Your AI policy is not an adoption strategy

Most law firms began their AI work in the right place: protecting clients. They formed committees, reviewed tools, and published rules about confidential information. That work matters. But many firms are now asking a policy document to do a second job it was never designed to do.

A policy tells people where the boundaries are. Adoption requires people to see a better way to complete a specific piece of work, trust the new method, and know who will help when it fails. Those are different conditions, owned by different people.

The gap between permission and practice

When a firm approves a tool, it has answered a risk question. It has not answered a workflow question. Lawyers still need to decide where the tool belongs, how its output will be checked, whether the economics make sense, and how the result should be explained to a client.

That is why broad training sessions often produce a burst of experimentation followed by quiet reversion. The tool was introduced, but the work was not redesigned.

Build adoption around matters, not features

Start with one recurring task inside one willing team. Describe the current method, including review points and failure modes. Then test whether AI can improve speed, quality, consistency, or lawyer experience without weakening judgment. A useful pilot ends with a documented way of working—not a list of prompts.

The firms that move well will treat governance and adoption as connected disciplines. Policy sets the perimeter. Practice leaders, knowledge teams, technologists, and lawyers build the path inside it.