suggestions will reflect the mix rather than any one person. Giving each regular viewer a separate profile is the simplest fix, and it costs nothing extra on most services.","Next, give clear feedback. Rate titles you have a view on, using the thumbs controls where they exist. On Spotify, saving a track, adding it to a playlist, or skipping it quickly all send signals, with full listens carrying more weight than quick skips.","Then clean up the history that misleads the system. On Netflix, you can hide a title from viewing activity, and hidden titles stop being used for recommendations unless you watch them again. On Spotify, you can exclude a specific playlist or track from your taste profile, so a sleep playlist, a child's music, or a one-off party mix stops shaping your suggestions.","Finally, search on purpose. Recommendations learn from what you play, so playing one new kind of title is often the fastest way to open a new row or playlist. New activity carries more weight than old activity, so your suggestions can shift within days, not months.","There are limits to all of this. A recommendation cannot make a title available in your country, and a high match does not promise you will enjoy it. The aim is practical: a home screen that reflects your current taste, with room left for something new.","
$\"A$
A person browses shows on a smartphone at home.
"],["Frequently asked questions","
Why do my recommendations change over time?
Because the system learns from recent activity. New viewing and listening carry more weight than older choices, so as your habits change, the rows and playlists change with them.
Can I reset my recommendations?
There is no single reset button on the services described here, but you can rebuild the signal. Use a separate profile, hide or exclude titles that do not reflect your taste, rate what you watch, and build fresh activity around the kinds of titles you want more of.
Do recommendations use my age or gender?
Netflix says its recommendation system does not use demographic information such as age or gender. Its suggestions are read from what you watch, not from who you are on paper. Spotify's Taste Profile is limited to Premium listeners aged 18 and older in the United States during its beta, but that is an eligibility rule for the feature, not a claim that age drives the music picks.
"],["What to watch next","Watch how control tools develop. Spotify's Taste Profile is still in beta, with no announced date for a wider rollout, so the question is whether direct, plain-word controls become standard across music and video apps, or stay a limited test.","Also watch the balance between familiarity and discovery. Services need to show titles you will play, but also surface new work, or home screens narrow over time."]],author:"Eri-Tech Global Ltd",metaTitle:"Streaming Recommendations Explained: How Picks Appear",takeaways:["Streaming recommendations are predictions, not certainties: they rank titles by how likely you are to play them, based on past behaviour and title details.","Netflix says its system uses viewing history and ratings, similar members, title information, and context such as time of day, language, device, and watch length — but not age or gender.","The home screen is personal in several ways at once: which rows appear, which titles sit in each row, their order, and sometimes even the artwork shown for a title.","You can steer the system: keep profiles separate, rate what you watch, hide or exclude titles that do not reflect your taste, and search for new kinds of titles on purpose."]},{title:"Digital ID Systems Explained: How Identity Checks Work",slug:"digital-id-systems-explained",category:"Politics & Policy",date:"2026-11-02",updated:"2026-11-02",primaryKeyword:"digital ID systems",metaDescription:"Digital ID systems let governments check who you are online without paper forms. Learn how enrolment, checks and wallets work, and what safeguards matter.",alt:"Close-up of hands holding a passport and a smartphone outdoors, with luggage nearby.",image:"20805604",excerpt:"Digital ID systems let governments check who you are online without paper forms. Learn how enrolment, checks and wallets work, and what safeguards matter.",sections:[["What a digital ID system is","Digital ID systems are the official ways governments record who a person is and then check that identity later, without relying on paper alone. A person enrols once, receives a digital record or credential, and presents that credential when a service needs to confirm identity.","Passports and driving licences have long served as proof of identity. What is changing is how that proof is stored, shared and checked: on a phone, through an online account, or by a number linked to a central record. The World Bank's Identification for Development guide describes digital ID systems as systems that use digital technology through the whole identity process, from capturing and checking data, to storing it, managing credentials, and verifying identity later. This article explains the parts most systems share, looks at examples in use today, and sets out the arguments made for and against them. It does not take a side.","A digital ID system answers a narrow question: is the person in front of the service the person the record describes? It does not, by itself, decide whether that person qualifies for a benefit, a loan or a licence. Those decisions still sit with the service that asks for the check.","Enrolment is the first step. A person gives basic details, such as name and date of birth, and in many systems also gives biometric details, such as a fingerprint, an iris scan or a face scan. The system checks those details where it can, and it checks for duplicates, so that one person does not hold two identities in the same system.","The second step is the credential: a number, a card, an online account or an app-based wallet. It points back to the record created at enrolment. It is not the record itself, and in a well-designed system it carries only the details needed for the check at hand. The third step is verification, sometimes called authentication: the system compares what the person presents now with what was recorded at enrolment. In some systems the answer is a simple match or no match; in others, the system shares a specific detail, such as a name or an age band."],["The three steps in practice","In the United Kingdom, the credential is an online account: GOV.UK One Login. GOV.UK says that at the moment One Login works only with some government services, and it gives Universal Credit as an example of a service it does not yet work with. Over time, GOV.UK says, One Login will replace other ways to sign in to services on GOV.UK, including Government Gateway.","To prove identity with One Login, GOV.UK lists three routes. The first is the GOV.UK One Login app, which checks that the photo ID is real, that the user is a real person, and that the user is the same person as in the photo ID. The second is answering security questions online, using details such as a mobile phone contract, bank accounts or loans, plus details from a passport, driving licence or current account. The third is a Post Office visit, where staff scan the photo ID and take a photo of the person; GOV.UK says the result usually arrives by email within a day. Once the check is complete, GOV.UK says the identity information is saved to the account, so the person does not need to prove identity again next time.","
$\"A$
A person unlocks a smartphone with a passcode.
"],["Three models in use today","The European Union model is a wallet, not a single sign-in. The European Commission describes the EU Digital Identity Wallet as a mobile app that lets a person access online and offline public and private services, store and share digital documents, and create binding signatures. Each Member State will provide at least one wallet, built to common specifications. The Commission lists uses that include applying for a passport, filing taxes, opening a bank account, and signing contracts.","Regulation (EU) 2024/1183, in force since 20 May 2024, sets the framework. A legal analysis of the timetable puts two dates at the centre: by 24 December 2026, each Member State must offer its citizens at least one free wallet, and by 24 December 2027, businesses in designated sectors, such as banking, energy, transport, healthcare and telecommunications, and major platforms must accept it as a means of authentication. The same analysis stresses that use of the wallet will always be voluntary for citizens.","A key feature of the EU wallet is selective disclosure: sharing only the detail a service needs, for example proving that a person is over 18 without showing a full date of birth.","Nigeria's model is built around a single number. BusinessDay reports that the National Identity Management Commission (NIMC) has announced more than 136 million enrolments into the National Identity Database, and that a new National Identity Management Commission Act in 2026 replaces the 2007 law and positions the National Identification Number (NIN) as Nigeria's primary identity under a \"one person, one identity\" policy. BusinessDay also notes the other side of that figure: with the population estimated at over 240 million, tens of millions of people, particularly children, rural residents and vulnerable groups, are yet to obtain a NIN, even as the NIN increasingly serves as a gateway to government programmes, financial services, telecom registration, passports, tax administration and social schemes.","
$\"Flags$
Flags outside the European Parliament building.
"],["What supporters point to, and what critics raise","Supporters, including the European Commission in its own description of the wallet, point to practical gains: easier access to public and private services, data shared only as far as necessary, stronger security standards, better fraud prevention, and less administration and lower cost when a business checks a customer's identity. For governments, a single verified record can also cut duplicate records across departments, a point Nigeria's budget minister made when he said the NIN should serve as a single, universally accepted identity standard, as reported by BusinessDay.","Critics raise three concerns, each reflected in the official sources themselves. The first is exclusion: a system that needs a phone, a network connection or a particular photo ID can leave out people who lack those things, and the Nigeria example shows the gap in plain numbers. The second is control: a legal analysis of the EU wallet records the criticism that a state-backed identity system could be seen as a tool for control, particularly if later linked to uses not currently planned. The regulation tries to limit this risk through voluntary use, pseudonyms, a ban on requiring the wallet when another method would do, and the traceability dashboard, but whether those safeguards work will depend on implementation and on independent supervisory bodies. The third is what happens when a check goes wrong: a wrong name, a failed fingerprint match or a lost phone can block access, so the World Bank's principles call for clear mandates, independent oversight and a route to complain and seek a remedy."],["Questions to ask about any system","First, is use voluntary, and is there a workable alternative for people who do not use it? The EU wallet is voluntary for citizens, while Nigeria's NIN is presented as a primary identity for access to services, so the answer varies by country and must be checked in the law, not in a press release. Second, what data is collected, and what is shared at each check? A system that shares only the detail a service needs is different from one that hands over a full record. The EU wallet's selective disclosure is one design answer; a simple yes-or-no reply to a check is another.","Third, who can see the data, and for what purpose? The World Bank blog says data should be accessed only by authorised users for purposes agreed in advance. If a proposal does not name those purposes, that is a gap, not a detail. Fourth, how does a person correct an error, replace a lost credential, or complain? Look for a named body, a time limit and a route that does not require the very credential that has failed. Fifth, what happens to people who cannot enrol in the usual way? Look for in-person routes, such as the Post Office option in the United Kingdom, and for help from a trusted person, which GOV.UK explicitly allows for One Login.","For a small business, the practical version is shorter: ask which credential is accepted, what data the check will share, and what fallback exists if the check fails."],["Frequently asked questions","
Is a digital ID the same as a national identity card?
No, not always. A national identity card is usually a physical card. A digital ID system is the record and the checking process behind a credential, which may be a number, an online account or a wallet app. A card can be part of a digital system, and a digital system can exist without a card, as with an online account.
Do I have to use the EU Digital Identity Wallet?
According to the legal analysis of Regulation (EU) 2024/1183 cited in this article, use of the wallet will always be voluntary for citizens. Member States must offer a wallet, but citizens are not required to take one up.
What should I do if an identity check fails?
Start with the service that asked for the check, and use its published help route: GOV.UK, for example, offers help from the One Login team and allows a trusted person to help, within stated limits. Keep the exact error message and the date, and if the record itself is wrong, ask the issuing body how to correct it.
