An AI policy is one of the first things a law firm should establish. It gives the organization a common set of expectations and creates a foundation for responsible use. But a policy is not the same thing as an operating governance program.
A policy cannot tell leadership which AI capabilities are already present, whether a vendor configuration changed, which employees completed training, whether approved tools still meet the firm's requirements, or what evidence exists when a client asks how the program is maintained.
A policy states the rules. A governance program applies, communicates, maintains, and proves those rules over time.
01 · The Foundation What an AI policy should accomplish
A useful AI policy establishes the firm's position on responsible use. It can define confidentiality expectations, prohibited conduct, human-review requirements, approved-use principles, escalation rules, and accountability.
It should help employees understand that professional obligations continue to apply when AI is involved. It should also provide enough flexibility to support responsible adoption rather than becoming an automatic prohibition on productive technology.
Those functions matter. The problem begins when the policy is treated as evidence that the entire governance problem has been solved.
02 · The Operating Gap Where policy and practice begin to separate
The policy may not match the tools employees actually use
A policy may refer generally to approved AI tools while the firm has no maintained record of which tools, models, plans, and configurations are approved. Employees are then expected to follow a rule the organization has not operationally defined.
The policy may not reach the people who need it
Publishing a document is not the same as educating employees. Attorneys and staff need practical examples, clear boundaries, and confirmation that they received and understood the expectations.
The policy may become outdated while appearing current
AI products, client expectations, court decisions, professional guidance, and vendor practices continue to change. A policy with no review process may remain formally effective long after parts of it no longer reflect the firm's actual environment.
The policy may not produce evidence
When a client, insurer, auditor, or internal leader asks how the firm governs AI, the policy is only one piece of the answer. The firm may also need to show approvals, training, acknowledgements, reviews, and current records.
The credibility of a policy depends on the operating records and actions that show the organization actually follows it.
03 · The Full Program What responsible AI governance includes beyond policy
AI Exposure Discovery
Visibility into embedded AI, vendors, employee practices, integrations, and other meaningful paths through which firm information reaches AI.
Approved Tools and Configurations
Maintained decisions about products, plans, models, settings, permitted uses, prohibited uses, and safeguards.
Employee Education
Practical guidance that explains how the policy applies to real work, confidential information, review obligations, and escalation.
Acknowledgements and Attestations
Records showing that employees received the policy and periodically confirmed their understanding or compliance.
Ongoing Review
A process for responding to material changes in tools, models, vendors, guidance, court decisions, client requirements, and firm practices.
Governance Evidence
Organized records that allow the firm to demonstrate what it decided, communicated, reviewed, and maintained.
The goal is not to create a large bureaucracy. The goal is to connect the policy to the few meaningful organizational decisions and recurring actions that make responsible use possible.
04 · The Ongoing Work Why governance must be maintained
AI governance is not a one-time drafting project because the environment does not remain still. A tool can add new capabilities. A vendor can change models or retention rules. A client can impose new restrictions. A court decision can raise new supervision concerns.
Maintenance does not mean rewriting the policy every month. It means having a clear process for recognizing material changes, deciding whether they affect the program, and updating the appropriate records when necessary.
- Review the policy on a defined schedule and after material changes.
- Update approved tools and configurations as capabilities change.
- Educate new employees and refresh training when expectations change.
- Maintain acknowledgements and periodic attestations.
- Record significant governance decisions and reviews.
- Prepare evidence in a form that can be produced when needed.
05 · Practical Response How to turn an AI policy into an operating program
Five practical steps
Assign clear ownership
Designate who maintains the policy, approved-tool decisions, employee records, reviews, and governance evidence.
Connect policy rules to actual capabilities
Record which tools and configurations are approved and how the policy applies to their permitted uses.
Communicate practical expectations
Train employees using realistic scenarios and require acknowledgement of the current policy.
Create a maintenance cadence
Schedule policy reviews, periodic attestations, vendor reviews, and updates after material changes.
Preserve evidence as the work occurs
Maintain records continuously so the firm does not have to reconstruct the program when a client or stakeholder asks.
Conclusion The policy opens the door. The program keeps it working.
A strong AI policy is essential, but it is only the beginning. Responsible governance requires the firm to translate that policy into approved decisions, employee understanding, ongoing review, and evidence.
Firms do not need an enterprise bureaucracy to do this well. They need a practical system that concentrates effort on meaningful governance events and maintains the resulting records over time.
That is the difference between having an AI policy and having an AI governance program.
