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AI Acceptable Use Policy (AUP) Explained
This episode of the ISACA Advanced in AI Security Management (AAISM) exam prep series turns to the single document that tells colleagues, in plain terms, what they are and are not allowed to do with AI: the Acceptable Use Policy. It defines the AUP, explains why every organization using AI needs one, and walks through the practical work that must happen before anyone sits down to write it.
What this episode covers
- What an AI AUP is — a communication tool that sets clear permitted and prohibited uses of AI, especially around data.
- Step 1 — Understand the technology, including model types, data sources, biases, limits, and public-versus-private deployment.
- Step 2 — Assess organizational needs and research legal and regulatory requirements specific to industry and region.
- Step 3 — Conduct a risk assessment covering both technical and ethical risks.
- Step 4 — Confirm purpose and scope so staff know exactly which systems the policy covers.
- Step 5 — Examine existing policies to borrow, reuse, or template wherever possible.
- Step 6 — Engage stakeholders to make the policy comprehensive and workable.
- Step 7 — Adopt a governance framework for ownership, responsibility, and assurance.
- Step 8 — Prepare communication for both internal and external audiences as a living document.
Watch the full episode above for the worked examples and detailed explanations of each concept.
Frequently Asked Questions
What is an AI Acceptable Use Policy?
An AI acceptable use policy spells out what the organization has decided is permitted and what is forbidden when using AI, right down to which types and classifications of data may be used to train or feed an AI tool. At its heart it is a communication tool; its job is to set clear expectations for staff so nobody has to guess where the line is.
Why does every organization need an AI acceptable use policy?
An AUP protects the organization from people feeding confidential data into the wrong tool and gives staff the clarity they need to use AI confidently instead of fearfully. Think of it like the posted rules at a community swimming pool — the water is there for everyone to enjoy, but rules about diving, lanes, and supervision keep people safe and the pool open.
What are the eight preparation steps before writing an AI AUP?
The eight steps are: understand the technology including model types, data sources, biases, and limits; assess organizational needs and research legal and regulatory requirements; conduct a risk assessment covering technical and ethical risks; confirm the purpose and scope of acceptable AI use; examine existing technology and information security policies for reusable rules; engage stakeholders in developing the policy; adopt a governance framework; and prepare for internal and external communication.
What risks should an AI AUP risk assessment cover?
The risk assessment must identify both technical risks like unintended or wrong outputs from the AI system, and ethical risks like the spread of misleading information. Covering both lenses prevents an AUP that only addresses obvious technical failures while ignoring the social harms AI can cause.
Why should an AI AUP be treated as a living document?
A policy is a living document, not a one-time memo, so teams must be told whenever it is updated or changed. Customers and regulators also want to understand intended uses of AI along with ethics and privacy safeguards, so the organization must plan for both internal and external communication from the outset of policy creation.
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Reference: This article is based on concepts discussed in AI Acceptable Use Policy (AUP) Explained.