For thousands of years, every major technological advancement in finance has promised the same thing – speed. Looking back at some of the great innovations in the space such as the abacus, double-entry bookkeeping, and spreadsheets, each one drastically improved efficiency and a finance professional’s daily existence.
What none of these technologies changed, however, was how/if finance teams really understood their company’s inner workings. They still had to build models manually, reconcile conflicting data, and translate financial information into business intelligence that could be acted upon. Technology improved operational efficiency, but the ability to understand what was happening inside a company and determine what should happen next, remained dependent on people.
Bluntly, the current conversation around AI in finance often misses the point. Most AI tools being marketed to CFOs today focus heavily on automation and productivity gains. They promise faster reporting, forecasting, and analysis, yet, while finance teams have spent decades trying to perfect this process by operating more efficiently, the operational burden has only expanded alongside that progress.
Time was never really a constraint for them. Finance teams have learned to move faster, but all that’s bought them is earlier deadlines. The work itself hasn’t evolved with what businesses need, they still deliver the same information, just sooner. It’s the judgment behind the data that makes finance truly impactful. The teams that thrive won’t be the ones reporting faster, they’ll be the ones thinking ahead and proactively guiding the business on where it should go next.
The growing complexity facing finance leaders
Modern CFOs are operating in an environment where complexity has reached unprecedented levels. Economic uncertainty, geopolitical volatility, and seemingly endless pressure on growth have transformed the role of finance from a reporting to a business intelligence function. It’s not enough now for finance teams to merely explain what happened last quarter, they need to help their companies shape what will happen next.
Consequently, the finance team has become the central information hub for a contemporary business. Every department routes questions through the finance team, such as headcount modelling, pricing scenarios, cash flow projections etc, with finance increasingly acting as the human API connecting the business plan to the rest of the company.
The result is that many finance leaders spend more time reacting than leading. Instead of proactively guiding decision-making, they become trapped servicing sporadic requests, pulling data, and translating information between departments. Irrespective of how much faster tools become, the operational burden has kept growing.
Different departments also operate with entirely different priorities, KPIs, and languages. Sales focuses on pipeline, marketing on attribution, while operations prioritise efficiency and delivery. Finance must sit in the middle of everything trying to group disparate perspectives together into a coherent picture of business performance. The conversations that define modern business around where to invest, where to make cuts, and where to double down, often become buried beneath reconciliation work and disjointed reporting processes. But it doesn’t have to be this way.
Why many AI solutions still fall short
Some organisations are layering large language models onto spreadsheets to accelerate analysis. And yes, these tools can save time. But they fundamentally lack governance, consistency, and legacy knowledge.
While others are investing heavily in custom-built AI tools, many quickly discover they have simply replaced one operational burden with another. What’s more, internal tools require ongoing maintenance and technical skills to scale them effectively. When key employees leave, the crucial knowledge often leaves with them.
Then there are AI agents layered onto rigid legacy platforms. While they may introduce automation, finance leaders are still responsible for managing disconnected and fragmented systems. While these approaches can make finance a little bit faster here and there, very few actually improve how businesses make decisions.
The new role of the CFO
The sole aim of a CFO should not be to simply make finance faster. They exist to ensure an organisation can operate with more clarity. This requires an entirely different approach to the role the finance function has traditionally played.
Historically, finance teams acted as gatekeepers of arguably obscure information. Their role was to pull numbers together, validate them, and explain said numbers to the wider business. However, AI is making financial insight increasingly accessible across companies, and as access improves, the role of finance itself changes.
The repetitive work that once consumed finance teams – e.g. pulling reports, answering ad hoc requests, manually gathering data – is becoming automated. But automation does not reduce the importance of financial expertise. If anything, it increases it. When everyone has access to more data and more analysis, human judgement is what makes the real difference.
Today’s finance leaders are responsible for shaping how businesses think and prioritise. That means determining which metrics truly matter, embedding business context into financial systems, and helping leadership teams move faster with greater confidence.
The leading CFOs will be those capable of building systems that anticipate what their company needs to know before questions are even asked. This is not just a more efficient version of the finance function we already know. Tomorrow’s finance teams won’t just report to the business, they will help it think.
