Legal work carries a particular kind of professional responsibility. An answer that is wrong, incomplete, or untraceable is not just unhelpful — it can cause harm. The case for AI in legal settings is therefore more careful than in most: the tool must earn trust through transparency, not undermine it through convenience. Used correctly, AI can give legal professionals more time for the work that actually requires their expertise. Used carelessly, it creates exactly the risks it is supposed to reduce.
The responsible framing
AI does not practise law. It assists lawyers. That distinction is not a disclaimer — it is a design principle. In legal work, the professional is responsible for what goes out under their name, regardless of how it was produced. That means AI in legal settings must be used with the same rigour applied to any other tool: verify the sources, check the reasoning, apply professional judgement, and own the output.
Where AI earns its place in legal practice is in the volume of work that does not require judgement but does require time: research, first drafts, document review, precedent searching, summarising large documents, maintaining templates. If that work is done faster and to a reliable standard, the lawyer's time is returned to the work that cannot be delegated.
How legal teams use askFinz
- Legal research and case preparation. Finding relevant precedents, summarising statutes, identifying how a principle has been applied across jurisdictions — this is painstaking work that AI can accelerate meaningfully. The Legal app keeps every source visible, so the lawyer can evaluate the research, not just receive it.
- First-draft contract and document work. Generating a first draft of a standard agreement, a template clause, or an internal policy saves time at the top of the drafting process. Lawyers review, revise, and take professional responsibility — but they do not start from a blank page.
- Document review and due diligence. Reviewing large volumes of documents against a checklist or a set of criteria is one of the most time-intensive parts of transactions and litigation. AI can surface the relevant sections, flag inconsistencies, and annotate — so the lawyer is reviewing analysis, not manually reading every line.
- Client-facing summaries. Translating complex legal material into plain language that a client can understand is valuable work that takes time. AI can produce a first version of a client briefing or explanatory note, maintaining the accuracy of the underlying legal content.
- Precedent and template libraries. Legal knowledge often lives in individual matter files. A searchable knowledge base means the firm's or team's accumulated expertise is accessible on the next similar matter.
What to watch for
A few principles that responsible AI use in legal settings requires:
Never accept AI output without review. Legal outputs have consequences. A clause, a summary, or a research finding produced by AI must be reviewed by a qualified professional before it is relied upon. This is not optional.
Check sources. AI that produces legal research without visible sourcing is not suitable for professional use. The material must be traceable to an actual authority — statute, case, regulation — that the lawyer can verify.
Confidentiality and privilege. Client information is protected. Legal work that involves privileged communications or confidential client data must not be run through general-purpose tools without understanding the data handling involved. askFinz's Legal app is designed with this in mind.
Scope clarity. AI assists with legal work. It does not replace independent legal advice. Any use that might give a non-lawyer the impression that AI output constitutes legal advice needs to be clearly framed.
Where to start
The most useful starting point for a legal team is usually document review or research — the tasks where volume is the constraint, not judgement. Run a real matter through the workflow. See whether the research is traceable, whether the first draft saves meaningful time, and whether the output is something you would sign off on.
Request access and bring a real matter to test with.
Further reading
- AI for research-heavy work — legal research is a specific instance of the broader research discipline; the principles carry directly.
- AI for wealth & finance teams — a parallel regulated-industry use case, where citation and auditability are equally non-negotiable.
- The Law Society and equivalent bodies in most jurisdictions have published guidance on AI use in legal practice — a useful reference for teams building internal policies.
- askFinz's approach to sensitive data and access control: Trust.