How to Build an AI-Literate Finance Function

AI literacy in a finance function is no longer a nice-to-have that sits with one enthusiastic analyst. Boards now expect the CFO to have a view on how the finance team uses AI, where it adds value, and where it introduces risk. Deloitte’s late-2025 CFO research found that 87% of CFOs believe AI will be very or extremely important to finance operations in 2026, and AI and automation skills now rank highest for finance capability development. That expectation lands on the finance leader, not on the tools — and building the capability is a leadership task, not a software rollout.

This guide sets out how a CFO or Finance Director builds AI literacy across a finance team: what ‘literate’ actually means at each level, when to hire for the skill versus upskill the people you have, the budget trap that causes most AI investments to underdeliver, and how to lead the change without losing the team. It draws on the current evidence for what separates finance functions that get value from AI from those that do not.

The state of adoption: why literacy is now urgent

The pace has shifted sharply. In a McKinsey survey of CFOs, 44% said they used generative AI for five or more use cases in 2025 — up from just 7% the year before. Where AI has been adopted robustly, McKinsey observed finance professionals spending 20 to 30 percent less time crunching data, and redirecting it toward business-partnering and strategy. Deloitte’s research points the same way: 54% of CFOs now rank integrating AI agents into finance as a top transformation priority for 2026, ahead even of improving data quality.

The implication for a finance leader is that AI literacy is no longer optional or future-facing. The function is adopting AI whether or not leadership directs it, and the gap between teams that use it well and those that use it carelessly is widening. Building literacy deliberately is how a CFO makes sure their function is on the right side of that gap.

What AI literacy means at each level of the finance team

AI literacy is not uniform. The competence a Financial Controller needs differs from what a management accountant or an FP&A analyst needs, and the finance leader needs something different again — the judgement to govern the whole thing.

At the leadership level

The CFO does not need to write prompts. They need to understand what AI can and cannot be trusted with, where accountability sits when an AI-assisted number is wrong, and how to set policy that lets the team move quickly without exposing the business. This is oversight literacy: knowing enough to ask the right questions and to sign off with confidence.

At the practitioner level

Financial controllers, management accountants and FP&A staff need working literacy: the ability to use AI tools on real tasks, to spot when an output is wrong, and to keep a human check on anything that reaches a report or a decision. This is where day-to-day value is created — and where an ungoverned rollout does the most damage.

The 7% trap: why most AI investment underdelivers

The single most important finding for a finance leader building literacy is about where the money goes. Deloitte research has found that around 93% of a typical organisation’s AI budget goes to the technology, and only 7% to the people and processes that determine whether it is used well. Organisations taking this tech-first approach were found to be 1.6 times more likely to miss their expected return on AI investment than those that put people at the centre of the change.

This is the trap. A finance leader who buys tools and assumes literacy will follow is spending against the grain of the evidence. The functions that capture value invest in capability — training, process redesign, change management — not just licences. For the CFO, that means AI literacy is a budget decision as much as a training one: some of the money earmarked for tools should be redirected to the people who will use them.

The hire-versus-upskill decision

Most finance leaders face a version of the same question: hire someone who already brings AI fluency, or develop the team you have? The answer is rarely all one or the other, but it should be deliberate.

• Upskill when the team is strong, stable and open to new methods. AI literacy layers well onto solid accounting fundamentals — a good management accountant who learns to use AI well is more valuable than a newcomer who knows the tools but not the numbers. Notably, around half of CFOs say they plan to hire or promote from within to control workforce costs in 2026, which favours upskilling where the base is sound.
• Hire when you are building a capability the existing team cannot credibly reach, or when you need someone at leadership level who has already governed AI adoption elsewhere and can set the direction.
• Hire at leadership level first if the function has no one who can own AI governance. Tools without oversight is the failure mode boards worry about — and the one that creates real exposure.

For many growing businesses the fastest route is to bring in a finance leader who has already done this — often on a fractional basis — to set the framework, then upskill the permanent team beneath it. FD Capital places finance leaders specifically for this kind of capability-building mandate.

Change management is where literacy succeeds or fails

The technical steps of adoption are the easy part. The hard part is bringing the team with you. Deloitte’s research points to poor adoption and resistance to change even as AI tools spread, with finance professionals lacking clarity on why the investment is being made and what it means for their roles. Workers engage with AI most when it visibly drives efficiency, reliability, recognition or better decisions — and disengage when it feels like a threat imposed from above.

For the finance leader, this means naming the fear directly — that AI is there to replace people — and reframing the change as a shift in what the team spends its time on: less data-crunching, more analysis and business-partnering. A leader who ignores this loses the team; one who leads it well builds a more capable function. The evidence is consistent that humans, not technology, are where the enduring advantage sits.

What an AI-literate finance function looks like in practice

It is worth being concrete about the destination. An AI-literate finance function is not one where everyone uses AI constantly; it is one where AI is used deliberately, by people who know its limits, inside clear rules. In practice that looks like a handful of observable things.

• A named owner for AI use in the function, and a short written policy the team has actually read.
• A team that can articulate what AI is trusted to do and what it is not — and who treats an AI output as a first draft to be checked, never as an answer to be shipped.
• Routine tasks — variance commentary, reconciliations, report drafting — measurably faster, with the freed time visibly redirected into analysis and business-partnering rather than absorbed silently.
• New tools assessed before they are used, not discovered in use.
• A finance leader who can answer a board’s questions about AI with evidence rather than reassurance.

A function with these traits captures the productivity the evidence promises while staying on the right side of the risk. A function without them may be using AI heavily and still be exposed — which is why literacy, not adoption, is the thing a finance leader should actually be building toward.

What this means for how you hire

The finance leadership spec has changed. A CFO or FD hired today is increasingly expected to bring not just financial leadership but the ability to build an AI-literate team beneath them — and to do it without falling into the tech-first trap. When you next recruit at leadership level, AI-adoption and capability-building belong in the brief as a real, assessable competence, not a buzzword. We explore this in our companion guides on hiring finance leaders in the AI era and building a finance function AI roadmap.

Call 020 3287 9501 or email recruitment@fdcapital.co.uk to discuss a CFO or Finance Director appointment where building an AI-capable finance team is part of the brief.

FD Capital — CFO and Finance Director Recruitment

Fellow of the ICAEW | Placing finance leaders who can build capable, modern finance teams since 2018. We recruit permanent, interim and fractional finance leaders across the UK. 4,600+ network. 160+ placements. Shortlists in 3–7 working days.

This guide is general information for finance leaders and does not constitute professional advice. Businesses should take their own advice on their specific circumstances.