An AI policy defines how your organization permits, restricts, verifies, and oversees AI use. Without a policy, decisions about AI use are likely to be inconsistent, undocumented, and without human accountability.
A policy that governs tool selection and usage restrictions is incomplete. Your policy needs to include permitted and prohibited uses, data and confidentiality boundaries, output verification requirements, approval authority, client disclosure obligations, and review parameters.
Your first governance effort needs to be a workflow audit to find out where AI is already influencing your workflow and how that influence is impacting decisions and client deliverables.
AI templates typically provide structure and a rundown of prohibited actions; they do not clarify who has authority, what verification is required before output becomes binding, or how your practices hold up under scrutiny. This is a shortcoming of every AI template, because policy depends on governance decisions made by your leadership.
Yes, but sequence matters. Before your policy reaches Legal, it should address risk tolerance, verification workflows, and authority structures. Make governance decisions, create a policy aligned with those decisions, and then have Legal review and validate the policy. For law firms, that review must address the ethical obligations in ABA Formal Opinion 512.
AI governance and policy is new territory, so companies fall into one or more of these pitfalls: starting with a template and calling it done; assigning ownership to IT; omitting output verification requirements; treating the policy as a one-time document; and most detrimentally, creating the appearance of oversight without doing the governance work.
The exposure is consistent across industries: AI-assisted output that lacks verification, documentation, and assigned accountability results in court sanctions, regulatory fines, lost contracts, and reputational damage.
Annually at minimum, but change is the better trigger. Build a review cycle and indicate the responsible role into the policy itself.
Yes, governance comes first. Policy can only document governance decisions.
See the AI Governance FAQ.