How IT Audit Teams Are Actually Embracing AI Right Now

Last updated November 6, 2026

When AI and IT audit come up together, many people ask whether IT audit is still a safe career to get into. They point to the World Economic Forum’s 2025 Future of Jobs report, which lists accountants and auditors among the roles it expects to shrink, and wonder how much of the work will still be there in a few years.

People who run internal audit teams see it differently. AI is handling more of the routine testing, and the new work around AI is growing faster than most teams can staff for.

AI is taking over the routine testing

The mechanical part of the job is shrinking. Few auditors will miss spending thirty hours verifying access logs or copying sample populations between spreadsheets. A 2026 Gartner survey found that 93% of audit teams already use AI in some form, and sixty percent use it specifically to help draft audit reports.

In practice, language models and scripts work through routine testing populations, draft first-pass walkthrough documentation, and flag anomalies in datasets too big to check by eye. An auditor still decides what to test, judges whether a control works or only looks good on paper, and signs their name to the conclusion.

The new work: checking how companies use AI

Companies are rolling out machine learning models, automated workflows and AI tools across their business units, and most of those tools go live before anyone puts controls around them. Reviewing them is messier than routine testing, and the demand is growing faster than most audit teams can staff for.

IT auditors are getting pulled into meetings where leadership has realized that nobody can tell whether a new system is leaking data, making biased decisions, or breaking compliance rules. Who approved the model going into production? Is anyone watching it for drift after launch? Is there a human checkpoint before an AI decision reaches a customer or an employee? Those are audit questions, and most companies don’t have anyone asking them yet.

ISACA now offers an AI audit credential

In May 2025, ISACA, the body behind the CISA, launched a new credential called Advanced in AI Audit. Credentialing bodies add a track like this when employers need the skill. Standard IT general controls were written for systems that do what they’re told. They don’t cover a model that hallucinates financial data, training data that has been corrupted without anyone noticing, a prompt injection that turns a chatbot against its own company, or an AI agent making an unmonitored call to an outside service.

What AI in IT audit looks like on a real engagement

Say a company starts using an AI tool to screen job applicants, flag loan applications for a closer look, or draft customer responses before a human sends them. The IT auditor checks whether the company controlled how that tool got deployed. Who signed off on using it for that purpose? When the model gets something wrong, is there a documented process for a human to catch it, or does the mistake go straight out the door? Is anyone tracking whether its outputs have shifted over time, and would the company notice if they had?

None of those questions require you to build machine learning models. They need the skill good auditors have always needed: knowing what evidence would prove a control is real, and being stubborn enough to ask for it.

Which auditors are at risk

The auditors with the most to worry about are the ones who only know how to ask for screenshots and check tick marks against last year’s workpapers. Auditors who learn how machine learning systems fail and how data pipelines get poisoned, and who can hold developers to a risk standard, are in a stronger position than ever.

If AI is taking over more of your current job every quarter (copywriting, admin work, entry-level operations), you are unlikely to find a field AI won’t reach. Look instead for work where people review and test AI and hold the company accountable for how it’s used. IT audit is that kind of work.

Where to start

You don’t need a technical background to start. You need the fundamentals: what a control is, how a finding gets written, and how governance works inside a company. You can learn those in weeks, and AI audit work builds on them. The first session of the MasterClass covers AI and the future of IT audit, and the rest of the curriculum builds on it.

If the WEF report has you worried about your current field, read past the headline. The same report also describes the shift that is creating demand for this one.