Our employees are adopting AI tools on their own to do daily work, but we do not have formal guidelines. How do we write a practical AI policy that governs tool approval, output quality, and changes to seats on the Accountability Chart?

Question

Tyler Smith · Accepted Answer

A clear AI policy is not a multi-page legal disclaimer. It is an operational framework that protects company assets while establishing who owns the result. Start by addressing tool approval. Require that any AI software ingesting company data, client files, or proprietary workflows must be vetted by the Integrator or operations leader. Free, consumer-facing tools that train on user inputs must be banned for business data.

Next, govern output ownership. Make it an absolute rule that employees are one hundred percent responsible for the accuracy of every deliverable, regardless of whether a machine drafted it. Hallucinations or math errors cannot be blamed on the model. If an employee puts their name on a report or client email, they own every word.

Finally, tie AI use to the Accountability Chart. When an employee uses AI to automate significant portions of their documented responsibilities, they cannot quietly pocket the time savings or change their workflow in secret. They must notify their manager so the Core Process can be updated and capacity can be reallocated to higher-value work. An effective policy should explicitly state:
- Approved tools are centrally managed and verified for data security.
- Human verification is required before any generated output reaches a client or financial ledger.
- Any automation that changes how an SOP is executed must be documented and reviewed.

When you clarify these boundaries, you encourage smart operational efficiency while maintaining strict accountability across the organization.