Free Guide · 10-Page PDF

AI in Internal Audit.

How the profession is changing — and what audit leaders need to know before it changes their team.

  • Five trends already reshaping the profession
  • What changes in an auditor's day-to-day work
  • A practical readiness checklist
AI in Internal Audit — A Looom Guide cover
What's Inside
Six sections, ten pages, zero fluff.
01Where Internal Audit Stands TodayPage 3
02What "AI in Internal Audit" Actually MeansPage 4
03Five Trends Reshaping the ProfessionPage 5
04The Future of Work for AuditorsPage 7
05A Practical Readiness ChecklistPage 8
06Key TakeawaysPage 9
From the guide
The gap isn't a talent problem.

Most audit functions are still running on a model built for a slower, smaller version of the business they now oversee. Testing happens on a sample because full-population testing by hand was never realistic. Evidence gets gathered and pasted into working papers by people whose real value lies elsewhere.

The gap isn't a talent problem. It's a capacity problem — and it's the reason "do more with the same team" has become the default expectation of every internal audit function, everywhere.

This is the backdrop against which AI is entering the profession. Not as a novelty, but as a response to a capacity problem that was already becoming unsustainable.

Section 02 Preview
Four concrete shifts in how audit work gets produced.
01

Full-population testing

Test every transaction instead of a statistically defensible slice — changing the underlying assurance, not just the speed.

02

Drafting from evidence

Working papers drafted from uploaded evidence and your firm's knowledge base. The auditor's first draft is already a first draft.

03

Continuous monitoring

Controls and risk indicators watched on an ongoing basis — issues surface while they're still small.

04

Reviewing, not authoring

The auditor's role shifts from producing the first version to critically reviewing one — a different skill, and arguably a higher-value one.

What doesn't change: professional scepticism, ethical judgement, and the auditor's accountability for the opinion they sign.

Section 05 Preview
A practical readiness checklist.

The guide includes a four-part readiness framework covering People (are auditors trained to review AI output critically?), Process (has methodology been revisited for full-population testing?), Technology (do planning, fieldwork, and reporting run in a connected workflow?), and Governance (does someone own the question of where AI output could be wrong?).

Readiness is a People, Process, Technology, and Governance question — not just a software purchase.

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