Concern 924 · Working draft · editorial review in progress
AI-audit function
An AI audit function can provide weak assurance when reviewers lack independence, relevant skills or access to the evidence behind a system's claims.
Understanding the concern
An audit examines whether controls and practices work as intended. It should go beyond asking the team that built the system whether everything is fine. AI can require several kinds of expertise, including technical testing, data handling and understanding the service where outputs are used.
The Institute of Internal Auditors provides a framework for examining AI governance and risk. Think of checking a restaurant's food safety by inspecting records and practice, not just its menu. Auditors need to state what they examined, what they could not access and what remains uncertain. A report that clearly limits its conclusion can be more useful than a broad reassurance unsupported by evidence.
An example
An audit signs off on an AI service after reviewing policy documents but never checks whether staff follow the required controls.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
Evidence and its limits
The framework guides assessment; it is not evidence that a particular audit is independent or complete. Technical model validation and organizational audit are related but distinct.
Institute of Internal Auditors · Professional framework
Artificial Intelligence Knowledge Center and Auditing Framework ↗ (opens in a new tab)Public description of AI governance, management and auditing framework. Some supporting tools require membership; no claim of reviewing inaccessible material.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
- NIST AI RMF (opens in a new tab)
framework
- ISO/IEC 42001 (opens in a new tab)
standard
A question to discuss
What evidence supports the audit's conclusion, and which important parts were outside its scope?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Trustworthiness
Trustworthiness means giving people good reasons to rely on you. It grows when promises, actions, and evidence line up. With AI, a friendly voice or a famous brand is not enough: people need to know what was checked and what could still go wrong.
In practice, keep promises small enough to test, record mistakes, and tell people when the tool's limits affect them. If a service promises human review, make sure a person really has time and authority to review it.
Ask together: What would give the people affected a sound reason to trust this use?
Stewardship
Stewardship means caring for resources and systems that others depend on, including people who will use them later. It looks beyond the benefit of a quick launch.
Plan for maintenance, energy use, data protection, and eventual shutdown. Ask who will look after the tool when the original team moves on and how future users can avoid inheriting hidden costs.
Ask together: What are we responsible for caring for over time?
Prudence
Prudence means using careful judgment before and during action. It balances worthwhile opportunities with the need to avoid harm that could have been anticipated.
Start with a limited trial, set stopping points, and prefer choices that can be undone when uncertainty is high. Review what happens rather than assuming the original plan remains sound.
Ask together: What is a careful next step, and when should we stop or change course?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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