How to make an AI policy your team can use
Turn AI policy into decisions about approved tasks, information, suppliers and review. Give staff examples and a place to ask about unfamiliar cases.
Photo unavailableMap each AI use to the information it receives, who relies on the result and who can pause it.
Start with the tools people already use
An AI policy is useful when people can decide whether a task is allowed, how to handle information and who must review the result. A document that nobody can apply leaves the practical decision unresolved.
AI governance consulting should connect the rules to the tools, tasks and owners in the business.
Read the source: NIST: AI Risk Management Framework.
Begin with an inventory of actual use
List the AI tools people use, what they use them for and what information enters each one. Include informal personal-account use where it affects business work. Group the uses by the information involved and the consequences if someone relies on a wrong answer.
For an illustrative drafting task, an assistant working from approved public material needs a different review from a tool proposing account changes using private customer information. The task and the consequence matter alongside the product name.
Turn broad principles into decisions
AI policy development should explain permitted uses, information boundaries, review expectations and the route for an unfamiliar case. Give staff examples that match their work. For example, specify which documents staff may upload to each approved tool.
An AI acceptable use policy consultant should identify which operational decisions the business can make and where qualified legal, privacy or other specialist review is needed for the actual arrangement. Record which decisions need specialist review before the policy goes live.
Assess the system in context
An AI risk assessment should consider what the tool can influence, who relies on its output and how a mistake would be detected and handled. Include limitations, access, evaluation and the ability to stop or change the system.
NIST's AI Risk Management Framework is voluntary guidance for considering risks across AI design, use and evaluation. Use it to structure the assessment and record the evidence behind each decision.
Review suppliers and information handling
An AI vendor assessment should examine the proposed product, account arrangement, information use, retention, access and important dependencies. Keep the answers attached to the actual service being bought. A provider's general marketing statement may not settle the details of your configuration.
An AI security assessment focuses on relevant threats and controls, such as access to company information and the actions an assistant may take. Agree its scope separately from policy writing so technical questions do not remain hidden inside a document exercise.
Give the rules an operating owner
Name who approves new uses, maintains the inventory, answers questions and responds to incidents. Review the arrangement when the tool's role, information or supplier terms materially change. Training should let people practise applying the rules, including when to stop and ask.
AI App Studio can help map AI use and define practical operating responsibilities. Book a call with the tools and decisions your team currently finds unclear.
Sources and further reading.
Our perspective is based on these sources. Product details and availability can change after publication.
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