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Legal AI tools
Legal AI tools are software products that use AI to help with legal research, drafting, document review or the running of a legal practice.
This page sorts them into categories and gives the questions a UK firm should ask before using any of them. It does not rank products. It supports our guide to AI for law firms and the broader picture in AI in law.
A clear view of which tool categories fit your work, and a set of evaluation questions on confidentiality, data location, citations and supervision to put to every supplier.
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 ↗
Garfield.Law Ltd is the first purely AI-based firm authorised by the SRA; AI litigation assistant for small debt claims; SRA checked quality, confidentiality, conflicts; system will not propose case law. SRA: SRA approves first AI-driven law firm (6 May 2025) ↗
New to the topic? Read the background on artificial intelligence.
ai tools for lawyers
what categories of legal AI tools are there?
Four main categories: research, drafting, review and practice management, plus general assistants used for legal work.
Research tools answer legal questions and find authorities, usually by retrieving from a database of cases and legislation and then summarising. Drafting tools produce first drafts of letters, clauses, submissions and notes.
Review tools read large sets of documents, such as contracts or disclosure, to classify, extract or flag issues. Practice management tools handle intake, time recording, billing narratives and matter administration.
General assistants, such as enterprise chat tools already licensed by the firm, are used for all of these. They are flexible but lack legal-specific sources unless connected to them.
Some services combine categories. Garfield.Law, which the SRA authorised in May 2025, is an AI-based regulated firm rather than a tool sold to lawyers: it guides businesses through small debt claims and, by design, does not propose case law.
Research, drafting, review, practice management.
General assistants cut across all four.
Judge each category on its own risk.
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how should we ask about confidentiality with legal AI tools?
Ask whether matter data is used for training, who can see it and how other clients' data is kept separate.
The SRA's Risk Outlook names the specific risks: confidential data revealed when transferred to an AI provider for training, and output from one case replicating confidential details in another.
So ask each supplier whether your data is used to train or improve any model, whether that can be switched off by contract, which staff and sub-processors can access it and how matters are separated.
Check the answers against your duties under the UK GDPR principles, including integrity and confidentiality, and against privilege.
Prefer written contract terms to marketing pages. A setting that can be changed by a user, or by the supplier in a later update, is weaker than a contractual commitment.
ai tools for lawyers
why does data location matter for legal AI tools?
Because transfers outside the UK, sub-processors and retention all affect your data protection position and client expectations.
Ask where data is stored and processed, including any third-party model providers the tool calls behind the scenes. Many legal AI tools are built on a general model hosted by another company.
Ask how long prompts, uploaded documents and outputs are retained, and whether deletion is complete when a matter closes or the contract ends.
Some clients, particularly in regulated or public sectors, have their own rules on data location. Check engagement terms before uploading their documents.
The ICO's guidance on AI and data protection covers the accountability and DPIA questions that sit behind these checks.
| Check | What to establish |
|---|---|
| 1 | Map every sub-processor. |
| 2 | Confirm retention and deletion. |
| 3 | Check client-specific restrictions. |
ai tools for lawyers
how do legal AI tools handle citations?
Unevenly, so the firm's verification rule matters more than any supplier claim.
The Ayinde judgment shows the cost of getting this wrong. The Divisional Court in Ayinde v Haringey dealt with false citations put before the court after the actual or suspected use of generative AI without checking.
Ask each research or drafting tool how it sources authorities: from a defined legal database, from the open web or from the model's own training. Ask whether every citation links to the source text.
Whatever the answer, the Law Society says citations must be verified against reliable and authoritative sources before documents go to court.
The Bar Council's commentary explains why: the model predicts plausible words and has no regard for truth, so even specialist legal AI tools can produce confident errors.
ai tools for lawyers
how should supervision work with legal AI tools?
Clear rules on who may use which tool for what, how output is checked and how use is recorded.
The SRA expects supervision systems that can cope with the increased speed of AI, and says firms should not trust an AI system to judge its own accuracy.
In practice that means defining which tasks each tool is approved for, what a supervisor must check, and how AI use is recorded on the file.
Trainees and junior staff are often the heaviest users, so supervisors need to know what good and bad AI-assisted work looks like. That is a training need, not only a policy line.
Our AI policy for law firms covers the rules; our AI training for lawyers covers the practice.
Approve tools task by task.
Record AI use on the file.
Train supervisors as well as users.
ai tools for lawyers
how should a firm pilot legal AI tools?
On real but low-risk matters, with a defined baseline, named reviewers and a written decision at the end.
Pick two or three tasks where the tool could help and where errors are easy to catch, such as summarising long correspondence or first-pass contract review.
Record how the work is done today, then run the tool on the same kind of work with named reviewers checking every output. Note errors, time spent checking and what reviewers changed.
A baseline of how the work runs now is not a promised saving. The pilot tells you whether the tool fits, and how much checking it needs, on your matters.
End with a written decision: adopt, adapt or stop, with the rules and training that adoption would need.
Start with low-risk, checkable tasks.
Measure checking time, not only drafting time.
Decide in writing.
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where does predeploy fit with legal AI tools?
We help firms choose, set up and train people on tools; we do not sell or rank them or give legal advice.
We work with your team to map tasks, match them to tool categories, prepare evaluation questions and run pilots on your own documents.
We then train fee earners and support staff on the approved tools, including prompting, verification, confidentiality and recording use.
We train people, not models: we do not train AI models on your client data. We do not offer CPD accreditation or guarantee time savings.
If you are starting out, read AI for law firms first, then contact us to talk through your tasks.
Task mapping and evaluation.
Pilots on your documents.
Training on the approved tools.
Make the decision concrete
What does the current task cost in time?
Choose a task connected to legal ai tools 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 legal ai tools.
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 ↗
Garfield.Law Ltd is the first purely AI-based firm authorised by the SRA; AI litigation assistant for small debt claims; SRA checked quality, confidentiality, conflicts; system will not propose case law. SRA: SRA approves first AI-driven law firm (6 May 2025) ↗
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 ↗
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 ↗
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) ↗
Article 5 UK GDPR sets out seven principles including data minimisation, accuracy and integrity and confidentiality. ICO: A guide to the data protection principles ↗
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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