"],["What to watch next","Watch three things: whether EU Member States meet the December 2026 wallet deadline; whether services that must accept the wallet by December 2027 ask only for the data they need; and, in Nigeria, whether enrolment reaches the people BusinessDay identifies as still unregistered, and whether the new Act's safeguards are put into practice."]],author:"Eri-Tech Global Ltd",metaTitle:"Digital ID Systems Explained: How Identity Checks Work",takeaways:["Digital ID systems share three steps: enrolment, a credential, and a later check against the record.","The United Kingdom's GOV.UK One Login saves a completed identity check so it can be reused across services, with three routes: an app, security questions online, or a Post Office visit.","In the European Union, each Member State must offer at least one free digital identity wallet by 24 December 2026, and use of the wallet by citizens is voluntary.","The World Bank's ten principles for identification stress coverage without discrimination, privacy and control by design, a clear legal framework, and independent oversight with a route to complain."]},{title:"AI Customer Service for Small Businesses Explained",slug:"ai-customer-service-small-business",category:"Business",date:"2026-11-02",updated:"2026-11-02",primaryKeyword:"AI customer service small business",metaDescription:"AI customer service helps small businesses answer routine questions fast, day and night. Learn what to automate, what to keep human, and how to start.",alt:"Close-up of a female call center agent using a headset while working at her desk.",image:"8681899",excerpt:"AI customer service helps small businesses answer routine questions fast, day and night. Learn what to automate, what to keep human, and how to start.",sections:[["What AI customer service means in a small business","AI customer service for small businesses is, at its simplest, a way for a small team to answer routine questions without being at a desk around the clock. A customer asks about opening hours, delivery times, or an order, and a chatbot or help page gives an answer drawn from the business's own information. When the question is harder — a refund, a complaint, or a request that needs judgement — the conversation passes to a person, with the earlier messages attached.","That split is the whole idea. Small firms rarely lack customers; they lack spare hands. Salesforce's seventh State of Service report, based on a survey of 6,500 service professionals in 40 countries, found that 82% of service professionals agree customer expectations are higher than they used to be, while representatives spend only 46% of their time with customers, with the rest taken up by admin and internal tasks. AI customer service aims to move the routine work out of the way so the people on the team can spend their time on the customers who most need them.","Three tools sit behind the phrase, and it helps to tell them apart. A knowledge base is a set of searchable help articles and answers on your own website. A chatbot is a chat window that answers questions in conversation, often by finding the right help article or asking a few short questions first. An AI agent goes a step further and can carry out simple tasks, such as checking an order or updating account details, rather than only giving information.","For a small firm, the practical difference is size. You do not need all three at once, and you do not need a large system. A help page and a simple chatbot on your website or messaging app, fed with your own prices, policies, and delivery details, is a start.","The research also puts the trend in scale. Salesforce reports that 69% of service professionals say their organisation uses at least one form of AI, and 39% say they use agentic AI, the kind that can take actions. Service teams in the survey estimate that AI resolves 30% of cases today, and expect that share to reach 50% by 2027. Those are survey estimates, not a promise for any one business — but they explain why customers increasingly meet AI first when they ask a question."],["The requests worth automating first","Zendesk's analysis of 165 million tickets from paid accounts in one quarter gives small firms a useful map. A quarter of incoming tickets were not real service requests at all — spam, system notices, and confirmation messages. Of the genuine requests, 49% were repeatable tasks with set answers, such as checking an order status, updating account details, or asking for a receipt. A further 31% came from something going wrong elsewhere in the business, such as a missed delivery or a delayed refund. The remaining 20% were high-value moments — complaints, cancellations, and account problems — where judgement and care matter most.","The failure cases need a different approach. A customer reporting a parcel marked delivered that never arrived does not want a tracking link; they want someone to look into it. AI can still help by pulling up the order and routing the case to the right person — but the fix itself needs a human. The same is true of the high-value 20%: a cancellation request may look simple, yet it can hide repeated problems or billing frustration that only a person will spot.","
$\"A$
A customer chatting on a smartphone.
"],["Keeping the human handoff easy","The most common complaint about automated service is not the automation itself. It is being trapped in it. HubSpot's research notes that 49% of customers cite not being able to reach a real human as a friction point of AI self-service. Zendesk's 2026 trends research found that 74% of consumers are frustrated when they have to repeat information, while 81% want the next person to pick up the conversation without going back over what was already said.","So the handoff is a design job, not an afterthought. Every automated answer should carry a plain route to a person: a button, a phone number, or a message option that works during stated hours. When the conversation moves to a person, the earlier messages should move with it, so the customer does not have to start again. Salesforce found that 85% of service professionals with voice AI say handoffs to human representatives are smooth for customers — a sign that this part can work well when it is planned rather than bolted on.","Transparency helps too. Zendesk reports that 95% of consumers expect an explanation when AI makes a decision, and 79% say plain-language reasoning matters. In practice that means saying, in simple words, what the system checked — for example, \"your order left our depot on Tuesday and is due Thursday\" rather than a bare status code. It also means saying when the system does not know, and offering a person instead of guessing."],["Setting it up in small steps","A small firm can set up AI customer service in a few steps, without a large budget or a technical team.","First, list the questions you actually get. Look at recent emails, messages, and call notes and pick the ten most frequent. If the same question appears again and again, it belongs in the first version. If a question needs judgement, money, or personal data, it stays with a person.","Second, write one clear answer for each question, in the words customers use. Short answers work better than long policy pages. Include the exceptions: what happens when an order is late, what proof is needed for a return, and who to contact when the standard answer does not fit. An AI tool can only repeat what it is given, so a vague answer becomes a vague chatbot.","Third, connect the tool to one source of truth. Salesforce found that firms which bring their service channel data together in one place are 1.4 times more likely to call their AI work very successful than firms with scattered systems, while 44% of service leaders say disconnected systems have delayed or limited their AI work. For a small firm, that can be as simple as one up-to-date price list, one delivery policy page, and one inbox, rather than answers spread across old posts and message threads.","Fourth, test it before customers do. Ask friends, staff, or regular customers to try the ten questions, plus a few awkward ones, and fix the answers that confuse them. Set a rule for what the system must never do on its own: never promise a refund, never change an account, never quote a price it cannot verify. Those stay with a person until the business is sure the process is safe.","
$\"Call$
A support team working together at a desk.
"],["How to tell whether it is working","A smaller inbox is not, on its own, proof of success. Zendesk's research makes the same point: 78% of customer experience leaders in its 2026 trends survey say AI requires firms to rethink how they measure success, and a request that leaves the queue is not necessarily a request that was solved.","Four measures give a fairer picture. The first is completed answers: did the customer get what they came for, without needing to ask again? The second is re-contact rate: how often does the same customer return with the same problem? The third is customer satisfaction, asked with one short question after the interaction. The fourth is first-contact resolution, which Zendesk's research links closely to loyalty — 85% of customer experience leaders in its survey say customers will leave brands that cannot resolve issues on first contact.","Watch the human side as well. Salesforce reports that among representatives at firms with AI, 83% say they have better career prospects because of it, 82% say it has helped them build new skills, 81% say it makes them more productive, and 80% say their job is less stressful. If your team reports the opposite, the setup needs adjusting, not more automation.","One honest warning belongs here. AI customer service saves time on routine work; it does not fix a broken delivery process, a wrong price list, or an unclear returns policy. Zendesk's ticket analysis found that nearly a third of genuine requests began with a failure elsewhere in the business. Fixing those causes will cut support demand more surely than any chatbot."],["Frequently asked questions","
Do small businesses need AI customer service, or is it only for large firms?
No, it is not only for large firms. The tools that suit a small team are the simplest ones: a help page, a chatbot answering the most common questions, and a clear route to a person. Salesforce's small-business guidance notes that AI agents can handle FAQs, order inquiries, and conversation summaries, which are exactly the jobs that eat up a small team's day.
Will customers be annoyed if a chatbot answers instead of a person?
Some will be, if they cannot reach a person when they need one. Most customers accept automated help for simple questions — HubSpot reports that 78% of customer relationship leaders say customers prefer to solve issues on their own — but the same research shows frustration when a real person is out of reach. Keep the human route visible and pass the conversation history along.
What should AI customer service never handle on its own?
Refunds, account changes, cancellations, complaints, and anything involving personal or payment details should stay with a person, or at least need a person's approval, until the process is tested and trusted. The same applies to any answer the system cannot verify from your own records. When in doubt, let the system gather the details and hand over, rather than guessing.
"],["What to watch next","Watch for AI tools that carry conversation history across channels — web chat, messaging apps, and phone — without making customers repeat themselves, and for clearer rules on explaining AI decisions to customers."]],author:"Eri-Tech Global Ltd",metaTitle:"AI Customer Service for Small Businesses Explained",takeaways:["AI customer service works best on routine, repeatable questions — order status, opening hours, prices, policies — while people handle complaints, refunds, and sensitive cases.","Customers now expect fast, accurate answers at any hour: Zendesk's 2026 trends research found 74% of consumers expect round-the-clock service because of AI, and 86% say fast responses and accurate answers shape their buying choices.","Start with your ten most-asked questions, write clear answers for them, and add one easy route to a person for everything else.","Judge the result by completed answers and customer satisfaction, not by how few messages reach a human — a question that leaves the queue unsolved is not a win."]},{title:"AI in Farming: How Data Helps Growers Decide",slug:"ai-in-farming",category:"Technology",date:"2026-11-02",updated:"2026-11-02",primaryKeyword:"AI in farming",metaDescription:"AI in farming turns field photos, soil readings and weather data into plain advice. Learn what helps growers, what small farms can use, and its limits.",alt:"A tractor working on a lush green field surrounded by rich greenery under a clear blue sky.",image:"16777933",excerpt:"AI in farming turns field photos, soil readings and weather data into plain advice. Learn what helps growers, what small farms can use, and its limits.",sections:[["What AI in farming means","AI in farming is not a robot taking over a farm. In most cases it is a set of tools that read measurements — photos of leaves, soil moisture readings, weather records — and turn them into advice a farmer can check in the field. A phone photo can point to a possible pest problem, a sensor can say one corner of a field is dry while the rest is fine, and a satellite image can show crop stress before it is easy to see from the ground.","That plain version matters, because much of the talk about farm technology skips the middle step: data has to be gathered, checked, and matched to local conditions before advice is worth acting on. Done well, AI in farming can help a grower use water, fertiliser and spray more carefully, catch problems earlier, and plan work with better timing. Done badly — with poor data, no signal, or advice built for a different climate — it can waste money and trust.","Precision agriculture is the older idea behind most of this work: not every part of a field needs the same treatment. One patch may be short of nitrogen, another may hold water after rain, and a third may carry more weeds. Measuring those differences lets a farmer treat each patch on its own terms.","AI adds pattern-finding to that idea. A computer vision system — software trained to recognise things in images — can be taught to tell a crop plant from a weed, or a healthy leaf from one showing signs of disease. The United States Department of Agriculture's Digital Agricultural Systems Hub, known as DASH, brings together images and sensor data from satellites, drones, field robots and farm equipment to map weeds and crop stress, using an image library of more than 50 terabytes of labelled crop and weed images to train its models.","The Food and Agriculture Organization of the United Nations (FAO) puts this work in a wider frame. Its 2022 State of Food and Agriculture report looks at agricultural automation — a range from tractors to artificial intelligence — through 27 case studies from around the world. Automation, it finds, can make food production more efficient and more environmentally friendly, and ease labour shortages — but uneven adoption can deepen inequalities, especially for small-scale producers, young people and women."],["Seeing trouble early: crops, weeds and pests","The most useful farm AI today is often a second pair of eyes. A drone flying over a field takes photos that software can sort into areas to check first. A camera on farm equipment can map plants as the machine moves, and a satellite image can track drought over a wide area. In each case the farmer still walks the field and makes the call — the tool narrows down where to look.","DASH shows how this works in practice. Its ModCam system, a modular camera fitted to equipment such as spray booms, uses models trained on its image library to map plants in fields and research plots. The same platform is being used for precision nitrogen management with cover crops, for mapping weeds, and with sugar beet growers to map cercospora leaf spot, a disease, in Fargo, North Dakota.","Drone research tells a similar story. Researchers at the USDA Agricultural Research Service and Auburn University have been testing drones in row crops, pasture and specialty crop systems, gathering crop, pest and soil information and carrying out pesticide and cover crop work. One effort is working out how drone imagery can detect weeds in a cotton field, so herbicide is applied only when weed pressure justifies it.","The value here is timing. A pest or disease found a week earlier is often cheaper to deal with, and a weed map means spray goes where weeds are, not across the whole field. None of that removes the need for a farmer's judgement — a photo can be misread, and a model trained on one crop may not read another well.","
$\"A$
A drone flying over a crop field.
