Go big or get left behind 

For decades, financial leadership was built on certainty. Big moves required airtight models. Proof came first. Action followed. AI is upending that model.

“CFOs need to get comfortable with being uncomfortable because ambiguity is not a reason to wait,” says Monica Proothi, VP, Senior Partner and Global Finance Transformation Leader for IBM Consulting®. “It’s a reason to design your AI investment approach differently, not a reason to stop moving.”

Traditionally, finance teams looked backward to verify transactions, reconcile accounts and produce financial statements—and that discipline still matters. But the AI era demands that CFOs look to the future, collaborate with peers across the company to uncover AI opportunities, make educated decisions about which initiatives to fund, build a strategy and then lead the charge forward.

Research shows that 55% of executives believe competitive advantage in 2030 will depend more on speed of execution than on making perfect decisions.¹ Finance, with its enterprise-wide perspective, can be the main force driving strategy and speed of execution, but it requires a change in mindset as well as focus.

“The CFO sits at the intersection of cost, growth, risk and capital—in a way no other leader does,” Proothi explains. “That gives them a holistic line of sight into how the enterprise actually works.” To make the most of this unique position, CFOs need to make three shifts to succeed in the age of AI.

“You’re no longer just closing the books and managing risk,” Proothi says. “You’re actively architecting future performance while protecting current results.”

One question comes up in nearly every finance conversation right now: “What do you fund when the value is real but the ROI isn’t clear?” The instinct to wait—for cleaner numbers, for more data, for certainty—is understandable. But when it comes to AI, it’s also dangerous. “By the time you have certainty, your competitors who didn’t wait have a huge head start,” Proothi says.

Leading CFOs are shifting away from single-purpose efficiency and productivity investments and moving toward AI portfolio-based funding models. Today, roughly 47% of AI spending focuses on efficiency, but by 2030, 62% is expected to flow into product, service and business model innovation.¹ But how? “Think big, start small, act fast,” Proothi says. “Build confidence with early use cases, then reinvest what you learn and save into bigger bets.”

The implication is clear. CFOs need to fund enterprise-wide capabilities, not individual use cases. The metric mix evolves as well. Adoption rates, decision speed, forecasting accuracy and cost-to-serve improvements become leading indicators long before traditional financial returns appear.

In most boardrooms, CFOs are still asked the same question, “What’s the ROI?” But in a world being rapidly transformed by AI, they need to reframe the question to be “What’s the cost of waiting?” AI is changing how work gets done, how value is created and how advantage is built. In that context, the biggest risk isn’t acting with imperfect financial information. It’s letting uncertainty delay action.

CEOs respond to financial exposure, and according to Proothi, “The most powerful thing a CFO can do isn’t argue that AI is worth the risk. It’s showing what the risk of not acting looks like in financial terms.” So, CFOs need to quantify market share erosion and the cost of AI debt while emphasizing the danger to competitiveness of delaying investments—because it gets harder and more expensive to close that gap as time goes by.

As Proothi puts it, “We’re not betting on an uncertain future. We’re buying protection against probable competitive disruption.”

Finance can’t scale AI on its own. Success depends on collaboration across the C-suite. Working closely with the CEO and board of directors, CFOs can turn ambition into smart investments—bold where it matters, disciplined where it counts. By partnering with CIOs and CTOs, they can focus AI spend on enterprise-wide initiatives that deliver long-term value with clear, risk‑adjusted returns, not one-off AI implementations. And alongside COOs, they can make sure that efficiency and productivity gains are reinvested into growth, not quietly absorbed into the bottom line.

One of the most critical yet overlooked relationships is between the CFO and CHRO. Large-scale AI transformation impacts the financial picture. In fact, by 2030, 46% of companies are more likely to redesign their organizational structure because of AI.¹ Becoming an AI-first company also impacts the employees—the most important investment of all. By 2030, 48% of organizations are more likely to create new job roles because of AI.¹

As Proothi notes, “Reskilling, workforce adjustments, new ways of working—those are finance conversations as much as HR conversations. I’d include talent acquisition in those conversations as well because many prospective employees are gravitating to companies that are serious about AI.”

CFOs also need to keep in mind that they must model the behaviors they expect to see across the organization. This means operating in a new way by switching to continuous planning instead of annual cycles, rolling forecasts instead of static targets, and AI‑augmented insight rather than manual reporting.

Enterprise AI rarely fails because the technology doesn’t work. It fails because organizations move too slowly—or because of rigid funding models, outdated controls and risk aversion.  “This is not a technology transformation,” Proothi says. “It’s a mindset and operating model transformation.”

The CFO’s real superpower in the AI era isn’t predicting the future. It’s designing an enterprise that can move through uncertainty faster than the market by making informed bets, learning quickly and scaling with confidence.