There is no shortage of commentary on what artificial intelligence means for the future of work. Most of it oscillates between utopian enthusiasm and existential anxiety. In internal audit the reality, as ever, is more nuanced, more interesting, and considerably more practical than either extreme suggests.
After thirty years of placing internal auditors in financial services firms, I have seen the profession absorb a lot of supposedly transformational change. Data analytics was going to replace the traditional auditor. Regulatory technology was going to automate compliance. Agile was going to reinvent how audit functions operated. Each of these developments has genuinely changed the profession, but the auditors who thrived were the ones who understood the technology well enough to use it, not the ones who feared it or, conversely, the ones who assumed it would do everything for them. AI is different in scale, but not in kind. Here is what we are actually seeing in the market.
WHAT FINANCIAL SERVICES FIRMS ARE DOING WITH AI IN AUDIT RIGHT NOW
The largest global banks are furthest ahead. Several of our clients at bulge bracket level already have dedicated AI audit teams, small, specialist groups whose entire remit is providing assurance over AI models, algorithmic decision making, and the data pipelines that feed them.
These are new roles that did not exist five years ago, and demand for people who can fill them is significantly outpacing supply.
Beyond the largest institutions, the picture is more varied. Most audit functions are using AI tools to some degree, to analyse larger datasets more quickly, to draft initial versions of audit reports, to automate routine testing procedures. The efficiency gains are real. A process that once took a week of manual work can in many cases be completed in hours.
But here is what the technology cannot yet do: it cannot exercise judgement. It cannot build a relationship with a Chief Risk Officer or CFO. It cannot read the room in a difficult conversation about a significant finding. It cannot understand the political context of an audit committee presentation. And it cannot, on its own, determine whether the risk it has identified actually matters.
These are the things that experienced internal auditors do every day. They are, if anything, more valuable in an environment where the routine work is being automated.
WHAT THIS MEANS FOR CANDIDATES
If you are a Senior Auditor or Audit Manager in financial services in 2026, the question is not whether AI will affect your role, it will. The question is whether you are going to engage with it proactively or wait for it to happen to you. Practically, this means:
Understanding the basics of how AI models work, even if you are not a data scientist. You do not need to be able to build a machine learning model. You do need to understand enough to ask the right questions about how one has been built, what data it was trained on, and where its limitations lie.
Getting comfortable with AI-assisted audit tools. The firms investing in these tools need auditors who can use them effectively, not just auditors who can audit them. Familiarity with tools like data analytics platforms, automated testing software, and AI-assisted report drafting is increasingly a baseline expectation.
Doubling down on the skills that AI cannot replicate. Stakeholder management, professional scepticism, the ability to communicate complex findings simply and persuasively, these are the capabilities that will differentiate the best auditors from the average ones in an AI-assisted world.
For those considering a move, we are seeing a clear premium in the market for auditors who can demonstrate genuine engagement with technology, not just awareness of it. If you have led an AI audit, contributed to your firm's AI governance framework, or developed expertise in a technology-adjacent area like cyber or data analytics, that is increasingly attractive to hiring managers.
WHAT THIS MEANS FOR HIRING MANAGERS
For Heads of Audit and Chief Auditors, the challenge is twofold: understanding what AI means for your audit plan, and understanding what it means for your team.
On the audit plan: if your organisation is using AI in any significant way, in credit decisioning, in fraud detection, in customer-facing products, in trading, then your audit plan almost certainly has a gap. Providing assurance over AI systems requires a combination of technical understanding and audit methodology that most teams are still developing. This is an area where the demand for specialist knowledge is acute and the supply of people who genuinely have it is limited.
On your team: the auditors who will add the most value over the next five years are those who combine strong audit fundamentals with genuine curiosity about technology. When hiring, we are increasingly advising clients to weight that curiosity heavily, it is harder to develop than technical knowledge, and it is what determines whether someone will grow with the profession or be left behind by it.
A FINAL THOUGHT
Internal audit has always been, at its best, a function that helps organisations understand and manage the risks that matter most. AI is simultaneously one of those risks and one of the tools available to manage others. The auditors and audit functions that will thrive in this environment are the ones who approach it with the same combination of intellectual rigour, professional scepticism, and genuine curiosity that has always defined the best in the profession.
That has not changed. It never does.
If you would like to discuss what AI means for your internal audit team, your hiring plans, or your own career in financial services, get in touch, we're always happy to talk.