"],["Water, fertiliser and timing: smaller doses, better placed","Water and fertiliser are two places where careful placement pays twice: the farmer spends less on inputs, and less runs off into soil and waterways. AI helps by joining up measurements that used to sit apart — soil moisture, weather forecasts, plant growth stage, and past yields — into a recommendation for a specific patch at a specific time.","Satellite monitoring is one part of that picture. FAO runs the Agricultural Stress Index System, which uses satellite imagery to monitor drought, and its next generation is set to integrate AI to improve accuracy and speed. On the ground, soil sensors can report moisture through the day, so irrigation can be timed to what the soil actually needs rather than to a fixed rota.","Small growers should ask of any tool that promises savings: savings compared with what, measured where? A result from a large, flat farm may not repeat on a small, hilly plot. The farm should shape the tool, not the other way round."],["Advice on a phone: what changes for small farms","For many small farms, the most important AI tool will not be a drone or a sensor network. It will be a phone. FAO is working with Digital Green, a non-profit organisation, to bring AI-supported advisory services to farmers through mobile apps, with pilots in Ethiopia and more planned in Mozambique, using datasets built for local farming needs rather than general internet data. Farmers can ask about a crop problem and get advice shaped for their area, in local languages.","According to Digital Green, as reported by FAO, traditional advisory services could cost around $30 per farmer; digital tools brought that to $3, and with AI it could go as low as $0.30. Those are reported figures from the organisation running the service, not a promise for every farm — but they explain why advisory services are often the first AI tool to reach small farms.","Shared services point the same way. FAO's 2022 report describes hire-a-tractor services in Africa and Asia that let small farmers use costly equipment without buying it. The same logic now applies to drones and sensors: a farmer can hire a flight or a mapping service, rather than owning the equipment.","None of this works without the basics. FAO's innovation chief, Vincent Martin, names the obstacles plainly: access to quality local data, training for farmers, and a policy environment that supports new tools, plus responsible use so AI does not reinforce existing inequalities. A failed season can devastate a household — so a tool untried on farms like yours deserves a small trial first, on one field, for one season."],["Where it still falls short","The honest limits of AI in farming are mostly not about the software. They are about signal, data, cost and trust.","Connectivity comes first. A joint FAO and International Telecommunication Union study of digital agriculture in 47 sub-Saharan African countries, published in 2022, found that about one-third of the region's population was still out of reach of mobile broadband signals, and only 28 percent had any access to the internet. Its authors called for urgent investment in last-mile connectivity and national digital agriculture strategies. A tool that needs a constant connection will not serve a farm that does not have one.","Data quality is the second limit. AI systems learn from examples, and examples from one region do not always transfer: a weed model trained in one country may misread weeds in another. FAO's innovation team says quality local data is essential, and is exploring how Farmer Field Schools — groups where farmers learn together in the field — can help gather it. Until then, advice is a suggestion to check, not a verdict.","Cost and skills follow. Sensors, drones and subscriptions add up, and a tool that needs digital skills its users have not been taught will sit unused. FAO's 2022 report notes that limited rural infrastructure, such as connectivity and electricity, holds back newer technologies in low- and middle-income countries. As early as 2005, Japan had more than 400 tractors per 1,000 hectares of arable land, compared with just 0.4 in Ghana.","There is also a jobs question, and FAO treats it with care. Its 2022 report concludes that fears about automation creating unemployment are not borne out by history, since automation tends to ease labour shortages. But it also notes that automation can lead to unemployment where rural labour is plentiful and wages are low, and that in those places policy should focus on social protection for the least skilled workers. The question for any farm community is not only \"does this tool work?\" but \"who gains, and who loses work?\"","
$\"A$
A farmer checking advice on a tablet in a field.
"],["Frequently asked questions","
Does AI in farming replace the farmer?
No. The tools described here narrow down where to look, when to act, and how much to apply — but the farmer still walks the field, checks the plant, and makes the final call. A model can misread a photo, which is why researchers describe their systems as support for decisions, not replacements for them.
Can a small farm use these tools without buying a drone?
Yes, in many cases. Phone-based advisory services, hire-a-drone or mapping services, cooperatives and extension advisers all let a small farm use the result without owning the equipment. Start with the cheapest option that answers a real question on your farm.
How do I judge an AI farming tool before paying?
Ask four questions: has it been tested on farms like yours, in your climate and on your crops? Does it work with the connectivity you actually have? What does it cost per season, including any subscription? If the seller cannot answer those plainly, wait.
"],["What to watch next","Watch for advisory services built on local data — FAO's pilots in Ethiopia and Mozambique are testing exactly that — and for drone services sold by the visit, not by the machine."]],author:"Eri-Tech Global Ltd",metaTitle:"AI in Farming: How Data Helps Growers Decide",takeaways:["AI in farming mostly turns field measurements into advice, spotting patterns in photos, sensor readings and weather data across a whole field.","The clearest uses today are early warning for crop stress, pests and disease, and placing water, fertiliser and spray only where needed.","Small farms can benefit without buying expensive kit, often through a phone, a shared service, or an adviser who carries the equipment.","The main limits are practical: patchy connectivity, poor local data, cost, and advice that has not been tested on farms like yours."]},{title:"AI in Video Games: How Game Worlds React to You",slug:"ai-in-video-games",category:"Entertainment",date:"2026-11-01",updated:"2026-11-01",primaryKeyword:"AI in video games",metaDescription:"AI in video games lets characters answer in their own words and remember what you did. Learn how it works, where it helps, and where it still falls short.",alt:"Close-up of hands holding a black game controller against a brown background.",image:"7046932",excerpt:"AI in video games lets characters answer in their own words and remember what you did. Learn how it works, where it helps, and where it still falls short.",sections:[["What AI in video games means","AI in video games is changing what happens when you talk to a character, walk into a town, or try a new way through a level. In older games, most of what a character said was written in advance. A shopkeeper had a set list of lines, and you heard the same ones each time you visited. New AI tools give some characters more room to respond to what you actually do and say, within limits set by the people who made the game.","The phrase AI in video games covers a wide range of tools, and that breadth causes much of the confusion around it. At one end, AI helps people build a game: suggesting code, drafting a first version of dialogue, testing a level, or filling in routine art and animation work. At the other end, AI runs inside the finished game. It decides how an enemy moves, what a shopkeeper says when you return, or how a companion reacts when you change your plan.","Older games already used AI, just not the kind that writes sentences. For decades, designers used rules and decision trees: if the player is close, the guard moves closer; if the player is hurt, the enemy presses its attack. Those systems were predictable, which let a designer test every path.","Language models add a different option: a character can form a reply from the current situation, rather than picking from a fixed list."],["Characters that answer instead of repeating lines","The clearest example of a live AI character is the non-player character, often shortened to NPC. These are the people and creatures in a game world who are not controlled by a player: the innkeeper, the guard, the companion, the rival. In many games, their lines, known as barks, are short phrases triggered by an event, such as entering a room, starting a fight, or passing by on a street.","Ubisoft's research team, La Forge, built a tool called Ghostwriter to help with exactly this kind of writing. According to Ubisoft, Ghostwriter produces first drafts of barks, and scriptwriters then choose and edit the versions they like. The writer creates a character and a type of interaction, and the tool proposes variations, offering two options at a time for the writer to compare. After thousands of such choices by people, Ubisoft says the tool becomes more effective and accurate. The main story stays with human writers; the tool takes on repetitive first drafts.","A newer step is the character that answers during play, not only on paper. NVIDIA's ACE system is a set of tools for in-game AI characters. In a developer post dated 27 October 2026, NVIDIA said its newest small language model for this work, Nemotron 3.5 Bolt E4B, runs on the player's device, uses a 4GB runtime memory budget, and can use facts from the game itself, such as an inventory item or a quest step, rather than guessing. NVIDIA also said the model supports 35 languages.","NVIDIA gave two public examples from 2026. PUBG rolled out AI teammates in a public beta powered by an earlier Nemotron model. Aniimo, a game built around AI pets that respond to a player's voice, used a second-generation model and is set for release in early 2027, according to NVIDIA. A separate report by Tech Times, covering the same NVIDIA update, added that Mecha Break became the first shipped game with an NVIDIA ACE-powered NPC earlier in 2026. Each example gives AI a defined job, rather than handing it the whole game.","
$\"A$
A player gaming on a couch with a controller.
