1. Decide what can enter the tool

A useful rule has to distinguish among public tools, organization-approved systems, vendor products, client-approved environments, and matters with special restrictions. The answer may change with the information, the system, the client, and the purpose of the work.

The operating task is to make those distinctions visible enough that a person can act on them before sensitive information is entered, not after an incident exposes the gap.

2. Decide who verifies the work

AI-assisted output can be useful and still be incomplete, misleading, or wrong. Review therefore cannot be reduced to a reminder to check the work. Legal organizations need to decide who is accountable, what sources must be checked, and when the use of AI should be disclosed or documented.

Different tasks will require different levels of review. The important move is to make the review standard deliberate rather than leaving each person to improvise it.

3. Decide how use will be governed

Policy becomes practice through approved tools, access controls, training, supervision, escalation paths, and clear ownership. If those pieces are missing, people may avoid useful tools, use unapproved ones out of view, or interpret the same policy in incompatible ways.

Governance should make responsible use easier to recognize and repeat. It should also create a feedback loop so emerging questions can improve the next version of the organization’s guidance.

Use the frame as a working agenda

A cross-functional team can use these three decisions to locate the next concrete gap. Start with one real workflow, identify the information entering the system, define how the output will be reviewed, and name the person responsible for resolving exceptions.

That exercise will not answer every AI governance question. It will reveal whether the organization’s policy can survive contact with the work it is meant to guide.

Questions to take back

Use these to locate the next decision.

  1. Can people tell which AI systems are approved for which kinds of information?
  2. Does each high-impact AI use case have an explicit review standard?
  3. Where do unresolved questions go, and who has authority to answer them?

This article is general research and educational material. It is not legal advice and does not create an attorney-client relationship.