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AI Policies & Procedures: Usage, Development, and Deployment
This eighth episode of the ISACA Advanced in AI Audit (AAIA) exam prep series looks at how organizations turn AI strategy into actionable rules. It covers the layered framework of policies, procedures, and acceptable use rules that lets a company embrace artificial intelligence confidently while keeping its data and reputation protected.
What this episode covers
- Creating organizational AI policies and aligning them with the broader AI strategy.
- What belongs inside the primary AI policy — authorized and prohibited uses, governance expectations, and reliance on accepted frameworks.
- The ripple effect new AI policies have on existing procedures, standards, and training plans.
- The AI Acceptable Use Policy (AUP) — its purpose, how it complements the main policy, and what makes it usable for staff.
- Guiding data usage and training so end users know what they can and cannot feed into AI tools.
- Bringing the policy framework together into three connected layers that work as one rulebook.
Watch the full episode above for the worked examples and detailed explanations of each concept.
Frequently Asked Questions
What is the difference between an AI policy and an AI procedure?
A policy is a high-level declaration of your company rules and culture, like the traffic laws you must follow. Procedures are the step-by-step instructions people follow to do their jobs. When you finalize new AI rules, updates to applicable standards, plans, or procedures may result, because the high-level policy change ripples down into the detailed instructions that staff actually carry out.
What must an AI policy contain?
An AI policy must establish authorized and prohibited uses of AI within the organization, where authorized uses are tasks employees are allowed to perform and prohibited uses are absolute off-limit activities. It must also provide expectations for the governance of implemented AI solutions, detailing who monitors the AI, how it is maintained, and who is responsible if something goes wrong, leveraging generally accepted frameworks.
What is an AI acceptable use policy (AUP)?
An AI acceptable use policy, or AUP, provides a framework for the ethical and responsible deployment of AI and complements the main AI policy. It should be simple to understand with no confusing legal jargon, explicitly identify approved AI solutions, guide acceptable use of organization data within those solutions, and consider a risk-benefit analysis given the rapid advancements in generative AI.
Should you align AI policies with existing IT and security policies?
Yes. Before drafting a massive new document you must examine your existing information technology and security policies for potential integration, and your AI policies must always align with the overarching organizational AI strategy. You might find that existing rules about data privacy already cover most of what you need for AI, so you can weave AI concepts into current standards rather than writing a brand-new manual.
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Reference: This article is based on concepts discussed in AI Policies & Procedures: Usage, Development & Deployment.