"],["Worlds that change with how you play","Studio Atelico, an independent game studio, opened early access on 29 October 2026 to an engine built for this kind of play. According to GamesBeat, which interviewed the studio's chief executive, Piero Molino, the Atelico AI Engine runs language models, image generation, speech systems, and character behaviour entirely on the player's device, and it works with the Unity, Unreal Engine, and Godot engines. Its Character Behavior System lets developers define a character's persona, backstory, relationships, and motivations, while collecting memories that shape later actions.","Atelico's own first game shows the other side of the same engine. In Bobium Brawlers, a turn-based card and dice game, players describe a character in plain language and receive a portrait and a playable deck made on their phone. GamesBeat reports that the game itself has not been released yet, and that the studio has not announced any outside customers for the engine. That detail matters. A tool can be promising in a studio's own game and still be unproven in other teams' hands. Early access means developers can request access and try it, not that it is already a standard part of how games are made.","There is also a practical reason on-device play matters. When AI runs on the player's device, there is no wait for a server to reply, and no fee for each answer sent to a cloud service. GamesBeat notes that Studio Atelico argues this keeps player data on the device. The trade-off is that the model must fit alongside graphics, sound, physics, and animation."],["The quiet work behind the scenes","Most AI use in games never reaches the player as a talking character. It sits in the daily work of making a game: writing code, drafting text, testing, and planning. Unity's 2026 Game Development Report, based on a survey of 300 developers who use the Unity engine, gives a useful picture of that balance. According to coverage of the report by Wccftech, 62% of those developers use AI tools for coding assistance, 44% for writing and narrative design, and 40% for NPC behaviour. Market research followed at 37% and automated playtesting at 35%. Only 5% said they do not use AI at all.","A second report on the same Unity survey, by GamesMarket, lists the same top figures and adds context about project size. It says 52% of developers surveyed now focus on smaller, more manageable projects, and that 46% spend between one and three months on prototyping. Smaller teams with shorter projects gain the most from tools that speed up first drafts and routine checks.","Wccftech also adds a caution. Its coverage notes that the survey does not specify whether the AI-assisted work ends up in the final game, or whether it is used for prototypes and drafts that human developers later replace. A team can use AI to draft dialogue, test a level, or suggest code, and still ship a game in which every line and system was reviewed, edited, and approved by people.","The same caution applies to efficiency claims. Wccftech reports that 79% of developers at studios with more than 150 team members said AI tools helped them improve efficiency. That is a self-reported survey result from larger studios, not a measured count of hours saved across the whole industry."],["Where it still falls short","Live AI characters bring problems that scripted lines do not. A scripted line can be checked once and trusted to stay the same. A generated reply can be wrong about the game's own facts, can repeat itself, can break character, or can say something the developers would not approve. That is why the examples here all keep a person in charge: Ubisoft's writers choose and edit drafts, NVIDIA's tools use facts from the game itself, and Atelico's engine adds filters so outputs stay within the game's own rules. None of these checks removes the risk entirely.","Cost and hardware form a second limit. A model that runs on a player's device must share memory with the rest of the game, and players do not all own the same hardware. A feature that works well on a strong graphics card may run poorly on an older machine or a phone. NVIDIA's own comparison also needs care: Tech Times notes that NVIDIA compares Nemotron 3.5 Bolt's response quality with Gemma 4 26B, a model nearly seven times its size, but that this comparison comes from NVIDIA's own evaluation and had not been independently reproduced at the time of writing.","A third limit is trust. Players notice when a character's voice, face, or words feel wrong, and they notice when a studio is open about how a game was made. Ubisoft's Ghostwriter post stresses that the tool was built with scriptwriters and that writers keep control of the final text. A studio that explains where AI helped gives players a clearer basis for judging the result.","
$\"An$
A player using a VR headset and controllers.
"],["Frequently asked questions","
What is an NPC in a video game?
An NPC, or non-player character, is a character in a game that is not controlled by a player. It may be a shopkeeper, a guard, a companion, or a rival. In older games, NPC lines were written in advance and picked from a fixed list. Newer AI tools let some NPCs form replies from the current game situation, within limits set by the developers.
Do AI characters mean writers are no longer needed?
No. The examples in this article keep writers in charge. Ubisoft's Ghostwriter produces first drafts that scriptwriters choose and edit, and NVIDIA's and Atelico's tools work inside rules, characters, and facts set by developers. Writers still shape the story and the final lines in the main plot.
Will AI characters work on any device?
Not yet. On-device characters must share memory and processing power with graphics, sound, and physics, so performance depends on the player's hardware. Cloud-based characters avoid that limit but add waiting time and running costs.
"],["What to watch next","Watch for more on-device character tools reaching real games, and for studio reports on what worked and what did not. The real test is a shipped game where AI characters stay in character and remember what matters."]],author:"Eri-Tech Global Ltd",metaTitle:"AI in Video Games: How Game Worlds React to You",takeaways:["AI in video games now covers two different jobs: tools that help developers make a game, and characters that respond during play.","Scripted lines still matter. AI drafts and live replies work best when writers set the character, the facts, and the limits first.","On-device models let some characters answer without a cloud connection, but they must share memory and processing power with the graphics and the game itself.","Survey data shows most Unity developers already use AI for coding help and writing support, while far fewer rely on it for in-game character behaviour."]},{title:

AI medical imaging can flag urgent scans and give radiologists a second check, but a person still makes the decision. Learn how it works and its limits.

2026-11-01Read More →

A professor gestures toward adult students seated at desks with laptops in a university classroom.

Technology

Small Business Cash Flow: A Plain Guide to Money In and Out",slug:"small-business-cash-flow-explained",category:"Business",date:"2026-11-03",updated:"2026-11-03",primaryKeyword:"small business cash flow",metaDescription:"Small business cash flow is about timing: when money arrives and when bills fall due. Learn the three cash types, a simple forecast, and how to close gaps.",alt:"A smartphone showing a calculator app rests on top of financial documents.",image:"8962444",excerpt:"Small business cash flow is about timing: when money arrives and when bills fall due. Learn the three cash types, a simple forecast, and how to close gaps.",sections:[["What small business cash flow actually means","Small business cash flow is the movement of money into and out of a business, and the timing of that movement. Sales, customer payments, wages, rent, supplier bills, loan payments and tax bills all land on different dates, and the gaps between those dates decide whether a business can pay its bills on time.","That timing is why a business can look healthy on paper and still struggle in a given week. The United States Small Business Administration puts the point plainly: even profitable businesses can fail if they do not have the right amount of cash available at the right time.","This article explains cash flow in plain terms: what it is, how it differs from profit, the three parts of a cash flow statement, how to build a simple forecast, and what to do first when a customer pays late. It is general information, not advice about any one business.","Cash flow is a record of cash in and cash out over a set period. Cash in includes money customers pay, and cash out includes money paid to suppliers, staff, landlords and lenders. When cash in is larger than cash out for a period, the business has positive cash flow for that period. When cash out is larger, it has negative cash flow for that period.","The Small Business Administration describes a cash flow statement as a document showing the timing of all cash going in and out of the business over a particular period. Two businesses can have the same sales in a month and very different cash positions at the end of it, if one is paid at once and the other waits sixty days for its invoices to be settled.","Cash flow also sits beside two other core documents. Chase for Business explains that an income statement shows profitability, but not cash balances, while a balance sheet summarises assets, liabilities and equity at a single point in time, but does not track cash flow. The cash flow statement fills the gap: it tracks cash actually moving."],["Why profit on paper is not cash in the bank","Profit is calculated when revenue is earned and expenses are incurred, even if no cash has changed hands yet. Cash flow is calculated when cash changes hands. That single difference explains most cash flow surprises, and it is worth working through with an example.","Imagine a design studio invoices a client for work completed in November, with payment due in January. The income statement for November records the sale. The bank account in November does not change, because the client has not paid yet. In the same month, the studio still pays November wages, rent and software costs in cash. The business can therefore report a profit for November and still end November short of cash.","Chase for Business gives the same warning in plainer form: a business with a backlog of unpaid invoices might be profitable on paper but not have enough cash on hand to pay its bills. Regular checks catch that pattern early, before a missed payment damages a supplier relationship or leads to late fees. Profit answers the question, did the business earn more than it spent in that period, on paper. Cash flow answers a different question, did cash arrive in time to meet the bills that fell due."],["The three parts of a cash flow statement","Every cash flow statement is divided into three sections: operating, investing and financing, as described by Chase for Business, Capital One and NetSuite.","Operating activities cover the day-to-day running of the business: cash in from customers, and cash out to suppliers, staff, rent, utilities and tax. NetSuite describes operating cash flow as generally the best measure of whether a company is generating cash from its core business.","Investing activities cover longer-term assets. Buying equipment, a vehicle or a second location is an investing cash outflow, and selling an asset is an investing cash inflow. A business that buys a large piece of equipment will often show negative investing cash flow in that period, and that is not, on its own, a warning sign.","Financing activities cover how the business is funded: a loan received or money put in by an owner is a cash inflow, while loan repayments, interest payments and dividends paid out are cash outflows. A loan can make total cash flow look positive in the month it arrives, which is why Chase for Business warns owners to look below the surface: a positive total driven by borrowing is not the same as one driven by customers paying.","A short worked example from Chase for Business shows how the three parts add up. In its fictional bakery example for one quarter, operating activities produced 8,000 dollars, investing activities used 13,000 dollars for a new oven and a mixer upgrade, and financing activities added 10,000 dollars from a loan after a loan payment, giving a net increase of 5,000 dollars. Add the three sections for the change in cash, then add that change to the opening balance for the closing balance.","
$\"A$
Small business essentials: a calculator, calendar, coins, and letter tiles.
"],["How to build a simple cash flow forecast","A cash flow statement looks backward at cash that has already moved. A forecast looks forward. NetSuite defines cash flow forecasting as estimating the amount of cash coming in and leaving a business over a specific coming period, so the business can see whether its obligations can be met.","Capital One describes a cash flow projection in the same way, and notes that projections typically cover twelve months, but can also be built weekly, monthly or quarterly. NetSuite adds that short-term forecasting often covers the next thirty to sixty days, medium-term forecasting often runs to a rolling twelve months, and longer-term forecasting looks beyond a year, with accuracy falling as the horizon gets longer.","A simple forecast needs only five lines per period, and a spreadsheet is enough to start. First, write the opening balance, which equals the closing balance of the previous period. Second, list expected cash in, using the dates customers actually pay, not the dates invoices were sent. Third, list expected cash out, using the dates bills actually fall due, including wages, rent, supplier payments, loan payments and tax. Fourth, subtract cash out from cash in to get net cash flow. Fifth, add net cash flow to the opening balance to get the closing balance.","Capital One states the two formulas in plain form. Net cash flow equals cash inflows minus cash outflows. Closing balance equals opening balance plus net cash flow. Two habits make a forecast useful rather than decorative: forecast by payment behaviour, not by hope, and update the forecast often.","
$\"A$
A professional woman calculates finances at a desk with charts and a calculator.
"],["When a customer pays late","Late payment is the most common way a sound forecast breaks. The work is done, the invoice is sent, and the cash arrives weeks after the wages and supplier bills it was meant to cover. The first step is a check of the terms themselves: what payment date was agreed, what date was printed on the invoice, and whether the invoice was sent on the day the work was completed rather than at the end of the month.","For business-to-business work in the United Kingdom, GOV.UK states that statutory interest on a late payment is 8 percent plus the Bank of England base rate, and that a business cannot claim statutory interest if its contract sets a different rate of interest. GOV.UK also states that a business should send a new invoice if it decides to add interest to the money it is owed.","GOV.UK gives a worked example. If a business were owed 1,000 pounds and the Bank of England base rate were 0.5 percent, the annual statutory interest would be 85 pounds, which is 1,000 pounds multiplied by 8.5 percent. Dividing 85 pounds by 365 gives daily interest of 23 pence, and after fifty days that would be 11 pounds 50 pence. Those figures use the example rate in the guidance, not a current rate, so any real claim must use the base rate that applies to the period in question.","The same guidance framework also sets fixed sums for debt recovery costs, depending on the size of the debt, and confirms business-to-business payment periods are normally expected to be within sixty days, with public authorities normally expected to pay within thirty days. Beyond any legal step, invoice on completion, state the payment date clearly, chase on the day after the due date, and keep a short list of which customers pay on time and which regularly pay much later."],["Frequently asked questions","
Is cash flow the same as profit?
No. Profit is revenue minus expenses for a period, recorded when sales are earned and costs are incurred. Cash flow is money actually received and paid in that period. A business can be profitable on paper and short of cash, if customers have not paid yet.
How often should a small business check its cash flow?
Weekly is a practical rhythm, with a monthly forecast alongside it. A weekly check catches a shortfall while there is still time to chase an invoice or talk to a supplier, and a monthly forecast shows the pattern across a quarter, including tax dates and seasonal stock buying.
