AI agents, explained for people with actual jobs.

Strip away the jargon and the idea is small enough for one sentence: a chatbot answers you, an agent acts for you. Everything else - the billions in funding, the conference keynotes, the breathless LinkedIn posts - is elaboration on that sentence, some of it true.

How is an agent different from a chatbot?

Ask a standard AI assistant to find you a venue for a 40-person offsite and it writes advice: things to consider, questions to ask. Useful, but the work is still yours. Give the same goal to an agent and it does the work: searches, opens venue pages, checks availability against your dates, compares prices, and returns a shortlist with the booking forms half-filled. That is a good day. On a bad day it returns three venues that closed last year, because the pages it read were stale and it had no way of knowing - and it presents those three with exactly the same confidence as the good ones. Both outcomes are normal for this category today, which is the most useful thing to know before you delegate anything to one. The difference from a chat assistant is not intelligence - it is hands. An agent can take actions: browse, click, fill forms, run searches, open files, use other software. "Agentic AI" simply means systems built to work this way: take a goal, break it into steps, execute the steps, check progress, adjust.

You have probably already met the early versions without the label: the assistant that browses the web before answering, the "deep research" mode that reads forty sources and returns a report, the agent modes in ChatGPT, Claude, Copilot and Gemini that operate a browser or your files - though these mostly sit on paid tiers, several are still in preview, and some have not reached the UK yet. This is the same technology as the chat window, given permission to do rather than only say.

What can AI agents genuinely do today?

• Research and comparison: gather information across many sources into a structured answer - suppliers, prices, policies, competitors. The most reliable category today.
• Bounded multi-step admin: fill a known form from your data, reformat a batch of documents, cross-check a list against a website, assemble a report from several files.
• Software operation: drive a browser or application to complete a defined workflow - the frontier category: impressive on a good day, clumsy on a bad one.

Where they still fall over: long chains where step twelve depends on step three being exactly right; unfamiliar interfaces; judgement calls mid-task (agents pick an option, not necessarily your option); and knowing when to stop. An agent that hits a paywall may improvise creatively rather than report the problem - confident improvisation being the family trait it inherits from chat assistants.

The mental model: an intern with fast hands and no judgement.

Delegate to an agent the way you would to a bright temp on day one: clear goal, clear boundaries, and never the company credit card.

Everything you need for working with agents follows from that model. Give a goal with acceptance criteria, not a vague wish - the same briefing discipline as everyday AI use, with the stakes raised because the output is actions, not words. Prefer tasks where mistakes are cheap and visible: a wrong venue on a shortlist costs nothing; a wrong form submitted somewhere costs real unwinding. Keep the irreversible steps - payments, commitments, anything sent to another human - on your side of the line. And review what it did, not just what it says it did: an agent's cheerful summary of its own work is not evidence.

Are AI agents safe to use at work?

Pasting one email into a chat window shares one email. Connecting an agent to your inbox, calendar or files shares everything, continuously - that is what standing access means, and it is the real safety difference between chat and agents. Before connecting anything at work: is this tool approved, what exactly can it read and do, and can you see a log of its actions? Personal agent subscriptions wired into work accounts are how confidential data walks out of buildings without anyone deciding it should. The full data rules are in using AI safely at work, and the adoption questions in choosing AI tools apply double here.

What it means for your job - measured, not breathless.

The honest reading of the market: enormous investment, real capability arriving in waves, and adoption in ordinary businesses far behind the keynote demos - the production reality in one sector is documented in our review of agentic AI in UK finance operations. For office workers the implication is the one from the jobs question: agents extend what AI absorbs from routine work, from drafting tasks toward multi-step admin, and they raise the value of the skills agents lack - specifying work clearly, checking it sceptically, owning the outcome. Delegation, in short. People who manage well will manage agents well; people who have never had to delegate are about to learn on a very literal-minded colleague.

No need to buy anything today. The agent features arriving inside the assistant you already use are the sensible place to experiment: one bounded research task, reviewed properly, tells you more than a month of commentary.

Frequently asked questions