AI in 2026. What UK law firms actually need to know
AI is moving from single chatbots to agentic workflows: multi-step systems that plan, draft, check, and iterate. That shift changes how you work, how clients evaluate firms, and how you protect your reputation. The biggest differentiator isn’t the tool, it’s governance, review discipline, and clear client-facing communication.
In 2026, the winners won't be firms that "use AI." They'll be firms that use it consistently, safely, and in ways clients can trust.
This guide cuts through the noise to focus on what's actually changing — and what you can do about it.
1. What AI trends should we watch in 2026?
Three shifts matter most for law firms: AI tools that work together, deeper personalisation, and growing pressure to show clients you're handling AI responsibly.
What's changing
AI assistants are starting to coordinate with each other. Instead of asking one tool to draft something, then copying it somewhere else, you'll see tools that handle research, scheduling, and first drafts across multiple steps — with you steering the process.
The same tool will also start behaving differently depending on who's using it. Two fee earners using identical software could have completely different experiences as the AI learns their preferences and working style.
Meanwhile, AI literacy is becoming a baseline professional skill. Clients and the public are paying closer attention to how firms handle these tools. "We use AI" isn't enough anymore — they want to know how you use it, and whether their data stays safe.
The pressure is coming from clients themselves. An October 2025 ACC/Everlaw survey of 657 in-house counsel across 30 countries found that 59% don't know whether their law firms are using AI on their matters. That's a transparency gap firms can close — or competitors will.
What to do now
If you don't have an AI policy yet, start there. It doesn't need to be lengthy, but it does need to cover: which tools are approved, what data can and can't go into them, who's responsible for checking output, and how you'll communicate your approach to clients. Without this foundation, everything else is guesswork. This will also minimise risks of "shadow AI".
Get IT involved early, but my view is that they shouldn't lead this process.
They'll know which tools meet your security requirements and are experts in the way data flows through your systems. But the decisions about what AI gets used for, how it fits into client work, and who signs off on output — those belong with fee earners and practice leaders. AI strategy led by IT alone tends to focus on risk avoidance rather than practical adoption. You need both perspectives at the table.
Once that's in place, pick three to five tasks where AI genuinely helps — research summaries, first-draft briefings, internal notes — and document exactly how your team should handle them.
Set clear rules for what information goes where. What's safe for public AI tools? What stays on internal systems? What never leaves the building?
Get leadership aligned on one simple message: AI supports the work, but humans remain accountable for the advice.
2. How will AI change day-to-day work beyond drafting emails?
AI is moving from "help me write this" to "help me think through this problem" — handling more of the legwork while you focus on judgement and client relationships.
Where it shows up first
Structuring arguments and deliverables gets faster. You can outline a client briefing, a research memo, or a pitch document in minutes rather than hours.
The draft-critique-revision cycle speeds up dramatically. AI can produce a first attempt, you mark what's wrong, and it tries again — repeatedly — until you're close to something usable.
But AI still makes confident mistakes. It can sound completely certain while being completely wrong. This means checking the output properly isn't optional — it's the whole point.
The good news: firms that get this right see results fast. An RSGI/Harvey study published in November 2025 found two-thirds of law firms saw measurable benefits within 90 days of adopting AI tools — and nearly a third within 30 days.
What to do now
Train teams on proper review habits: checking facts against sources, capturing where information came from, asking "what if this is wrong?"
Make human sign-off non-negotiable for anything that reaches a client.
Reward quality and judgement, not just speed. The goal is better work, not just faster work.
3. Is AI-driven job loss overblown for law firms?
In the near term, yes. You'll see tasks change before roles disappear. But the gap between AI-confident teams and AI-hesitant teams will widen quickly.
What to expect
Individual tasks will shift first — research, first drafts, document review — while core advisory work stays human. Over time, if each person can handle more output, that changes how teams are structured. But wholesale redundancies aren't the immediate story.
The real risk isn't AI replacing lawyers. It's AI-literate competitors winning work because they're faster, sharper, and more cost-effective.
Here's the client-side reality: the same ACC/Everlaw survey found 64% of in-house counsel expect to rely less on outside counsel because of their own AI capabilities. And 61% plan to push for changes in how outside legal services are priced. Corporate legal teams are building internal capacity — firms that can't demonstrate comparable efficiency will feel the squeeze.
An AI Futures Forum report from September 2025 put it bluntly: the primary driver of AI strategy is no longer internal debate — it's client pressure. Trust in AI among general counsel nearly doubled in a single year (21% to 40%), and 80% of GCs now expect to allocate up to 20% of their legal budgets to technology.
What to do now
Make AI literacy a baseline skill across the firm: how to prompt effectively, how to evaluate output, how to handle sensitive information safely.
If your AI policy exists but nobody's read it, that's the same as not having one. Build it into induction, reference it in team meetings, and update it when tools change.
Redesign roles around what humans do best: judgement, client communication, quality control, and the relationships that win and retain work.
Keep messaging human-first. Tools support expertise — they don't replace responsibility.
4. What is "agent-to-agent" communication — and why should we care?
Think of an AI agent as software that can plan and complete tasks toward a goal — not just answer a single question. "Agent-to-agent" is what happens when these tools start talking to each other.
Why does this matter? Because an increasing share of initial research and comparison may be done by AI systems, not just humans browsing your website.
What it changes for business development
Your website needs to answer questions clearly enough for software to understand, not just humans to skim. Who is this for? What do you actually deliver? What's the process? What proof do you have?
Clarity and verifiability become more important than polish. If a prospective client's AI assistant is comparing three firms, the one with unambiguous information wins the shortlist.
This isn't theoretical. The FOIL Update from October 2025 noted that nearly 80% of the UK's top 40 firms now actively promote their AI use to clients — up from 60% a year earlier. The conversation has moved from "are you using AI?" to "how are you using it, and what does that mean for me?"
What to do now
Add an "at a glance" summary to key service pages: who it's for, what outcomes to expect, typical timelines, and proof that you've done it before.
Make your credentials and process steps easy to extract — not buried in paragraphs of marketing copy.
Ask yourself: "If an AI agent were researching firms for a client, what would it need to recommend us?"
You could also run your site through Captain C.L.E.A.R — my free AI visibility GPT that'll take you through my proprietary framework.
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What should I do next?
Here's a simple checklist to kick things off.
Write an AI policy (or dust off the one nobody's read) — cover approved tools, data rules, review requirements, and client communication
Pick three to five safe use cases and write down exactly how your team should handle them
Set tiered data rules: what's public, what's internal, what's client-confidential
Publish a clear statement on how you use AI responsibly — and link it from your main pages
Refresh service pages with "at a glance" blocks and answers to the questions clients actually ask