Does negative cash flow always mean a business is in trouble?
Not always, and the reason matters more than the sign. Negative cash flow from buying equipment, or in the early months of a new business, can be planned and temporary, as Chase for Business notes for early-stage businesses. Negative operating cash flow that continues month after month is a different pattern, and it needs a closer look at pricing, payment terms, and spending.
"],["What to watch next","Watch payment behaviour over the next two quarters, customer by customer, rather than as a single average, which can hide the one large customer whose late payment causes most of the strain. Also watch the dates that repeat: tax payments, rent reviews, and seasonal stock buying."]],author:"Eri-Tech Global Ltd",metaTitle:"Small Business Cash Flow: A Plain Guide to Money In and Out",takeaways:["Cash flow is about timing, not just totals: money is counted when it arrives or leaves the bank account, not when a sale is recorded.","Profit and cash can point in different directions in the same month, because a sale invoiced today may not be paid for weeks while wages and rent fall due now.","A cash flow statement has three parts: operating, investing and financing, and each part answers a different question about where cash came from or went.","A simple forecast, updated often, turns a surprise into a date you can see coming: opening balance, plus money in, minus money out, gives the closing balance."]},{title:

AI in education can tutor, plan lessons and draft feedback, but it can also mislead. Learn where it helps, where it fails, and how schools stay in charge.

2026-11-03Read More →

A tractor working on a lush green field surrounded by rich greenery under a clear blue sky.

Technology

Small Business Cash Flow: A Plain Guide to Money In and Out",slug:"small-business-cash-flow-explained",category:"Business",date:"2026-11-03",updated:"2026-11-03",primaryKeyword:"small business cash flow",metaDescription:"Small business cash flow is about timing: when money arrives and when bills fall due. Learn the three cash types, a simple forecast, and how to close gaps.",alt:"A smartphone showing a calculator app rests on top of financial documents.",image:"8962444",excerpt:"Small business cash flow is about timing: when money arrives and when bills fall due. Learn the three cash types, a simple forecast, and how to close gaps.",sections:[["What small business cash flow actually means","Small business cash flow is the movement of money into and out of a business, and the timing of that movement. Sales, customer payments, wages, rent, supplier bills, loan payments and tax bills all land on different dates, and the gaps between those dates decide whether a business can pay its bills on time.","That timing is why a business can look healthy on paper and still struggle in a given week. The United States Small Business Administration puts the point plainly: even profitable businesses can fail if they do not have the right amount of cash available at the right time.","This article explains cash flow in plain terms: what it is, how it differs from profit, the three parts of a cash flow statement, how to build a simple forecast, and what to do first when a customer pays late. It is general information, not advice about any one business.","Cash flow is a record of cash in and cash out over a set period. Cash in includes money customers pay, and cash out includes money paid to suppliers, staff, landlords and lenders. When cash in is larger than cash out for a period, the business has positive cash flow for that period. When cash out is larger, it has negative cash flow for that period.","The Small Business Administration describes a cash flow statement as a document showing the timing of all cash going in and out of the business over a particular period. Two businesses can have the same sales in a month and very different cash positions at the end of it, if one is paid at once and the other waits sixty days for its invoices to be settled.","Cash flow also sits beside two other core documents. Chase for Business explains that an income statement shows profitability, but not cash balances, while a balance sheet summarises assets, liabilities and equity at a single point in time, but does not track cash flow. The cash flow statement fills the gap: it tracks cash actually moving."],["Why profit on paper is not cash in the bank","Profit is calculated when revenue is earned and expenses are incurred, even if no cash has changed hands yet. Cash flow is calculated when cash changes hands. That single difference explains most cash flow surprises, and it is worth working through with an example.","Imagine a design studio invoices a client for work completed in November, with payment due in January. The income statement for November records the sale. The bank account in November does not change, because the client has not paid yet. In the same month, the studio still pays November wages, rent and software costs in cash. The business can therefore report a profit for November and still end November short of cash.","Chase for Business gives the same warning in plainer form: a business with a backlog of unpaid invoices might be profitable on paper but not have enough cash on hand to pay its bills. Regular checks catch that pattern early, before a missed payment damages a supplier relationship or leads to late fees. Profit answers the question, did the business earn more than it spent in that period, on paper. Cash flow answers a different question, did cash arrive in time to meet the bills that fell due."],["The three parts of a cash flow statement","Every cash flow statement is divided into three sections: operating, investing and financing, as described by Chase for Business, Capital One and NetSuite.","Operating activities cover the day-to-day running of the business: cash in from customers, and cash out to suppliers, staff, rent, utilities and tax. NetSuite describes operating cash flow as generally the best measure of whether a company is generating cash from its core business.","Investing activities cover longer-term assets. Buying equipment, a vehicle or a second location is an investing cash outflow, and selling an asset is an investing cash inflow. A business that buys a large piece of equipment will often show negative investing cash flow in that period, and that is not, on its own, a warning sign.","Financing activities cover how the business is funded: a loan received or money put in by an owner is a cash inflow, while loan repayments, interest payments and dividends paid out are cash outflows. A loan can make total cash flow look positive in the month it arrives, which is why Chase for Business warns owners to look below the surface: a positive total driven by borrowing is not the same as one driven by customers paying.","A short worked example from Chase for Business shows how the three parts add up. In its fictional bakery example for one quarter, operating activities produced 8,000 dollars, investing activities used 13,000 dollars for a new oven and a mixer upgrade, and financing activities added 10,000 dollars from a loan after a loan payment, giving a net increase of 5,000 dollars. Add the three sections for the change in cash, then add that change to the opening balance for the closing balance.","
$\"A$
Small business essentials: a calculator, calendar, coins, and letter tiles.
"],["How to build a simple cash flow forecast","A cash flow statement looks backward at cash that has already moved. A forecast looks forward. NetSuite defines cash flow forecasting as estimating the amount of cash coming in and leaving a business over a specific coming period, so the business can see whether its obligations can be met.","Capital One describes a cash flow projection in the same way, and notes that projections typically cover twelve months, but can also be built weekly, monthly or quarterly. NetSuite adds that short-term forecasting often covers the next thirty to sixty days, medium-term forecasting often runs to a rolling twelve months, and longer-term forecasting looks beyond a year, with accuracy falling as the horizon gets longer.","A simple forecast needs only five lines per period, and a spreadsheet is enough to start. First, write the opening balance, which equals the closing balance of the previous period. Second, list expected cash in, using the dates customers actually pay, not the dates invoices were sent. Third, list expected cash out, using the dates bills actually fall due, including wages, rent, supplier payments, loan payments and tax. Fourth, subtract cash out from cash in to get net cash flow. Fifth, add net cash flow to the opening balance to get the closing balance.","Capital One states the two formulas in plain form. Net cash flow equals cash inflows minus cash outflows. Closing balance equals opening balance plus net cash flow. Two habits make a forecast useful rather than decorative: forecast by payment behaviour, not by hope, and update the forecast often.","
$\"A$
A professional woman calculates finances at a desk with charts and a calculator.
"],["When a customer pays late","Late payment is the most common way a sound forecast breaks. The work is done, the invoice is sent, and the cash arrives weeks after the wages and supplier bills it was meant to cover. The first step is a check of the terms themselves: what payment date was agreed, what date was printed on the invoice, and whether the invoice was sent on the day the work was completed rather than at the end of the month.","For business-to-business work in the United Kingdom, GOV.UK states that statutory interest on a late payment is 8 percent plus the Bank of England base rate, and that a business cannot claim statutory interest if its contract sets a different rate of interest. GOV.UK also states that a business should send a new invoice if it decides to add interest to the money it is owed.","GOV.UK gives a worked example. If a business were owed 1,000 pounds and the Bank of England base rate were 0.5 percent, the annual statutory interest would be 85 pounds, which is 1,000 pounds multiplied by 8.5 percent. Dividing 85 pounds by 365 gives daily interest of 23 pence, and after fifty days that would be 11 pounds 50 pence. Those figures use the example rate in the guidance, not a current rate, so any real claim must use the base rate that applies to the period in question.","The same guidance framework also sets fixed sums for debt recovery costs, depending on the size of the debt, and confirms business-to-business payment periods are normally expected to be within sixty days, with public authorities normally expected to pay within thirty days. Beyond any legal step, invoice on completion, state the payment date clearly, chase on the day after the due date, and keep a short list of which customers pay on time and which regularly pay much later."],["Frequently asked questions","
Is cash flow the same as profit?
No. Profit is revenue minus expenses for a period, recorded when sales are earned and costs are incurred. Cash flow is money actually received and paid in that period. A business can be profitable on paper and short of cash, if customers have not paid yet.
How often should a small business check its cash flow?
Weekly is a practical rhythm, with a monthly forecast alongside it. A weekly check catches a shortfall while there is still time to chase an invoice or talk to a supplier, and a monthly forecast shows the pattern across a quarter, including tax dates and seasonal stock buying.
Does negative cash flow always mean a business is in trouble?
Not always, and the reason matters more than the sign. Negative cash flow from buying equipment, or in the early months of a new business, can be planned and temporary, as Chase for Business notes for early-stage businesses. Negative operating cash flow that continues month after month is a different pattern, and it needs a closer look at pricing, payment terms, and spending.
