For managing partners, practice managers and COOs at small and mid-sized law firms. By the end you should know which tasks to start with, which to keep away from, and what your firm needs in place first.
AI helps law firms most with reading, summarising and first drafts: reviewing documents, summarising bundles, drafting routine letters and answering questions from the firm’s own precedents. It is weakest at unverified legal research, because general tools can invent case citations. Every output still needs a lawyer to check it before it reaches a client or a court.
In brief
- Most lawyers already use AI. A 2026 LexisNexis survey of 543 UK legal professionals found 94% had adopted it, yet 17% of firms in a separate Clio study had no AI policy.
- The safest early wins are internal: summarising files, first drafts of routine correspondence, and searching the firm’s own knowledge.
- Court submissions and legal research need every authority checked. The High Court has already referred lawyers to their regulators for citing cases that don’t exist.
- The Law Society’s guidance comes down to five things: confidentiality, verification, supervision, agreement with clients and data protection.
- A firm needs an AI policy and an approved set of tools before it needs a clever use case.
Where does AI help law firms most?
AI is most useful on work that involves reading or writing a lot of text that a lawyer then checks. It is least useful where a single wrong fact can’t be caught by a quick review.
| Task | How well AI does it | What a lawyer still does |
|---|---|---|
| Summarising long files, bundles and correspondence | Well | Checks the summary against the source on anything that matters |
| First drafts of routine letters, emails and standard clauses | Well | Edits for the client, the matter and the firm’s tone |
| Answering staff questions from the firm’s own precedents and policies | Well, if set up on the firm’s documents | Confirms the answer before relying on it |
| Document review and due diligence | Well for first-pass sorting and flagging | Reviews everything flagged and samples what wasn’t |
| Triage of new enquiries | Well for sorting and routing | Decides whether to act |
| Legal research | Mixed: better with tools grounded in legal databases | Verifies every authority against the original source |
| Court submissions | Only as drafting help | Checks every citation, quotation and fact personally |
The pattern is the same throughout. AI produces a first version quickly, and a qualified person decides what goes out. Firms that get value from it are the ones that build the checking step into how work is done, so it isn’t left to individual habit.
To see the scale, take a firm with 20 fee earners. If each saves 30 minutes a day on summaries and first drafts, that’s 10 hours a day, or roughly 2,200 hours over 220 working days. Those figures are an illustration, not a forecast, but they show why small daily savings matter more than one impressive demo.
Where does AI go wrong for lawyers?
The biggest risk is AI producing something that looks right and isn’t. General chatbots can write convincing case names and citations for cases that don’t exist, and the lawyer who files them is responsible.
In June 2025 the High Court dealt with two cases together, Ayinde v London Borough of Haringey and Al-Haroun v Qatar National Bank, where fictitious authorities had been put before the court. In Al-Haroun, 18 of the 45 case citations had been entirely fabricated. The court said that people with leadership responsibilities in firms and chambers need to take practical steps to stop it happening again.
Lawyers know the risk, even where firms haven’t caught up: 17% of firms have no formal AI policy despite allowing AI use, according to Clio’s 2026 report. In the LexisNexis survey, fabricated or inaccurate information has been the top concern since 2024, and the share of lawyers worried about AI outputs rose from 57% to 83%.
The other two common problems are quieter:
- Confidential client information pasted into public AI tools, where the firm has no control over how it is stored or used
- Junior staff relying on AI output without enough supervision, which the courts have said is a leadership problem as well as an individual one
What do the Law Society and the courts expect?
Responsibility stays with the lawyer, whatever tool is used. The Law Society’s generative AI guidance, last updated in September 2025, comes down to five points:
- Keep confidential information out of AI tools you don’t control, especially free public services.
- Check AI outputs for accuracy, and verify every citation and authority against a reliable source.
- Your professional duties apply to AI-assisted work, whether you used the tool or someone you supervise did.
- Agree with clients whether and how AI will be used on their matters.
- Check where AI providers process and store data, and use fictional data for testing.
None of this stops a firm using AI. It does mean a firm needs written rules on which tools are allowed, what data can go into them and who checks the output.
How should a law firm check AI output?
