AI adoption in legal is accelerating. But the firms that deploy thoughtfully — rather than reactively — are the ones that avoid costly reversals, regulatory scrutiny, and staff resistance. This checklist was developed by the Valren team over two years of implementation work with law firms, FCA-regulated fintechs, and in-house legal departments.
It is not exhaustive. It is a filter. If you cannot confidently answer these 12 questions, you are not ready to deploy — and that is useful information to have before you sign a contract.
The 12 Questions
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01
What problem are you actually solving? AI should address a specific, measurable pain point — not be deployed for its own sake. Define the workflow, the bottleneck, and the outcome you expect to improve before selecting any tool.
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02
Who owns the output? When an AI system drafts a clause or summarises a document, a human must remain responsible for that output. Identify named accountability before go-live — not after something goes wrong.
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03
Where does your data go? Understand exactly where client data is processed, stored, and retained. Many off-the-shelf AI tools route data through third-party servers in jurisdictions that create conflict with your professional obligations.
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04
Is this compliant with your regulator's expectations? The SRA, FCA, and ICO have all issued guidance on AI use. For FCA-regulated firms, Consumer Duty adds another layer. Map your planned deployment against the current guidance before proceeding.
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05
Have you checked your professional indemnity cover? Some PII policies contain exclusions for AI-assisted work or require notification of material changes to workflow. Check with your broker before deployment — not after a claim.
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06
How will you detect errors? AI systems hallucinate. Define the review process that catches errors before they reach a client or a filing. A human sign-off step is not enough — it needs to be structured and logged.
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07
What does staff training look like? Tool adoption fails when training is an afterthought. Budget time and resource for proper onboarding, including how to critically evaluate AI output rather than accept it uncritically.
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08
How will you measure success? Define your baseline metrics before deployment — time per task, error rate, cost per matter — so you have something to measure against at 30, 90, and 180 days.
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09
What is the rollback plan? If the AI system underperforms or creates a compliance issue, you need a documented path back to the previous process. Define it before go-live, not during an incident.
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10
How are you communicating this to clients? Some clients — particularly institutional ones — will want to know if AI is involved in their work. Decide your disclosure position and make sure it is consistent with your engagement terms.
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11
Is the vendor financially stable and contractually committed? The AI vendor landscape is consolidating rapidly. Review the vendor's funding position, data portability provisions, and what happens to your data and workflows if they are acquired or shut down.
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12
Have you reviewed the model's known limitations? Every AI model has documented failure modes. Request technical documentation from your vendor and assess whether those failure modes are acceptable given your use case and risk tolerance.
What a Credible Answer Looks Like
The point of this checklist is not to produce 12 polished answers for a board presentation. It is to identify the questions where your answer is weak or uncertain — and treat those as blockers rather than risks to manage later.
In our experience, firms that rush past questions 3, 5, and 10 are the ones that face the most significant issues post-deployment. These are the questions that feel administrative but carry the highest consequence when they go wrong.
A credible answer is specific. "We will review AI output" is not a credible answer to question 6. "All AI-drafted clauses are reviewed by a qualified solicitor before client delivery, and this step is logged in our matter management system" is a credible answer.
Using This in Practice
We recommend running this checklist as a structured exercise with your senior partners or general counsel, your IT lead, and your compliance officer — not as a solo exercise by whichever partner is championing the AI initiative.
The questions where there is disagreement or uncertainty in the room are the questions that need answering before you move forward. Document the discussion. It forms the basis of your AI governance framework.
If you would like to work through this checklist with the Valren team — and map your answers against your planned deployment — we offer a one-hour AI readiness session as part of our onboarding process.