"],["What to watch next","Watch payment behaviour over the next two quarters, customer by customer, rather than as a single average, which can hide the one large customer whose late payment causes most of the strain. Also watch the dates that repeat: tax payments, rent reviews, and seasonal stock buying."]],author:"Eri-Tech Global Ltd",metaTitle:"Small Business Cash Flow: A Plain Guide to Money In and Out",takeaways:["Cash flow is about timing, not just totals: money is counted when it arrives or leaves the bank account, not when a sale is recorded.","Profit and cash can point in different directions in the same month, because a sale invoiced today may not be paid for weeks while wages and rent fall due now.","A cash flow statement has three parts: operating, investing and financing, and each part answers a different question about where cash came from or went.","A simple forecast, updated often, turns a surprise into a date you can see coming: opening balance, plus money in, minus money out, gives the closing balance."]},{title:"AI in Education: Tutors, Teachers, and the Human Check",slug:"ai-in-education-explained",category:"Technology",date:"2026-11-03",updated:"2026-11-03",primaryKeyword:"AI in education",metaDescription:"AI in education can tutor, plan lessons and draft feedback, but it can also mislead. Learn where it helps, where it fails, and how schools stay in charge.",alt:"A professor gestures toward adult students seated at desks with laptops in a university classroom.",image:"8197534",excerpt:"AI in education can tutor, plan lessons and draft feedback, but it can also mislead. Learn where it helps, where it fails, and how schools stay in charge.",sections:[["What AI in education actually means","AI in education is no longer a trial running in a few wealthy schools. Chatbots answer homework questions, teachers draft lesson plans with AI help, and tutoring tools talk a student through a maths problem one step at a time. The tools arrived fast, and in many schools they arrived before the rules did.","That gap matters, because education is not like shopping or streaming. A wrong suggestion in a shop costs a little time. A wrong answer in a lesson can settle in a student's mind as fact, and a system that writes a student's essay can hide the very learning a teacher needs to see.","This article explains where AI helps in schools and colleges, where it misleads, and what the main guidance from UNESCO, the OECD and the United States Department of Education actually says. The short version: AI works best as a helper that a teacher directs, not as a replacement for teaching, practice, or judgement.","AI in education covers three different kinds of tool, and mixing them up causes most of the confusion. The first is a general chatbot: a tool trained on vast amounts of text that can draft, summarise, translate and answer questions on almost any topic. It is flexible, but it was not built for teaching, and it will answer with confidence even when it is wrong.","The second is a tutoring system built for one subject. These tools have been used in maths and reading for years, and newer versions use chat-style conversation to guide a student step by step instead of handing over a finished answer. The OECD's Digital Education Outlook 2026 notes that tools of this kind, designed with a clear teaching purpose, show more promise than general tools used without a plan.","The third works behind the scenes for teachers and schools: drafting lesson materials, adapting a text to a different reading level, drafting feedback, and helping with marking. Andreas Schleicher, the OECD's Director of Education and Skills, writes that in the best case this help buys teachers time for relationships, richer feedback, and the judgement no machine can copy."],["Where AI helps teachers most","The clearest gains so far are on the teacher's side of the desk. Lesson planning is the example teachers cite most often. In the OECD's TALIS survey of lower secondary teachers in 2024, 57% agreed that AI helps them write or improve lesson plans. A teacher can ask for a first draft of a worksheet or a set of practice questions, then edit the result into something that fits their class.","Feedback is a second gain. Drafting comments on a set of essays takes hours, and AI can produce a first draft of that feedback, which the teacher then corrects. The same applies to adapting materials: a text can be simplified for a student still building reading skill, or extended for one ready for harder work. UNESCO's Global Education Monitoring Report 2023, as described by UNESCO, points to personal support of this kind as especially valuable for students with disabilities and for students living in remote areas.","Teacher training is a newer gain. Early OECD trials found new teachers who practised with simulated students came out better prepared and more confident, though more research is needed across different settings.","None of this removes the teacher's duty to check. England's Department for Education guidance, described in a written parliamentary answer in December 2025, says schools must check AI output for accuracy, and must not put personal or sensitive pupil information into public AI tools without a proper data protection route."],["Where AI helps learners, and where it misleads","For students, the honest picture has two halves. On one side, a good tutoring tool can do what a busy classroom often cannot: wait patiently, explain the same idea a second way, and ask a follow-up question instead of giving the answer.","On the other side, the OECD's warning is plain. When AI removes the effort that learning needs, students finish tasks faster and produce better-looking work, but their understanding is less firmly built. Researchers call the habit that follows \"metacognitive laziness\": the student stops checking their own thinking, because the machine seems to have done it. Studies reviewed by the OECD found that students who studied with a general AI tool produced higher-quality responses, yet their exam performance did not show the gain, and in some cases got worse once the tool was removed.","That result should change how homework and assessment are set. If a task can be completed by pasting a question into a chatbot, the task measures access to the tool, not learning. Teachers are responding by asking for working shown, drafts kept, and oral explanations.","Age matters here too. Schleicher argues that a six-year-old and a sixteen-year-old tapping the same screen are not having the same experience, and younger learners need stronger filters and more guidance. UNESCO's 2023 guidance proposed an age limit of 13 for independent use of generative AI tools in education, alongside data protection rules.","
$\"Two$
Two students study together with books and laptops in a library.
"],["The rules schools are writing now","Schools did not start with rules. In a UNESCO survey carried out in May 2023 among more than 450 schools and universities, fewer than 10% had institutional policies or formal guidance on generative AI.","Since then, the guidance has converged on a small set of shared ideas. UNESCO published its first global guidance on generative AI in education and research in September 2023, built around a human-centred approach: protect data privacy, set age limits, and keep human agency, so AI does not take away chances to build thinking and social skills.","The United States Department of Education took a similar line in May 2023, in a report called Artificial Intelligence and the Future of Teaching and Learning. It said plainly that the people it consulted wanted AI that supports teachers and rejected visions of AI that replace teachers. Its recommendations included keeping humans in the loop, strengthening trust, and involving educators in decisions.","England's Department for Education guidance follows the same pattern: AI should add to teaching, not weaken human oversight, and schools must take care with pupil-facing AI.","A school writing its own policy today does not need to invent this from scratch. It needs to answer, in writing, where AI may be used, where it may not, who checks the output, and what data must never be entered."],["How to use AI for learning without losing the learning","Start with the goal, not the tool. Before opening a chatbot, write down what the student should be able to do afterwards without help. If the goal is to understand fractions, a tool that walks through examples and then asks the student to solve one alone fits.","Second, treat every AI answer as a draft to check. Read it against a textbook, a class note, or a trusted source, and look for invented facts and confident errors. Students who learn this habit early gain a skill that matters far beyond school, because AI output will keep sounding confident whether it is right or not.","Third, keep the hard parts human. Discuss ideas with classmates, explain an answer out loud, and do some work by hand. The OECD's phrase for the risk is worth remembering: when the machine does the thinking for you, the learning does not happen.","Fourth, protect privacy as a habit. Do not paste names, photos, or school records into a public chatbot, and do not let a tool keep a record of a child's conversations without asking what it stores and why.","Finally, build AI literacy as a subject in its own right: the ability to engage with AI, question it, and manage it with critical thinking. A student who can say when to use AI, when to put it aside, and how to check its work is better prepared than one who can only prompt it quickly.","
$\"A$
A student works at a desk with a laptop, books and a notebook.
"],["Frequently asked questions","
Should students be allowed to use AI for homework?
It depends on what the homework is for. If the task is meant to build a skill, such as solving problems or writing clearly, doing it through AI defeats the purpose. If the task is to research, brainstorm, or check understanding, AI can help, as long as the student still does the thinking and the final work is their own.
Will AI replace teachers?
The guidance from UNESCO, the OECD and the United States Department of Education all point the same way: no. AI can draft materials, give practice, and handle routine work, but teaching also involves judgement, relationships, and knowing a particular student. The reports describe AI as a helper for teachers, with humans kept in charge of decisions, especially high-stakes ones.
What should a school check before adopting an AI tool?
Four things: whether the tool was built for education or is a general chatbot; what student data it collects, stores, and trains on; whether its output can be checked and corrected by a teacher; and whether it fits the age of the students who will use it. A tool that fails any of those checks should wait until the school has answers, however popular it is.
"],["What to watch next","Watch whether education-specific tools, built with teachers and tested in classrooms, pull ahead of general chatbots in the next round of trials. The trials so far are early, and the results need to hold across different countries and subjects.","Also watch how age rules and data rules develop. As more countries write AI rules for schools, the question will be whether those rules stay practical for a busy teacher, or become paperwork that schools work around."]],author:"Eri-Tech Global Ltd",metaTitle:"AI in Education: Tutors, Teachers, and the Human Check",takeaways:["AI in education works best when a teacher sets the goal first: tools built for learning, used with a clear purpose, help more than general chatbots used without a plan.","A finished answer is not proof of learning: studies reviewed by the OECD found that students using general AI tools produced better work, yet did worse when the AI was taken away, such as in exams.","Teachers are already using AI, and they are worried too: in 2024, 37% of lower secondary teachers in the OECD's TALIS survey said they used AI in their work, while 72% feared students could pass off AI work as their own.","The guardrails are now clear and shared across countries: keep a human in charge, protect student data, check every AI output, and teach students to judge what AI produces."]},{title:"Streaming Recommendations Explained: How Picks Appear",slug:"streaming-recommendations-explained",category:"Entertainment",date:"2026-11-02",updated:"2026-11-02",primaryKeyword:"streaming recommendations",metaDescription:"Streaming recommendations shape what you see first on Netflix and Spotify. Learn how viewing, listening and taste signals work, and how to take control.",alt:"A couple relaxes on a sofa with popcorn, watching television at home.",image:"6336665",excerpt:"Streaming recommendations shape what you see first on Netflix and Spotify. Learn how viewing, listening and taste signals work, and how to take control.",sections:[["What a streaming recommendation actually is","Streaming recommendations are the suggestions that fill your home screen when you open a video or music app. Instead of showing every title in the catalogue in the same order, the service makes a guess about what you are most likely to play next, and puts those titles where you will see them first.","That guess is not magic, and it is not a fixed list. It is built from what you have watched or listened to before, what people with similar tastes have chosen, and details about each title, such as its genre, cast, or release year.","This article explains how the main systems work, using Netflix for video and Spotify for music as the clearest public examples. You will learn which signals matter most, why two people see different screens, and what you can do when the suggestions stop matching your taste.","A recommendation is a ranked guess. When you open a streaming app, the service has far more titles than you could browse in an evening, so it has to choose an order. The titles at the top of the screen and at the start of each row are the ones its models rank highest for your profile at that moment.","Netflix describes this work as a set of models rather than a single formula. Different models handle different parts of the job, such as predicting which titles you will like, choosing which rows to show, and ranking the titles inside each row. In March 2025, Netflix described a foundation model for recommendations: one large model trained on hundreds of billions of interactions, which smaller features can draw on.","The older ideas still sit underneath. Collaborative filtering looks for members who watch in similar ways to you and suggests what they enjoyed. Content-based filtering looks at the titles themselves — genre, cast, release year, mood — and suggests similar ones. Netflix mixes both, which is why a brand-new show with no viewing history can still reach the right home screens: at first it leans on its details, and as people watch it, viewing data takes over.","That mix also helps lesser-known titles find the viewers most likely to enjoy them. The flip side is the cold-start problem: a title with no early audience gives the system little behaviour to learn from, and the same applies to a brand-new user."],["The four signals services use most","Netflix lists four groups of inputs, as reported by Simplilearn and Stratoflow. The first is your own activity: your viewing history and how you rated other titles. Finishing a series, stopping a film after ten minutes, and giving a thumbs up or thumbs down all send different signals.","The second is other members with similar tastes and preferences. If many people who watched the same documentaries as you later enjoyed a particular drama, the system may suggest that drama to you, even if you have never searched for it. This is the \"people who liked that also liked this\" pattern, applied at very large scale.","The third is information about each title: genre, categories, actors, release year, and similar details. Title details let the system connect a new release to titles you already liked, and they help it group titles into rows with a theme, such as suspenseful films or witty dramas.","The fourth is context: the time of day you watch, the languages you prefer, the devices you use, and how long you watched a title. Netflix says its system does not use demographic details such as age or gender, so two members of very different ages who watch the same kinds of shows can receive similar suggestions.","Search is a separate route into the same catalogue. Netflix executives wrote in 2015 that recommendations influenced about 80 percent of hours streamed, with the rest coming from search. That figure is old, so treat it as a historical snapshot, not a current measure. The practical point is simpler: if you only follow the home screen, you only see what the system already expects you to like."],["Why two people see different home screens","Open the same app on two accounts and the screens will differ in four ways. Netflix personalises which rows appear and in what order, which titles sit in each row, the order of titles inside each row, and, for many titles, the artwork shown. The strongest matches tend to sit in the top rows and at the start of each row, because that is where viewers look first.","Artwork is the most visible example. Netflix creates several images for many titles and uses machine learning to choose which one to show each member. Simplilearn gives the example Netflix itself used for Good Will Hunting: a viewer who watches many romantic films might see an image of Matt Damon and Minnie Driver, while a viewer who watches many comedies might see Robin Williams. The film is the same; the picture that introduces it is not.","Rows themselves come from different jobs. Stratoflow lists the kinds Netflix described in its 2015 paper: a ranker for genre rows, a ranker for the best picks from the whole catalogue, a Trending Now row, a Continue Watching row, and similarity rows that power \"Because You Watched\" suggestions. A page step then picks and orders the rows, balancing relevance with variety, because one account often serves a whole household in different moods."],["Music picks work a little differently","Music recommendations follow the same basic pattern — past listening, similar listeners, and track details — but the unit is smaller. A song lasts minutes, not hours, so a service can learn from many more plays, skips, and saves in a single week. That makes playlists a natural home for music suggestions.","Spotify's Discover Weekly is the best-known example. It first appeared in July 2015 as a playlist that appears each Monday in every Spotify user's account. Fast Company reported that it analyses a person's listening history, with a focus on what they played recently, then compares that with the playlisting behaviour of others. Scanning millions of playlists, it finds tracks commonly listed alongside music the listener already knows, and groups them into a new personal playlist.","The result is built to feel familiar: a playlist, not a new screen to learn. Matthew Ogle, the Discover Weekly product owner at the time, told Fast Company that the team removed much of the work of discovery by putting suggestions in a format listeners already used.","Spotify has since added a more direct control. In September 2026, Spotify rolled out Taste Profile in beta to Premium listeners aged 18 and older in the United States, after earlier testing in New Zealand. It shows Spotify's brief interpretation of your taste across music, podcasts, and audiobooks, and lets you ask for changes in plain words, such as more of a genre or more variety. Your notes act as guidance for the Home feed, not strict rules: Spotify says Taste Profile cannot follow an artist for you, and cannot apply absolute rules such as \"always show\" or \"never show\". Changes typically appear within a few hours.","
$\"A$
A young person listens to music with headphones and a phone.
