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AI for lawyers
AI for law firms
AI for law firms is now a practical question rather than a speculative one: fee earners, support teams and business services are already using general and legal-specific tools for research, drafting, document review and client intake.
This guide sets out where AI for lawyers genuinely helps, which professional duties apply when it is used, and what a firm needs in place before scaling it. It is written for partners, COLPs, practice managers and heads of knowledge or innovation.
Leave with a clear view of sensible use cases, the duties that do not change when AI is involved, and the governance and training steps that make adoption defensible.
Firms remain responsible and accountable for AI outputs, cannot delegate accountability to IT or providers, need supervision that copes with AI speed, and should decide what to tell clients. SRA: Risk Outlook report, the use of artificial intelligence in the legal market ↗
Solicitors' duties to court and client apply regardless of AI use, including work under their supervision; citations must be verified; misleading the court breaches para 1.4 of the SRA Code. The Law Society: Generative AI, the essentials ↗
New to the topic? Read the background on artificial intelligence.
AI for lawyers
where does AI for law firms actually help?
Mostly in first drafts, summaries, document review and intake, always with a lawyer checking the result.
The most useful applications of AI for law firms sit in work that is high-volume and checkable: summarising long documents, producing a first draft of a letter or clause, comparing versions, and triaging a data room.
Legal research is a more careful case. A general chatbot can explain a concept, but any authority it names must be checked against a reliable source before it goes anywhere near advice or a court document.
Intake and client communication are a third area: structuring enquiries, drafting acknowledgements and routing matters, provided the client is properly informed and nothing amounts to unsupervised advice.
The use cases for business guide covers the general method for choosing where to start; the legal version adds a stricter verification step.
Draft and summarise first.
Treat research outputs as leads, not authority.
Keep intake within supervision.
AI for lawyers
what do the SRA and the Law Society say about AI for lawyers?
Both are clear that existing professional duties apply in full, whatever tool was used.
The SRA's Risk Outlook report on AI in the legal market says firms remain responsible and accountable for the outputs of AI they use, and that accountability cannot be delegated to an IT team or external provider.
The same report says supervision systems need to cope with the speed of AI, and that firms should decide what to tell clients about how AI is used on their matters.
The Law Society's generative AI essentials states that a solicitor's duties to the court and to the client apply regardless of whether AI was used, including to work done by people under that solicitor's supervision.
For AI for lawyers, this means the question is never whether the tool is allowed in the abstract, but whether the person relying on it can show they checked it.
AI for lawyers
what have the courts said about AI-generated citations?
The courts have treated unchecked fake citations as a serious professional failure.
In [Ayinde v Haringey [2025] EWHC 1383 (Admin)](https://caselaw.nationalarchives.gov.uk/ewhc/admin/2025/1383), the Divisional Court dealt with referrals arising from lawyers' actual or suspected use of generative AI to produce arguments or witness statements that were not checked, so that false citations were put before the court.
The judgment also raised concerns about the adequacy of training and supervision for those who practise before the courts, which is a direct message to firm management, not only to individual fee earners.
The Law Society guidance says all citations in pleadings and other documents must be verified, and that misleading the court, even without deliberate dishonesty, breaches paragraph 1.4 of the SRA Code of Conduct.
Any programme of AI for law firms therefore needs a citation-checking rule that is written down, trained and audited.
| Check | What to establish |
|---|---|
| 1 | Verify every authority. |
| 2 | Training and supervision are in scope. |
| 3 | Write the checking rule down. |
AI for lawyers
how should a firm think about confidentiality and privilege?
Assume nothing about a tool until you know where data goes and who can see it.
The SRA lists specific threats: a staff member pasting a client question into a public chatbot, confidential data being passed to a provider for training, and one matter's details surfacing in another's output.
The ICO's guidance on AI and data protection applies alongside professional confidentiality; the ICO notes the guidance is under review following the Data (Use and Access) Act.
In practice, AI for law firms starts with a short list of approved tools, a plain rule on what client material may and may not be entered, and settings checked by IT rather than assumed.
Enterprise tools often make firmer commitments than consumer ones, but the firm still needs to read those terms and match them to its own client obligations.
AI for lawyers
what does the judiciary's own guidance tell firms?
It shows how seriously the courts take confidentiality and hallucination risk.
The judicial guidance on AI, refreshed in October 2025, expands on hallucination and bias risks and reminds judicial office holders not to enter private information into public AI tools.
It is written for judges and their staff, not for firms, but it signals what the bench expects of anything put in front of it.
The Bar Council has also published commentary, AI in law: breaking down the latest developments, explaining why AI outputs should not be trusted simply because a computer produced them.
Firms using AI for lawyers in litigation should read both and reflect them in internal rules.
Courts expect verified material.
Public tools and private data do not mix.
Computer output is not automatically accurate.
AI for lawyers
what governance does AI for law firms need?
A written policy, named owners, training on real matters and periodic checks.
Governance does not need to be heavy, but it must exist: an AI policy for law firms that names approved tools, permitted uses, verification duties and who to ask.
Owners matter. Someone, often the COLP working with IT and knowledge management, should own the tool list, the risk register and the client-information position.
The weakest point is usually people rather than paperwork, which is why the most effective step after the policy is AI training for lawyers on the firm's own matter types.
The broader AI governance framework guide covers the same structure for organisations outside law.
Write the policy first.
Name an owner.
Train on real work.
Make the decision concrete
What does the current task cost in time?
Choose a task connected to ai for law firms and enter its current workload. This gives you a baseline to discuss before buying training or commissioning a build.
A baseline is useful even if you decide to keep the process manual. Measure the work that matters, then compare quality and review effort as well as time.
Assess the workflow before changing it, or plan business AI training if the gap is how people use existing tools.
Your current workload
Estimate how much time the existing task takes before discussing ai for law firms.
16 hours per week
People × minutes × weekly tasks ÷ 60. A workload baseline from your inputs, not a prediction of AI time savings. Include review and support time when comparing a proposed workflow.
A useful AI investment leaves your team able to do the work and judge the result.
Continue with the right question
Where should you go next?
Use the overview for context, then follow the pages that match your delivery decision.
See our ai training service or read the ai for law firms overview.
FAQ
Questions, answered
Evidence and further reading
Which sources support the guidance?
Source links support the specific background described here. The practical checklists and illustrative examples are predeploy’s guidance.
Firms remain responsible and accountable for AI outputs, cannot delegate accountability to IT or providers, need supervision that copes with AI speed, and should decide what to tell clients. SRA: Risk Outlook report, the use of artificial intelligence in the legal market ↗
Solicitors' duties to court and client apply regardless of AI use, including work under their supervision; citations must be verified; misleading the court breaches para 1.4 of the SRA Code. The Law Society: Generative AI, the essentials ↗
Divisional Court referrals over lawyers' unchecked use of generative AI putting false citations before the court; raises concerns about training, supervision and regulation. Ayinde v London Borough of Haringey [2025] EWHC 1383 (Admin) ↗
Refreshed guidance replacing April 2025 version; expands on hallucination and bias risks and reminds judicial office holders not to enter private information into public AI tools. Courts and Tribunals Judiciary: AI judicial guidance (October 2025) ↗
Explains why AI outputs should not be assumed accurate because a computer produced them, referring to the Bar Council's 2024 guidance. Bar Council: AI in law, breaking down the latest developments ↗
ICO guidance covers AI accountability, transparency and fairness; the guidance is currently under review. ICO: AI and data protection guidance ↗
Background reading on the broader field of artificial intelligence. Wikipedia: artificial intelligence ↗
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