AI Won’t Transform Finance Until We Transform How We Work

Why CFOs Must Focus on Process Before Technology to Unlock the Real Value of AI

For all the bold predictions about artificial intelligence transforming the finance function, the reality on the ground feels very different. While AI headlines promise revolutionary change, most finance teams today are still buried in spreadsheets, chasing down data, and spending late nights manually fixing reports. Technology has advanced dramatically, but the work of finance hasn’t changed nearly as much. This disconnect is not due to a failure of AI itself, but rather a failure to recognize that technology alone cannot fix the way work gets done. If CFOs want to capture the true value of AI, they must look beyond platforms and focus on the very design of their processes and workflows.

The heart of the challenge is this: AI doesn’t automatically transform a broken process; it simply exposes the inefficiencies that already exist. Many finance processes were never designed for speed, adaptability, or automation. Instead, they evolved over time to support control, compliance, and consistency. These legacy workflows may have served their purpose in an earlier era, but they now stand in stark contrast to the dynamic, data-rich capabilities of modern AI tools. When AI enters this environment, it often reveals how much effort is wasted on low-value tasks like copying data between systems, reconciling reports, or preparing static presentations. Rather than unlocking insight, AI pilots can quickly become stuck in the mud of outdated processes that were never built to handle the speed and flexibility AI offers.

Consider how most finance teams spend their time today. The typical monthly forecast cycle involves countless hours gathering data from disconnected systems, validating numbers, adjusting assumptions, and aligning narratives across multiple stakeholders. Analysts spend far more time assembling data than analyzing it. The financial close process often resembles a chaotic relay race, with teams handing off spreadsheets and narratives in a mad dash to meet reporting deadlines. These realities are not the result of poor technology choices but of legacy work design. Without addressing how work happens day-to-day, even the most advanced AI tools become little more than expensive add-ons that fail to deliver real impact.

Where AI is showing true promise in finance is not in massive enterprise platforms or standalone dashboards, but in small, targeted interventions embedded directly into daily workflows. Increasingly, organizations are discovering value when AI acts as an assistant, quietly removing friction from common tasks. This could be a generative AI tool embedded within Excel that helps analysts run scenarios faster. It could be a natural language processing tool that drafts variance explanations based on system data. It might be an AI agent that automatically routes journal entries for approval or flags unusual transactions during the close process. In all these cases, the technology isn’t replacing finance professionals—it’s amplifying them by taking on repetitive, rules-based work so they can focus on higher-value activities.

This shift from adjacent AI tools to embedded AI capabilities marks an important evolution in how CFOs should approach transformation. It requires moving from a technology-first mindset to a process-first mindset. The most successful finance leaders are no longer asking, “Which AI platform should we buy?” Instead, they are asking, “Where does work slow down today, and how could AI remove friction?” This reframing leads to a very different kind of transformation journey—one grounded in redesigning workflows, clarifying data flows, and empowering finance teams to experiment with new tools in safe, low-risk environments. Rather than treating AI as an IT project, these leaders treat it as an operational design challenge.

Ultimately, the promise of AI in finance will not be fulfilled through software alone. It will be fulfilled through the careful and intentional redesign of how finance work happens. This is not simply about efficiency gains or cost reduction. It is about freeing finance professionals to focus their energy on insight, strategy, and decision support—the very areas where human expertise and judgment remain irreplaceable. AI can automate the busywork of finance, but it cannot automate curiosity, creativity, or business acumen. Those capabilities come from people, supported by technology that enables them to do their best work.

As CFOs look ahead, the path to realizing AI’s potential begins not with new tools, but with new questions.

• Where in your organization is work harder than it needs to be?
• Where are people still performing tasks that could be automated or assisted?
• Where is valuable time being lost to manual data preparation or communication gaps?
• And most importantly, if you were designing this process today—from scratch—with AI as an available tool, how would you design it differently?

The future of finance will not be defined by the technology organizations buy, but by how well they redesign work to take advantage of that technology. AI has already arrived. The real question is whether our processes, workflows, and ways of working are ready to meet it. Transforming finance is not about replacing people with machines. It’s about freeing people from tasks machines can do better, so they can focus on the work that truly drives value. That future is possible—but only if we’re willing to transform how we work first.