"],["How to steer your own recommendations","Start with profiles. Suggestions, ratings, and viewing activity belong to a profile, not to a whole subscription. If several people share one profile, their tastes mix, and the suggestions will reflect the mix rather than any one person. Giving each regular viewer a separate profile is the simplest fix, and it costs nothing extra on most services.","Next, give clear feedback. Rate titles you have a view on, using the thumbs controls where they exist. On Spotify, saving a track, adding it to a playlist, or skipping it quickly all send signals, with full listens carrying more weight than quick skips.","Then clean up the history that misleads the system. On Netflix, you can hide a title from viewing activity, and hidden titles stop being used for recommendations unless you watch them again. On Spotify, you can exclude a specific playlist or track from your taste profile, so a sleep playlist, a child's music, or a one-off party mix stops shaping your suggestions.","Finally, search on purpose. Recommendations learn from what you play, so playing one new kind of title is often the fastest way to open a new row or playlist. New activity carries more weight than old activity, so your suggestions can shift within days, not months.","There are limits to all of this. A recommendation cannot make a title available in your country, and a high match does not promise you will enjoy it. The aim is practical: a home screen that reflects your current taste, with room left for something new.","
$\"A$
A person browses shows on a smartphone at home.
"],["Frequently asked questions","
Why do my recommendations change over time?
Because the system learns from recent activity. New viewing and listening carry more weight than older choices, so as your habits change, the rows and playlists change with them.
Can I reset my recommendations?
There is no single reset button on the services described here, but you can rebuild the signal. Use a separate profile, hide or exclude titles that do not reflect your taste, rate what you watch, and build fresh activity around the kinds of titles you want more of.
Do recommendations use my age or gender?
Netflix says its recommendation system does not use demographic information such as age or gender. Its suggestions are read from what you watch, not from who you are on paper. Spotify's Taste Profile is limited to Premium listeners aged 18 and older in the United States during its beta, but that is an eligibility rule for the feature, not a claim that age drives the music picks.
"],["What to watch next","Watch how control tools develop. Spotify's Taste Profile is still in beta, with no announced date for a wider rollout, so the question is whether direct, plain-word controls become standard across music and video apps, or stay a limited test.","Also watch the balance between familiarity and discovery. Services need to show titles you will play, but also surface new work, or home screens narrow over time."]],author:"Eri-Tech Global Ltd",metaTitle:"Streaming Recommendations Explained: How Picks Appear",takeaways:["Streaming recommendations are predictions, not certainties: they rank titles by how likely you are to play them, based on past behaviour and title details.","Netflix says its system uses viewing history and ratings, similar members, title information, and context such as time of day, language, device, and watch length — but not age or gender.","The home screen is personal in several ways at once: which rows appear, which titles sit in each row, their order, and sometimes even the artwork shown for a title.","You can steer the system: keep profiles separate, rate what you watch, hide or exclude titles that do not reflect your taste, and search for new kinds of titles on purpose."]},{title:"Digital ID Systems Explained: How Identity Checks Work",slug:"digital-id-systems-explained",category:"Politics & Policy",date:"2026-11-02",updated:"2026-11-02",primaryKeyword:"digital ID systems",metaDescription:"Digital ID systems let governments check who you are online without paper forms. Learn how enrolment, checks and wallets work, and what safeguards matter.",alt:"Close-up of hands holding a passport and a smartphone outdoors, with luggage nearby.",image:"20805604",excerpt:"Digital ID systems let governments check who you are online without paper forms. Learn how enrolment, checks and wallets work, and what safeguards matter.",sections:[["What a digital ID system is","Digital ID systems are the official ways governments record who a person is and then check that identity later, without relying on paper alone. A person enrols once, receives a digital record or credential, and presents that credential when a service needs to confirm identity.","Passports and driving licences have long served as proof of identity. What is changing is how that proof is stored, shared and checked: on a phone, through an online account, or by a number linked to a central record. The World Bank's Identification for Development guide describes digital ID systems as systems that use digital technology through the whole identity process, from capturing and checking data, to storing it, managing credentials, and verifying identity later. This article explains the parts most systems share, looks at examples in use today, and sets out the arguments made for and against them. It does not take a side.","A digital ID system answers a narrow question: is the person in front of the service the person the record describes? It does not, by itself, decide whether that person qualifies for a benefit, a loan or a licence. Those decisions still sit with the service that asks for the check.","Enrolment is the first step. A person gives basic details, such as name and date of birth, and in many systems also gives biometric details, such as a fingerprint, an iris scan or a face scan. The system checks those details where it can, and it checks for duplicates, so that one person does not hold two identities in the same system.","The second step is the credential: a number, a card, an online account or an app-based wallet. It points back to the record created at enrolment. It is not the record itself, and in a well-designed system it carries only the details needed for the check at hand. The third step is verification, sometimes called authentication: the system compares what the person presents now with what was recorded at enrolment. In some systems the answer is a simple match or no match; in others, the system shares a specific detail, such as a name or an age band."],["The three steps in practice","In the United Kingdom, the credential is an online account: GOV.UK One Login. GOV.UK says that at the moment One Login works only with some government services, and it gives Universal Credit as an example of a service it does not yet work with. Over time, GOV.UK says, One Login will replace other ways to sign in to services on GOV.UK, including Government Gateway.","To prove identity with One Login, GOV.UK lists three routes. The first is the GOV.UK One Login app, which checks that the photo ID is real, that the user is a real person, and that the user is the same person as in the photo ID. The second is answering security questions online, using details such as a mobile phone contract, bank accounts or loans, plus details from a passport, driving licence or current account. The third is a Post Office visit, where staff scan the photo ID and take a photo of the person; GOV.UK says the result usually arrives by email within a day. Once the check is complete, GOV.UK says the identity information is saved to the account, so the person does not need to prove identity again next time.","
$\"A$
A person unlocks a smartphone with a passcode.
"],["Three models in use today","The European Union model is a wallet, not a single sign-in. The European Commission describes the EU Digital Identity Wallet as a mobile app that lets a person access online and offline public and private services, store and share digital documents, and create binding signatures. Each Member State will provide at least one wallet, built to common specifications. The Commission lists uses that include applying for a passport, filing taxes, opening a bank account, and signing contracts.","Regulation (EU) 2024/1183, in force since 20 May 2024, sets the framework. A legal analysis of the timetable puts two dates at the centre: by 24 December 2026, each Member State must offer its citizens at least one free wallet, and by 24 December 2027, businesses in designated sectors, such as banking, energy, transport, healthcare and telecommunications, and major platforms must accept it as a means of authentication. The same analysis stresses that use of the wallet will always be voluntary for citizens.","A key feature of the EU wallet is selective disclosure: sharing only the detail a service needs, for example proving that a person is over 18 without showing a full date of birth.","Nigeria's model is built around a single number. BusinessDay reports that the National Identity Management Commission (NIMC) has announced more than 136 million enrolments into the National Identity Database, and that a new National Identity Management Commission Act in 2026 replaces the 2007 law and positions the National Identification Number (NIN) as Nigeria's primary identity under a \"one person, one identity\" policy. BusinessDay also notes the other side of that figure: with the population estimated at over 240 million, tens of millions of people, particularly children, rural residents and vulnerable groups, are yet to obtain a NIN, even as the NIN increasingly serves as a gateway to government programmes, financial services, telecom registration, passports, tax administration and social schemes.","
$\"Flags$
Flags outside the European Parliament building.
"],["What supporters point to, and what critics raise","Supporters, including the European Commission in its own description of the wallet, point to practical gains: easier access to public and private services, data shared only as far as necessary, stronger security standards, better fraud prevention, and less administration and lower cost when a business checks a customer's identity. For governments, a single verified record can also cut duplicate records across departments, a point Nigeria's budget minister made when he said the NIN should serve as a single, universally accepted identity standard, as reported by BusinessDay.","Critics raise three concerns, each reflected in the official sources themselves. The first is exclusion: a system that needs a phone, a network connection or a particular photo ID can leave out people who lack those things, and the Nigeria example shows the gap in plain numbers. The second is control: a legal analysis of the EU wallet records the criticism that a state-backed identity system could be seen as a tool for control, particularly if later linked to uses not currently planned. The regulation tries to limit this risk through voluntary use, pseudonyms, a ban on requiring the wallet when another method would do, and the traceability dashboard, but whether those safeguards work will depend on implementation and on independent supervisory bodies. The third is what happens when a check goes wrong: a wrong name, a failed fingerprint match or a lost phone can block access, so the World Bank's principles call for clear mandates, independent oversight and a route to complain and seek a remedy."],["Questions to ask about any system","First, is use voluntary, and is there a workable alternative for people who do not use it? The EU wallet is voluntary for citizens, while Nigeria's NIN is presented as a primary identity for access to services, so the answer varies by country and must be checked in the law, not in a press release. Second, what data is collected, and what is shared at each check? A system that shares only the detail a service needs is different from one that hands over a full record. The EU wallet's selective disclosure is one design answer; a simple yes-or-no reply to a check is another.","Third, who can see the data, and for what purpose? The World Bank blog says data should be accessed only by authorised users for purposes agreed in advance. If a proposal does not name those purposes, that is a gap, not a detail. Fourth, how does a person correct an error, replace a lost credential, or complain? Look for a named body, a time limit and a route that does not require the very credential that has failed. Fifth, what happens to people who cannot enrol in the usual way? Look for in-person routes, such as the Post Office option in the United Kingdom, and for help from a trusted person, which GOV.UK explicitly allows for One Login.","For a small business, the practical version is shorter: ask which credential is accepted, what data the check will share, and what fallback exists if the check fails."],["Frequently asked questions","
Is a digital ID the same as a national identity card?
