Most chief audit executives cannot tell stakeholders what their department's AI investments return. A May 2026 Gartner poll of 142 CAEs found that 54% have not started measuring the value of audit's use of AI, and only 7% tie AI to cost metrics such as reduced external spend or avoided hiring.
The numbers arrive as AI use among auditors has become widespread. Gartner reports that 93% of audit leaders and auditors use AI at some level in their daily work. But the adoption is largely informal - only 15% say their department has deployed formal use cases and runs them routinely in audits. Auditors are figuring out the tools on their own.
Strategy gaps are closing, but slowly
Only 38% of the 161 CAEs polled in May have an AI strategy at any level. Most of those folded AI into the overall department strategy rather than writing a separate one for audit. Another 39% are building one now, a sign that the gap may narrow soon.
"AI adoption is widespread across audit teams, but the lack of a formal strategy means most audit functions are not realizing the full potential of these technologies," said James Bourke, Director Analyst in Gartner's Risk & Audit Practice. For executives responsible for AI for Executives & Strategy, the data underscores a familiar pattern: tool adoption outrunning governance.
Where auditors actually use AI
Drafting and planning dominate. Among 743 respondents, 60% use AI for engagement preplanning work such as research and brainstorming risks. The same share uses it to draft audit issues, ratings, or reports. Smaller groups apply AI to planning deliverables like risk and control matrices and to reviewing drafts before they go out.
Audit testing sits at 30%. Testing is the part where an auditor checks whether a control works, and it changes the conclusions in the report. A hallucination or omission there costs more than a clumsy paragraph in a draft. Departments using AI for testing need tighter validation of what the model produces, plus documentation that holds up when a regulator or an external auditor asks how the answer was reached.
People problems outweigh technology problems
Audit leaders and auditors named unclear expectations for AI tool use as the most common obstacle, at 48%, followed by variation in how individual auditors use the tools. Technology and tool problems such as model selection and data access ranked below both. More respondents pointed at how their colleagues work than at the software.
When everyone uses a tool their own way, the department gets variable output and no basis for comparing one engagement to the next. Structured use cases for high-value workflows are the fix Gartner puts forward. Currently, 12% of respondents are piloting them.
Why this matters for executives and strategy
Audit committees and boards will eventually ask what AI is delivering. The CAEs who cannot answer that question today are operating on borrowed time. The path forward is not more tool experimentation - it is a formal strategy that defines where AI gets used, how output gets validated, and which metrics determine whether the investment was worth it. For senior leaders building that capability, an AI Learning Path for CEOs can provide the framework to connect AI deployment to measurable business outcomes before the board asks the hard question.
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