How IT Audit Teams Are Actually Embracing AI Right Now

Last updated — September 28, 2026

The honest part first

Let’s not dodge the AI question. The World Economic Forum’s 2025 Future of Jobs report lists accountants and auditors among the roles it expects to shrink. That’s a real finding, not exaggeration used to sell fear. The part of the job it’s talking about is the repetitive, checklist-style work, pulling the same evidence and running the same test the same way every quarter.

If you’re worried AI is coming for your current job, that worry is reasonable. The mistake is assuming every job that touches “audit” or “compliance” is exposed the same way. It isn’t. The clerical end is exposed. The technical end is where the field is actually moving, and it’s growing.

What audit teams are actually doing with AI right now

Here’s what that shift looks like in practice, not as a prediction but as something already happening. A 2026 Gartner survey found that 93% of audit teams already use AI in some form. Most of that isn’t dramatic. It’s AI drafting the first version of a finding, or summarizing a control’s documentation before a human reviews it. Sixty percent of teams already use AI specifically to help draft audit reports.

None of that removes the auditor from the process. Someone still has to decide what to test, gather the actual evidence, judge whether a control is really working or just looks like it is on paper, and sign their name to the conclusion. AI speeds up the writing. It doesn’t do the judgment.

The bigger shift: auditing AI itself

Here’s the part that doesn’t get talked about enough. Every company adopting AI right now, in every department, is creating a new category of risk. Who approved the model going into production. Is anyone monitoring it for drift or bias after launch. Is there a human checkpoint before an AI-generated decision actually affects a customer or an employee. Those are audit questions, and most companies right now don’t have anyone asking them yet.

ISACA, the body that issues the CISA certification, launched a new credential in May 2025 called Advanced in AI Audit. A credentialing body doesn’t build a whole new certification track for a niche that doesn’t exist yet. It built one because organizations are adopting AI faster than anyone is governing it, and that gap is already turning into real audit work.

What that actually looks like in a real audit

Say a company starts using an AI tool to screen job applicants, or to flag which loan applications need a closer look, or to draft customer responses before a human sends them. An IT auditor’s job isn’t to build that tool or to argue whether it should exist. The job is to check whether the company controlled how it got deployed. Who signed off on using it for that purpose. What happens when the model gets something wrong, is there a documented process for a human to catch it, or does it just go out the door. Is anyone tracking whether its outputs have shifted over time, and would the company even notice if they had.

None of those questions require you to build machine learning models yourself. They require the same skill a good auditor has always needed: knowing what evidence would prove a control is real, and being stubborn enough to ask for it. The AI part is new. The audit method underneath it isn’t.

What this means if AI is already eating your current field

If you’re in a role where AI is doing more of your job every quarter, copywriting, admin work, entry-level operations, the honest reframe isn’t “find a field AI can’t touch.” No field gets to claim that. The better move is finding a field that sits on the other side of AI, the side that reviews it, tests it, and holds it accountable, instead of the side competing against it for the same output.

That’s the actual shift happening in IT audit. Not a promise that the field is AI-proof, since nothing honestly gets to claim that. It’s a field that’s already restructuring itself around governing AI rather than getting replaced by it, with a professional body building the credential to prove it, and teams already using the tool day to day instead of pretending it isn’t there.

Where to start

You don’t need a technical background to start learning this. The fundamentals, what a control is, how a finding gets written, how governance actually works inside a company, come before any AI-specific material. The AI layer sits on top of a foundation that’s still learnable in weeks, not years. This is exactly why the first class of this program now opens with a segment on AI and the future of IT audit, before anything else gets covered. It’s not an add-on. It’s the framing the rest of the curriculum builds on.

If the WEF report is what’s making you nervous about your current field, it’s worth reading past the headline. The same report is describing the exact shift that’s opening this one up.