16. 02. 2026

AI in Finance: A New Proving Ground for Finance Leadership

AI is being discussed in finance as an efficiency tool.

And yes, it can be.

But inside many organisations, AI is also doing something quieter and arguably more important: it’s revealing who can lead when the answers aren’t neat.

Because once AI touches reporting, forecasting, controls, or decision support, it stops being purely “process improvement”. It becomes a judgement exercise. And judgement is exactly what modern finance leadership is measured on.

The CFO job has evolved. The expectations have moved even faster.

Boards will always expect grip: strong controls, credible numbers, and a finance function that can be relied on.

But increasingly, finance leaders are being judged on something harder to teach: the ability to steer decisions through uncertainty, trade-offs, and imperfect information without losing control of the basics.

That shift is one of the reasons the market for high-calibre finance leadership in the UK feels tight. It isn’t just a shortage of experience. It’s a shortage of people who can combine technical credibility with commercial judgement and change leadership.

AI projects are not just technology work. They are leadership work.

When AI enters finance, it forces decisions that don’t sit comfortably in one team.

Questions like:

What data can we trust and what needs tighter governance?
Where are the control risks and how do we manage them sensibly?
What can be automated safely and what still needs human judgement?
How do we explain outcomes and limitations to auditors, the board, and the wider business?
Who owns accountability when the output is wrong?

These are finance questions, even when the tools sit elsewhere.

And the people who can answer them in a practical, commercially-minded way tend to stand out quickly.

AI separates technical strength from leadership capability

There’s a difference between being excellent at finance and being excellent at running a finance function.

AI projects often surface that difference.

Not because technical capability stops mattering, but because the work demands more than technical answers. It demands:

the confidence to challenge outputs without making it political
the ability to translate complexity into plain commercial language
the discipline to build governance without slowing everything to a crawl
the judgement to prioritise impact over perfection

That blend is increasingly what “CFO-ready” looks like in real life.

The people who thrive in AI-enabled finance are building CFO muscle

Most finance roles reward precision and certainty.

AI doesn’t always offer that.

Instead, it rewards structured thinking, risk awareness, and the ability to land decisions that move the business forward. In practice, the people leading AI adoption are often developing leadership behaviours that boards recognise:

thinking in scenarios, not certainties
defending decisions, not just numbers
balancing speed with control
influencing across functions without relying on authority
communicating with clarity when the detail is messy

This is not about “being into tech”. It’s about being able to lead through change without losing grip.

A market reality: transformation work changes people’s expectations

When someone takes ownership of automation, AI-enabled reporting, forecasting improvements, or governance frameworks and delivers outcomes, they come out of it with a broader view of what they can do.

That is a good thing.

The risk for businesses is not that people become disloyal. It’s that capability becomes more visible, and scope becomes the deciding factor. High performers want roles that reflect what they’ve proven they can handle.

If progression stays vague, those individuals don’t necessarily leave for more money. They often leave for more responsibility.

What the better-run organisations are doing

The organisations getting value from AI in finance tend to do a few things consistently.

They treat AI projects as a leadership lens, not just a delivery plan.

They pay attention to:

who owns the commercial outcome, not just the process
who can bring stakeholders with them
who can build sensible controls without killing momentum
who can explain risk clearly without hiding behind jargon

And when those people show themselves, they make sure the next step is real: scope, exposure, and a progression path that matches the capability being built.