If you were at London Tech Week (8–12 June 2026), you couldn’t move for the phrase “agentic AI.” It came up in almost every keynote, every panel, every corridor conversation. Investors were excited about it. Enterprise software vendors were rebranding around it. Startup pitches were built on top of it.
And if you run a small or medium-sized business in the UK, there’s a reasonable chance you’ve never heard the term at all.
That gap matters. Here’s why — and what it actually means.
What is agentic AI?
The simplest way to think about it: agentic AI is AI that doesn’t just answer questions. It takes actions.
Tools like ChatGPT or Microsoft Copilot respond to prompts. You type something in, you get something back. That’s useful, but you’re still doing most of the work — deciding what to ask, reviewing the output, then doing the next thing yourself.
An AI agent works differently. You give it a goal, and it figures out the steps needed to get there — then carries them out. It can browse the web, write and send emails, book calendar slots, run searches, update spreadsheets, pull data from one system and push it to another. It moves through a chain of actions without you doing each one manually.
The practical difference: instead of asking an AI to “draft a follow-up email to my leads from last week’s event,” an agent would identify the leads, research each one briefly, write personalised messages, and send them — while you’re doing something else.
What could this look like in a real business?
Three examples that are already being deployed:
Customer support. A customer emails to ask about a refund. Instead of the query sitting in a queue, an agent checks the order details, applies your refund policy, processes the refund through your payment system, and sends a confirmation — without a human touching it. You only get involved if something falls outside the standard rules.
Sales outreach. A sales agent monitors a list of target prospects, researches each one when it’s time to reach out (recent news, job changes, relevant context), drafts a personalised first message, and sends it from your email account on a schedule you’ve set.
Stock and operations. An operations agent monitors inventory levels across your products, flags when a line is running low, and automatically generates and sends a reorder to your supplier — logging everything in your spreadsheet or stock system as it goes.
These aren’t science fiction. They’re running in businesses right now, including small ones.
Why are people talking about it now?
Two reasons. First, the technology has got dramatically better in the last twelve months — agents are more reliable, make fewer random errors, and can work across more systems.
Second, the cost has dropped significantly. In 2025, building an agent required a development team and a decent budget. In 2026, basic agents can be configured through no-code and low-code tools by someone who isn’t a developer. Gartner predicts that 40% of enterprise applications will embed AI agents by the end of 2026. The consumer and SME market is following fast.
Three questions to ask before deploying an agent
1. Where could mistakes cause real damage? Agents can make errors at scale. An agent sending 200 emails gets 200 things wrong if the logic is off. Start with low-stakes processes, and build in a human review step before anything goes out to customers or suppliers.
2. What data does it need — and should it have it? Agents need access to your systems to do their job. Think carefully about what permissions you’re granting and to which tools. The same caution you’d apply to a new member of staff applies here.
3. Can you explain what it’s doing if someone asks? Agents take actions on your behalf. You remain responsible for those actions — legally, commercially, and reputationally. Make sure you understand what the agent is doing and why, and that you can audit its decisions.
Where to go from here
If you want practical guidance on deploying AI agents for your UK business, ApplyAI.org.uk is a useful starting point — built specifically to help businesses move from curiosity to implementation without needing a technical background.
If you’ve identified a process you want to automate and need someone to build it properly, BuildApps.co.uk works with businesses on custom agent builds. For the underlying technical implementation of agent workflows, CoolCoding.co.uk specialises in exactly that.
The LTI Observatory will keep tracking how agentic AI develops and what it means for businesses at the sharp end — watch this space for more signals as things move quickly.
The question worth sitting with
The businesses that benefited most from the early wave of AI tools — the ChatGPTs and Copilots — were the ones that started experimenting early, made some mistakes, and got ahead of the curve.
Agentic AI is the next wave. It’s moving faster, and the gap between early movers and everyone else is closing quicker.
The question isn’t whether AI agents will affect your business. It’s whether you’re the one deploying them — or whether your competitors get there first.
