Free AI diagnosis: 30 minutes, and you leave with a plan

Examples

Examples of AI in audit, and where judgment stays

Seven ways audit teams use AI today, the job the AI does in each, and the decisions the auditor keeps.

Updated 5 min read

The short answer

Examples of AI in audit include testing every transaction instead of a sample, flagging anomalies, reading contracts and documents, gathering evidence, monitoring controls and drafting report sections. The AI prepares the work. The auditor reviews it, forms the conclusion and signs off.

Key points

  • Start with document-heavy, repetitive tests
  • AI flags items; the auditor decides what they mean
  • Simple tools like data extraction are the most common today
  • Every output needs review before it enters the file

Examples

Examples of AI in audit, by task

Each example names the work the AI does and what stays with the auditor.

  • Testing

    Full-population transaction testing

    AI checks every transaction against rules instead of a sample. The auditor investigates the exceptions and judges their impact.

  • Risk

    Anomaly detection in ledgers

    AI flags unusual amounts, timing or counterparties for a closer look. A person decides whether each one is a real issue.

  • Documents

    Contract and document review

    AI reads contracts and pulls out terms, dates and obligations into a table the auditor checks against the books.

    Read the case →

  • Evidence

    Evidence gathering from source files

    AI extracts key data from invoices and statements and matches it to entries. The auditor decides if the evidence is enough.

  • Controls

    Control monitoring between audits

    AI watches approvals, access and payments on a schedule and alerts the team when a control looks broken.

  • Reporting

    Audit report drafts

    AI drafts findings and summaries from the working papers. The auditor edits the wording and owns the conclusion.

  • AI governance

    Auditing the AI itself

    Teams also examine how an AI system was designed, trained and deployed, using frameworks built for that purpose.

    Read the case →

How audit teams use AI today

  • Last year

    15% of audit leaders used generative AI

  • This year

    40% report using it

  • Next year

    83% expect to use more AI

Adoption is growing fast. The Institute of Internal Auditors found that generative AI use among chief audit executives climbed from 15% to 40% in one year, for internal audit work.

Plans point the same way. In a later IIA and AuditBoard survey, 83% of respondents expect their function to use more AI over the next year.

Simple AI comes first

Widely used now

  • Key data extraction
  • Optical character recognition
  • Document matching

Still in development

  • Complex AI tools
  • Broader judgment support

Academic research on audit practice finds that simple AI, such as pulling key data from documents and optical character recognition, is already widely used in audits.

More complex tools are still being developed. That makes document-heavy tests the practical starting point for most teams.

Where the auditor's judgment stays

AI does

  • Test full populations
  • Flag exceptions
  • Extract and match data
  • Draft first versions

Auditor keeps

  • Judging materiality
  • Forming conclusions
  • Signing the report
  • Questioning odd results

Auditors worry about leaning too much on AI. The same research lists fear of overreliance and the need for guidance among the main adoption challenges.

So the rule is simple: AI finds and prepares, the auditor evaluates. Frameworks such as the NIST AI Risk Management Framework help teams build in trust and review.

A safe way to start

  1. 01

    Pick one test

    Choose a repetitive, document-heavy task

  2. 02

    Run both ways

    Compare AI output with the manual result

  3. 03

    Review exceptions

    The auditor checks every flagged item

  4. 04

    Expand

    Add the next test once results hold

Pick one repetitive test, run the AI beside the manual method and compare results before relying on it.

For governance and compliance questions, see our AI audit and compliance guide.

Our data

What AI answers when buyers ask

We asked ChatGPT, Gemini and Perplexity 10 buyer questions about AI audit and compliance. They named 85 companies, and 69% appeared in only one of the three.

CriterionChatGPTGeminiPerplexity
Companies named413945
Sites cited mostholisticai.com and deloitte.com (5 of 10)xcelacore.com (4 of 10)aicompliancevendors.com (4 of 10)

Nexum measurement, October 22, 2026, via DataForSEO: 10 buyer questions to each AI, US English, 30 answers in total. 14 companies appeared in all three. Google showed an AI Overview for 10 of the 10 questions.

FAQ

Questions about AI in audit

  • Full-population testing, anomaly detection, contract review, evidence gathering, control monitoring and report drafting. In each, the auditor reviews the AI's output before relying on it.

  • An AI audit is a structured, evidence-based look at how an AI system is designed, trained and deployed. The IIA also publishes an AI auditing framework focused on risks, governance and controls. See our guide on how to audit AI.

  • Not in the work that matters most. AI handles volume, such as reading documents and testing transactions. Judgment, skepticism and sign-off stay with the auditor.

  • Yes. Research on audit practice shows simple tools like data extraction and OCR are widely used, while complex AI is still being developed.

  • The IIA's 2025 Pulse survey found 40% of chief audit executives using it for internal audit activities, up from 15% the year before.

  • Overreliance. Auditors cite fear of trusting AI too much, plus a lack of guidance. Reviewing every output and following a risk framework limits that exposure.

  • Choose a repetitive test that eats many hours, like matching invoices to ledger entries. Run it beside the manual method first. Our AI strategy guide covers how to pick.

Related

Keep reading

Final step

Pick a time. Let's talk.

You leave knowing which processes to automate first and what each one costs you today, whether we work together or not.

You can keep paying for manual work, or find out this week exactly what it costs you.

What happens on the call

  1. Before

    You answer 3 quick questions when you book, so we come prepared.

  2. On the call

    We find the manual work that costs you most and put a number on it, live.

  3. Decide

    An honest read on whether we're the right fit. If we're not, you'll hear it on the call.

Once you book, we look at your site and tools before the call, so the 30 minutes go to your numbers, not introductions.

Prefer to write first? Email us directly: contact@nexumautomations.com

30 minutes · Video call · Free