Set the checking rule by risk, and write it down so it doesn’t depend on individual habit. A sensible rule has three levels:
- Internal notes and summaries for your own use: read the summary against the source for anything you’ll rely on
- Anything going to a client: a fee earner reviews it as they would a trainee’s draft, and takes responsibility for it
- Anything going to a court or another party: every authority, quotation and fact is checked against the original source, and the check is recorded on the file
Recording the check matters. If a question is ever raised, the firm can show that a person verified the work, which is what the courts and the Law Society expect.
Should law firms use general AI tools or legal AI tools?
Most firms will use both. General tools such as ChatGPT Enterprise or Microsoft Copilot, on business terms, are good for drafting, summarising and working with the firm’s own documents. Legal AI tools that ground their answers in legal databases are better for research, because their answers point back to real sources.
LexisNexis found that just over half of lawyers who use AI have chosen tools built for legal work. That leaves almost half relying on general tools, which is fine for drafting and dangerous for research.
The account tier matters more than the brand. A free or personal account of any AI tool is the wrong place for client data. A business account with no training on your data, a signed data processing agreement and a known storage location is the minimum. Our guide to sovereign AI for regulated businesses explains the levels of control available.
Where should a small or mid-sized law firm start?
Start with a policy and two or three internal tasks, and leave the firm-wide rollout until later. For most firms of 10 to 50 fee earners, we’d begin like this:
- Write a one-page AI policy: approved tools, what data may go into each, and the verification rule for anything that leaves the firm.
- Move everyone onto approved business accounts and close off personal use for client work.
- Pick two or three high-volume internal tasks, such as summarising files, first-draft letters and questions about the firm’s own precedents.
- Set a simple measure for each, such as minutes saved per matter, and check it after a month.
- Update client care letters to say how AI is used, in line with the Law Society’s guidance.
- Only then look at bigger projects, such as an assistant that answers questions from the firm’s whole knowledge base.
We’d expect a firm that starts at step 6 to stall, because the policy, the data access and the habits aren’t in place yet.
What’s different for law firms in the Isle of Man and Channel Islands?
Firms in the Crown Dependencies often act for international clients, trusts and regulated businesses that expect their information to stay on the island. UK data residency from an AI provider keeps data in the UK, which may not meet that expectation.
Where it doesn’t, the options are an AI model hosted in a local data centre or on the firm’s own servers. Data protection law on the island already applies to AI that processes personal data, so a data protection impact assessment is a sensible step before any AI tool touches client files. This is general information, not legal advice.
Frequently asked questions
Is it safe to use ChatGPT for client work?
It depends on the account. The free and personal versions of ChatGPT are the wrong place for client information. Business tiers such as ChatGPT Enterprise offer contracts that rule out training on your data and options for where data is stored. Even then, check the terms against your client agreements, and keep anything highly sensitive on a system the firm controls.
Do law firms have to tell clients they use AI?
The Law Society recommends agreeing with clients whether and how AI tools will be used on their matters, and communicating this clearly. Its guidance notes that the SRA has no specific rule on disclosure for client care. In practice, a short paragraph in client care letters explaining how AI is used and checked is a sensible default.
Will AI replace trainee solicitors and paralegals?
AI is taking over parts of the work juniors have traditionally done, such as first-pass document review and summarising. So far that changes what juniors spend their time on more than whether firms need them. Someone still has to check AI output, and supervising that checking is now a recognised duty, so reviewing AI work is becoming part of junior training.
Which AI tool is best for lawyers?
There isn’t one best tool. For legal research, choose a tool grounded in a legal database, so answers link to real sources. For drafting and summarising your own documents, a general AI tool on a business account works well. For questions about the firm’s own precedents and know-how, the best results come from a system set up on those documents specifically.
Can AI connect to our case management system?
Often, yes. Many case and practice management systems now include AI features or allow other tools to connect through an integration. Check what your vendor offers first, because a built-in feature is usually quicker to adopt than a separate tool. A custom connection makes sense when you want AI to work across several systems at once.
How Hyperlabs can help
Hyperlabs Activate puts AI to work inside regulated firms, including law firms that need client data to stay under their control. We find the tasks where AI saves the most fee-earner time, build the system on your own documents, then support, maintain and train your team on a fixed monthly basis. For an overview of the whole process, see our AI implementation guide.