No, not always. A national identity card is usually a physical card. A digital ID system is the record and the checking process behind a credential, which may be a number, an online account or a wallet app. A card can be part of a digital system, and a digital system can exist without a card, as with an online account.
Do I have to use the EU Digital Identity Wallet?
According to the legal analysis of Regulation (EU) 2024/1183 cited in this article, use of the wallet will always be voluntary for citizens. Member States must offer a wallet, but citizens are not required to take one up.
What should I do if an identity check fails?
Start with the service that asked for the check, and use its published help route: GOV.UK, for example, offers help from the One Login team and allows a trusted person to help, within stated limits. Keep the exact error message and the date, and if the record itself is wrong, ask the issuing body how to correct it.
"],["What to watch next","Watch three things: whether EU Member States meet the December 2026 wallet deadline; whether services that must accept the wallet by December 2027 ask only for the data they need; and, in Nigeria, whether enrolment reaches the people BusinessDay identifies as still unregistered, and whether the new Act's safeguards are put into practice."]],author:"Eri-Tech Global Ltd",metaTitle:"Digital ID Systems Explained: How Identity Checks Work",takeaways:["Digital ID systems share three steps: enrolment, a credential, and a later check against the record.","The United Kingdom's GOV.UK One Login saves a completed identity check so it can be reused across services, with three routes: an app, security questions online, or a Post Office visit.","In the European Union, each Member State must offer at least one free digital identity wallet by 24 December 2026, and use of the wallet by citizens is voluntary.","The World Bank's ten principles for identification stress coverage without discrimination, privacy and control by design, a clear legal framework, and independent oversight with a route to complain."]},{title:"AI Customer Service for Small Businesses Explained",slug:"ai-customer-service-small-business",category:"Business",date:"2026-11-02",updated:"2026-11-02",primaryKeyword:"AI customer service small business",metaDescription:"AI customer service helps small businesses answer routine questions fast, day and night. Learn what to automate, what to keep human, and how to start.",alt:"Close-up of a female call center agent using a headset while working at her desk.",image:"8681899",excerpt:"AI customer service helps small businesses answer routine questions fast, day and night. Learn what to automate, what to keep human, and how to start.",sections:[["What AI customer service means in a small business","AI customer service for small businesses is, at its simplest, a way for a small team to answer routine questions without being at a desk around the clock. A customer asks about opening hours, delivery times, or an order, and a chatbot or help page gives an answer drawn from the business's own information. When the question is harder — a refund, a complaint, or a request that needs judgement — the conversation passes to a person, with the earlier messages attached.","That split is the whole idea. Small firms rarely lack customers; they lack spare hands. Salesforce's seventh State of Service report, based on a survey of 6,500 service professionals in 40 countries, found that 82% of service professionals agree customer expectations are higher than they used to be, while representatives spend only 46% of their time with customers, with the rest taken up by admin and internal tasks. AI customer service aims to move the routine work out of the way so the people on the team can spend their time on the customers who most need them.","Three tools sit behind the phrase, and it helps to tell them apart. A knowledge base is a set of searchable help articles and answers on your own website. A chatbot is a chat window that answers questions in conversation, often by finding the right help article or asking a few short questions first. An AI agent goes a step further and can carry out simple tasks, such as checking an order or updating account details, rather than only giving information.","For a small firm, the practical difference is size. You do not need all three at once, and you do not need a large system. A help page and a simple chatbot on your website or messaging app, fed with your own prices, policies, and delivery details, is a start.","The research also puts the trend in scale. Salesforce reports that 69% of service professionals say their organisation uses at least one form of AI, and 39% say they use agentic AI, the kind that can take actions. Service teams in the survey estimate that AI resolves 30% of cases today, and expect that share to reach 50% by 2027. Those are survey estimates, not a promise for any one business — but they explain why customers increasingly meet AI first when they ask a question."],["The requests worth automating first","Zendesk's analysis of 165 million tickets from paid accounts in one quarter gives small firms a useful map. A quarter of incoming tickets were not real service requests at all — spam, system notices, and confirmation messages. Of the genuine requests, 49% were repeatable tasks with set answers, such as checking an order status, updating account details, or asking for a receipt. A further 31% came from something going wrong elsewhere in the business, such as a missed delivery or a delayed refund. The remaining 20% were high-value moments — complaints, cancellations, and account problems — where judgement and care matter most.","The failure cases need a different approach. A customer reporting a parcel marked delivered that never arrived does not want a tracking link; they want someone to look into it. AI can still help by pulling up the order and routing the case to the right person — but the fix itself needs a human. The same is true of the high-value 20%: a cancellation request may look simple, yet it can hide repeated problems or billing frustration that only a person will spot.","
$\"A$
A customer chatting on a smartphone.
"],["Keeping the human handoff easy","The most common complaint about automated service is not the automation itself. It is being trapped in it. HubSpot's research notes that 49% of customers cite not being able to reach a real human as a friction point of AI self-service. Zendesk's 2026 trends research found that 74% of consumers are frustrated when they have to repeat information, while 81% want the next person to pick up the conversation without going back over what was already said.","So the handoff is a design job, not an afterthought. Every automated answer should carry a plain route to a person: a button, a phone number, or a message option that works during stated hours. When the conversation moves to a person, the earlier messages should move with it, so the customer does not have to start again. Salesforce found that 85% of service professionals with voice AI say handoffs to human representatives are smooth for customers — a sign that this part can work well when it is planned rather than bolted on.","Transparency helps too. Zendesk reports that 95% of consumers expect an explanation when AI makes a decision, and 79% say plain-language reasoning matters. In practice that means saying, in simple words, what the system checked — for example, \"your order left our depot on Tuesday and is due Thursday\" rather than a bare status code. It also means saying when the system does not know, and offering a person instead of guessing."],["Setting it up in small steps","A small firm can set up AI customer service in a few steps, without a large budget or a technical team.","First, list the questions you actually get. Look at recent emails, messages, and call notes and pick the ten most frequent. If the same question appears again and again, it belongs in the first version. If a question needs judgement, money, or personal data, it stays with a person.","Second, write one clear answer for each question, in the words customers use. Short answers work better than long policy pages. Include the exceptions: what happens when an order is late, what proof is needed for a return, and who to contact when the standard answer does not fit. An AI tool can only repeat what it is given, so a vague answer becomes a vague chatbot.","Third, connect the tool to one source of truth. Salesforce found that firms which bring their service channel data together in one place are 1.4 times more likely to call their AI work very successful than firms with scattered systems, while 44% of service leaders say disconnected systems have delayed or limited their AI work. For a small firm, that can be as simple as one up-to-date price list, one delivery policy page, and one inbox, rather than answers spread across old posts and message threads.","Fourth, test it before customers do. Ask friends, staff, or regular customers to try the ten questions, plus a few awkward ones, and fix the answers that confuse them. Set a rule for what the system must never do on its own: never promise a refund, never change an account, never quote a price it cannot verify. Those stay with a person until the business is sure the process is safe.","
$\"Call$
A support team working together at a desk.
"],["How to tell whether it is working","A smaller inbox is not, on its own, proof of success. Zendesk's research makes the same point: 78% of customer experience leaders in its 2026 trends survey say AI requires firms to rethink how they measure success, and a request that leaves the queue is not necessarily a request that was solved.","Four measures give a fairer picture. The first is completed answers: did the customer get what they came for, without needing to ask again? The second is re-contact rate: how often does the same customer return with the same problem? The third is customer satisfaction, asked with one short question after the interaction. The fourth is first-contact resolution, which Zendesk's research links closely to loyalty — 85% of customer experience leaders in its survey say customers will leave brands that cannot resolve issues on first contact.","Watch the human side as well. Salesforce reports that among representatives at firms with AI, 83% say they have better career prospects because of it, 82% say it has helped them build new skills, 81% say it makes them more productive, and 80% say their job is less stressful. If your team reports the opposite, the setup needs adjusting, not more automation.","One honest warning belongs here. AI customer service saves time on routine work; it does not fix a broken delivery process, a wrong price list, or an unclear returns policy. Zendesk's ticket analysis found that nearly a third of genuine requests began with a failure elsewhere in the business. Fixing those causes will cut support demand more surely than any chatbot."],["Frequently asked questions","
Do small businesses need AI customer service, or is it only for large firms?
No, it is not only for large firms. The tools that suit a small team are the simplest ones: a help page, a chatbot answering the most common questions, and a clear route to a person. Salesforce's small-business guidance notes that AI agents can handle FAQs, order inquiries, and conversation summaries, which are exactly the jobs that eat up a small team's day.
Will customers be annoyed if a chatbot answers instead of a person?
Some will be, if they cannot reach a person when they need one. Most customers accept automated help for simple questions — HubSpot reports that 78% of customer relationship leaders say customers prefer to solve issues on their own — but the same research shows frustration when a real person is out of reach. Keep the human route visible and pass the conversation history along.
What should AI customer service never handle on its own?
Refunds, account changes, cancellations, complaints, and anything involving personal or payment details should stay with a person, or at least need a person's approval, until the process is tested and trusted. The same applies to any answer the system cannot verify from your own records. When in doubt, let the system gather the details and hand over, rather than guessing.
"],["What to watch next","Watch for AI tools that carry conversation history across channels — web chat, messaging apps, and phone — without making customers repeat themselves, and for clearer rules on explaining AI decisions to customers."]],author:"Eri-Tech Global Ltd",metaTitle:"AI Customer Service for Small Businesses Explained",takeaways:["AI customer service works best on routine, repeatable questions — order status, opening hours, prices, policies — while people handle complaints, refunds, and sensitive cases.","Customers now expect fast, accurate answers at any hour: Zendesk's 2026 trends research found 74% of consumers expect round-the-clock service because of AI, and 86% say fast responses and accurate answers shape their buying choices.","Start with your ten most-asked questions, write clear answers for them, and add one easy route to a person for everything else.","Judge the result by completed answers and customer satisfaction, not by how few messages reach a human — a question that leaves the queue unsolved is not a win."]},{title:

AI in farming turns field photos, soil readings and weather data into plain advice. Learn what helps growers, what small farms can use, and its limits.

2026-11-02Read More →

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