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Traditionally, finance functions have largely operated in a hindsight frame of mind.

Reports, reconciliations, and audits are retrospective views of cash flows, forecasts are projected from what happened over the last year or quarter, and even something as basic as an expense request often authorises a payment after the fact of purchase.

That operating context, however, is now changing on several fronts at once.

First, business spending is becoming increasingly decentralised, with employees being given more authority over more fundamental costs, rather than going via a central point of control. That can mean faster decision-making around urgent opportunities, and operations that better reflect the needs of globally dispersed teams, but it also creates visibility gaps that mere hindsight can’t cover.

Second, businesses are asking their finance functions to play an increasingly strategic role that enables forward-thinking teams to innovate and transform. Traditional finance approaches struggle to answer questions about what happens if the next quarter’s operating procedure is fundamentally different to the last quarter’s, while also requiring manual effort that limits finance teams’ capacity to engage with those issues creatively.

And third, AI adoption is creating new dynamics – both within finance teams and more widely across businesses – that are challenging for traditional cycles of finance work. It is leading to new patterns of employee behaviour and spending, while also creating new expectations for speed and automation that offering a regular cadence of backwards views does not fulfil.

In this context, sticking to finance as usual is no longer an option: following traditional approaches to finance can risk incurring significant business costs. However, making change in this area needs to be carefully navigated.

The cost of finance as usual

Specifically, it might be tempting to think in terms of directing finance teams to catch up with today’s operating contexts, reskilling them and redefining their roles to better match modern business needs. The evidence shows, though, that finance is no laggard when it comes to seeking out new approaches and methods.

In a survey of 3,500 European finance leaders, Pleo found that 98% are now using AI in their daily processes, actively looking for ways to accelerate their work and the businesses they support.

While upskilling is certainly a factor (as 84% of UK finance leaders agree), we also need to ask why, despite near-universal adoption, many also report that their finance processes are not fit for purpose and that they struggle to move at speed. This question is not an academic one: according to our respondents, the average cost to a business of a missing opportunity due to ineffective approvals in the UK is £231,220.

To answer that question, it is worth thinking from the ground up about what finance teams do every day, and what they could do.

Traditional, hindsight-based workflows are also highly manual workflows: in acting as a point of control for business spending, finance teams have built many checkpoints into their processes, and much administrative work around reporting functions as reassurance that employee-driven processes have been properly executed.

Bolting AI on top of those tasks might accelerate some steps, but that does not transform what finance teams are actually engaged in day-to-day. If they need to shift their focus from control towards enablement, from administration towards strategic input, and from hindsight to future-facing vision, the tools they rely on need to rework finance processes at a much deeper level.

Seeing the future, unblinded by hindsight

Finance professionals represent a unique set of skills and resources within their organisations, with insight into the mechanics of a business that will be essential as the operating context keeps rapidly evolving. They are tasked with granular oversight because they have the capabilities to assess the minute practical details of how businesses run and what they mean for the big picture.

In other words, gaining a view of the top to bottom of a business is how finance functions have delivered on their traditional role, but that input would be far more valuable on a broader stage of business strategy and direction.

That means that, if finance functions are lagging behind changing businesses, it’s the tools and not the teams that need to be rethought. Today, much of their time is spent working around the limitations of their finance stacks, and AI is not generally not having the transformative effect that was promised.

Transformation will come when AI investment stops trying to accelerate what finance already does, and instead clears away the noise of finance so that teams can focus on playing a new, much more valuable role.

An effective, tailored platform for finance should handle the routine workflows like verifying data and labelling expenses by itself, only looping in a person where ambiguity makes it necessary. It should build governance into those workflows rather than requiring human verification after the fact by default. And it should integrate with the tools finance already uses, bringing data to them rather than needing them to work around the tool’s needs.

That way, finance leaders can be freed from the pressure of hindsight, and instead freed up to invest their time into thinking about what comes next.