The AI Learning Hub Journal

Building a Firm AI Policy

What a workable firm AI policy has to containSEVEN PARTS — a policy missing any one of them is a policy people quietly work aroundApproved toolsNamed, reviewed, contractedAnything else is off-limitsOne owner keeps it currentShadow tools are the real exposurePermitted tasksWhat AI may touch freelyWhat needs supervisionWhat is never delegatedAmbiguity gets resolved badlyHuman review pointsNamed checkpoints, in writingBefore anything leavesBefore anything is filedReview has to be scheduledClient consentEngagement-letter wordingMatters with tighter limitsClient instructions winAssume nothing on their behalfBilling treatmentCharge for work, not keystrokesSay how savings are passed onSettle it before the matter runsFee disputes start right hereTrainingEveryone who touches a toolRefreshed as the tools changeTeaches the failure modesPolicy without training is decorIncident pathHow to report a bad outputWho to tell, and how fastWhat gets fixed afterwardsSilence is what makes it worseWritten once and never taught is the common failure — the incident path is what tells you whether the rest is real
A firm AI policy works only when the approved tools, the permitted tasks and the review points all describe the same job

Start From Actual Behaviour

The most common policy failure is writing rules for a firm that does not exist. By the time most firms formalise a policy, people are already using these tools, often on personal accounts, and often without telling anyone. A policy written in ignorance of that reality regulates an imaginary organisation and drives real use further underground. The first step is an honest, non-punitive survey: what is being used, for what, by whom. Amnesty framing matters here — the objective is accurate information, and disciplinary framing guarantees you will not get it. Firms that skip this step typically produce a restrictive policy, achieve nominal compliance, and discover the actual position only when something goes wrong.

  • Adoption precedes policy in almost every firm — write for the organisation you have
  • Survey use honestly and without penalty; disciplinary framing guarantees inaccurate answers
  • Policy written in ignorance drives shadow use further out of sight
  • Nominal compliance with a restrictive policy is the most common and least useful outcome

What the Policy Has to Contain

A policy that functions covers a specific set of things. An approved-tools list identified by product tier and agreement, not by vendor name. A data classification mapping each sensitivity tier to permitted tools. Task rules stating what is permitted, permitted with verification, and prohibited outright. Verification requirements with defined depth, named ownership, and a required artefact. Disclosure rules for courts and clients, with a maintained per-forum register. Supervision expectations for AI-assisted work. Billing treatment. An incident procedure covering what to do when a fabricated citation is discovered. And a review cadence, because a policy written against last year's tools will be silently wrong within months.

  • Approved tools by product tier and agreement; data classification mapped to permitted tools
  • Task rules in three tiers: permitted, permitted with verification, prohibited
  • Verification depth, named owners, artefacts, plus disclosure rules and a per-forum register
  • Incident procedure and a scheduled review cadence — this material dates quickly

Making It Survive Contact With Practice

Policies fail for predictable reasons: too long to read, too slow to comply with, no named owner, no route to get a new tool approved, no consequence for ignoring it, and no update when the tools change. The countermeasures are unglamorous. Keep the operative rules to a page that fits next to a desk. Provide a fast, low-friction approval route for new tools so the answer to a good idea is not simply no. Name an owner with actual authority. Build the verification artefact into existing workflow rather than adding a parallel system. Review on a fixed schedule. And treat the first reported near-miss as the most valuable thing that will happen to the policy, because it is the only real feedback you are going to get.

  • Operative rules on one page; the long version can exist but nobody will consult it
  • Provide a fast approval route for new tools or people will route around the policy entirely
  • Name an owner with authority and build artefacts into existing workflow, not a parallel system
  • Treat the first reported near-miss as the policy's most valuable feedback, and respond accordingly

Try It Yourself

A policy is far easier to argue about than to write. Draft one section of it properly and the gaps become obvious.

◆ Try it yourself

Write the approved-tools and data-classification section of an AI policy for your firm or team: the sensitivity tiers, which product tier and agreement is permitted at each, and what is prohibited outright. Keep it to one page, describe data categories generically, and put no client material into any tool while drafting.

Tier 1 — public or non-client material. Permitted tools:
Tier 2 — client material, not privileged. Permitted tools:
Tier 3 — privileged or highly sensitive. Permitted tools:
Prohibited outright:
How a new tool gets approved, and by whom:
Owner of this section, and review date:
How you'll know it worked
  • Every tool is identified by product tier and agreement, not by vendor name alone
  • Someone reading it cold could tell which tool to use for a given document
  • It fits on one page and names an owner and a review date

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