By Razzak Jallow
Finance has always evolved alongside technology, from calculators to spreadsheets to SaaS. Today, AI is rewriting the rules again. To stay relevant, CFOs must not only adopt new tools but also nurture curiosity, adaptability, and fluency in AI among their teams. The finance leaders of tomorrow are already preparing today.
The shifting skill curve in finance
Every decade has reshaped what it takes to succeed in finance. In the 1990s, financial professionals relied on their HP 12C calculators to run complex formulas at speed. By the 2000s, spreadsheet mastery became the single most valuable skill. The 2010s brought the rise of SaaS platforms and ERP systems, requiring accountants to integrate data across multiple tools.
Now, as we progress through the 2020s, the skill curve is shifting again. While spreadsheets and planning systems remain important, they are no longer the pinnacle of efficiency. Instead, the ability to harness AI tools, particularly through effective prompt engineering, is rapidly becoming the differentiator between average and exceptional finance teams.
The lesson is clear; what makes finance professionals valuable is not static expertise, but the ability to adapt to each technological era.
Building a future-ready finance team
Technology shifts don’t just redefine tools; they redefine talent. As AI reshapes finance, CFOs must rethink how they build and support their teams.
The key quality to prioritise is curiosity.
In previous decades, the most valuable employees were those who pushed the boundaries of spreadsheets, learning pivot tables, experimenting with macros, and finding ways to make Excel do more than anyone thought possible. In the AI era, the most impactful employees will be those who actively experiment with generative tools, not only for work but in their personal lives.
Someone who builds a simple AI workflow to streamline a personal project is exercising the same muscles that will make them invaluable at work. This spirit of experimentation is difficult to teach from scratch, which is why CFOs must look for it in the hiring process and cultivate it internally through a culture of continuous learning.
Early wins – and limitations
The most promising use cases for AI in finance today are narrow but powerful. Transaction matching, for example, has long frustrated teams. Rules-based engines struggled to capture edge cases, leaving matches incomplete and requiring extensive manual work. With AI, transaction matching that once left teams bogged down in exceptions can now be handled far more efficiently. Instead of combing through unresolved items, accountants can redirect their focus toward analysis and insight.
Other applications, like AI-assisted scenario planning in FP&A, are advancing but still require careful oversight. The complexity and sensitivity of financial forecasts mean CFOs must balance innovation with prudence, ensuring outputs can be validated and explained. The risk of treating AI as a ‘black box’ remains a serious concern.
Why AI is different
Finance is no stranger to automation. Rules-based engines and reconciliations software have long eliminated tedious tasks. But AI is unlocking the ability to solve bespoke problems that never justified expensive software solutions.
Every finance team has a ‘long tail’ of small but persistent challenges; an obscure reconciliation issue that takes 2 days each month, or a recurring one-off report built manually in Excel. These problems were too minor to warrant new systems but significant enough to drain time and energy. AI now allows finance teams to automate and streamline such tasks with minimal setup, creating efficiency at scale where none existed before.
At the same time, finance’s adoption of AI faces higher hurdles than in other functions. In functions like marketing or sales, teams can often work with approximate answers or directional insights. Finance doesn’t have that luxury, every number must stand up to audit, regulatory, and compliance scrutiny. Even a small error can carry outsized reputational or financial consequences.
This demand for precision means CFOs must rigorously evaluate AI tools for transparency, auditability, and compliance readiness, not just speed or cost savings.
The CFOs role in leading through change
CFOs are uniquely positioned to guide this transition. More than adopting new tools, their role is to ensure finance remains a trusted source of truth for the business. That requires balancing innovation with governance, experimentation with compliance, and speed with accuracy.
The next decade will reward finance leaders who invest in both technology and people—those who champion AI adoption while cultivating adaptable, AI-fluent teams. Just as spreadsheet mastery became a career superpower in the 2000s, fluency in AI will be the defining skill of the 2030s.
The future of finance won’t be about replacing professionals with machines. It will be about empowering professionals with smarter tools and hiring people curious enough to use them creatively.
About the Author
Razzak Jallow is Chief Financial Officer at FloQast, where he oversees global finance, accounting, and business operations. With more than 20 years of experience in finance leadership, he is passionate about leveraging technology to modernise the finance function and preparing teams for the next wave of innovation.
