On a recent afternoon in downtown Boston, we sat around a cluster of tables with fellow CFOs and other business leaders. The topic for discussion? How AI is transforming the finance function and enterprises at large.
It’s not a novel topic. Business leaders have (or should be having) these conversations regularly. But after an hour of chatting, two novel themes emerged. Lessons many of us had been mulling, but hadn’t fully articulated.
The first: At organizations where AI adoption succeeds, companies transform their entire operating model, not select pieces. And second: In those same organizations, CFOs play an outsized role as agents of transformation.
Many organizations have a myopic view of transformation: Use this AI model or tool, focus on that task or function. A patchwork approach can provide incremental productivity gains, but it’s impossible to scale. Progress stays siloed, but no true integrated intelligence emerges. The coveted productivity flywheel remains out of reach.
Instead, business leaders need to weave AI into the DNA of their very operating model. Don’t focus on niche use cases. Think big about where AI is taking the market, and how your company can grow, compete, and win in that context. AI should play a major role in decisions about portfolio optimization, capital allocation, and enterprise-wide productivity initiatives. At IBM, this operating-model approach created $4.5 billion in productivity gains in just two and a half years. This then enabled a flywheel effect: incremental financial flexibility for reinvestment to accelerate growth.
During that Boston conversation, we also agreed CFOs are uniquely placed to lead the operating model transformation. The best CFOs sit at the epicenter of a company, blending strategic vision, business model innovation, and organizational agility. In the era of AI, this skill set is more important than ever. CFOs can connect AI strategy to execution, insight to action, and technology to value. They can also shape a company’s future workforce. If CFOs act as a traditional guardian of stability, they miss an opportunity. They must step up from functional partner to AI strategy co-architect. If they don’t, they – and their companies – risk obsolescence.
That evolution in the CFO role reflects a broader shift in AI itself, moving from experimentation to enterprise accountability. For years, many companies approached AI with an expansion logic: launch pilots, distribute tools broadly, encourage experimentation, and assume value would follow. In some cases, it did. In many others, what looked like momentum was often just activity.
As AI investment grows, that distinction becomes harder to ignore. Finance leaders can no longer afford to fund AI on the assumption that value will emerge over time. They need to know where it is being applied, what business process it is improving, and whether the return is material enough to justify continued investment.
This is why the next phase of AI transformation will be defined less by experimentation and more by operating discipline. The companies that pull ahead will be the ones that treat AI with the same rigor and accountability they apply to any other major business investment, redesigning core workflows end to end, and integrating AI agents, data, and governance into how the business actually runs, not just how individual tasks get completed.
For CFOs, this requires a broader shift in posture. The job is no longer just to track performance after the fact. It is to design how value gets created in the first place. That means asking harder questions up front. What specific business outcome do we want to achieve, and will it drive returns, revenue growth, and margin expansion in three-to-six-month increments? Is there clear accountability for outcomes across the business, not just within a function? And if productivity improves, is the organization prepared to capture that gain and put it back to work?
There’s no shortage of talk about AI transformation, much of it noise. But that afternoon in Boston we landed on a clear signal – one that is further validated by IBM’s new Institute for Business Value CFO study. It’s less about specific AI models, more about the larger operating model. And this makes CFOs indispensable.
Operating-model transformation requires both strategic vision and rigorous accountability, and only finance leaders sit at the intersection of both. By 2030, most CFOs say they will have
greater responsibility for shaping operating models, organizational structures, workforce strategies, and enterprise value creation, with 62% already taking on greater responsibility for enterprise technology or AI strategy leadership.
The finance leaders who embrace that reality can do more than contain cost. They can help build an operating model where productivity unlocks capacity, capacity funds reinvestment, and reinvestment drives growth – a value creation flywheel.
#
The post AI is redefining operating models. CFOs can lead the transformation appeared first on Fortune.
