As AI shifts from experimental pilot projects to a core operational necessity, the CFO has emerged as the primary architect of enterprise strategy. Matthew Rodgers, Executive Vice President, EMEA at OneStream, tells us why the finance function is uniquely positioned to turn AI investment into measurable business value and why high-quality data is the new non-negotiable for the modern C-suite.
The role of the Chief Financial Officer is undergoing a fundamental transformation. No longer confined to the boundaries of recordkeeping and reporting, today’s CFO has emerged as the primary architect of enterprise AI strategy.
We sat down with Matthew Rodgers, Executive Vice President, EMEA at OneStream, to discuss why finance is taking the lead on artificial intelligence, how boards are shifting their expectations, and why the “pilot phase” of AI is officially over.
For years, AI was viewed through the lens of IT, a technical implementation to be managed by the CIO. However, Rodgers points out that a significant shift is underway. OneStream’s research highlights a striking trend: 75% of CFOs are now leading enterprise AI strategy. According to Rodgers, this isn’t just a change in title; it’s a recognition that finance sits at the unique intersection of data, performance, and decision-making. He believes that because the finance function possesses a bird’s-eye view of the entire organization, it is the best-placed department to translate AI investments into measurable business value.
“Boards and CEOs now expect CFOs to guide the organization through its AI journey,” Rodgers explains, noting that leadership must focus on solving real operational pain points rather than just chasing tech trends.
The era of AI “curiosity” is rapidly being replaced by “commitment.” Rodgers observes that while the last two years were defined by small, controlled experiments, AI has now become an operational imperative. This is reflected in surging budgets: 83% of CFOs expect AI investment to rise this year.
The driver for this expansion, Rodgers argues, is the need for trusted and contextualized insights in a difficult economic climate. By integrating AI directly into core financial processes and moving toward a unified data model, finance functions are finally moving away from isolated use cases toward enterprise-scale deployment.
Rodgers is clear that the days of buying into “AI promises” are gone. “Boards have stopped buying AI promises they’re now putting their money behind proof that AI is moving the needle on the bottom line,” he says.
When justifying these investments, Rodgers sees boards focusing on three critical areas:
Cost Savings: Reducing operational overhead.
Measurable ROI: Linking spend directly to financial outcomes.
Productivity & Accuracy: Demonstrating improvements in forecasting, close cycles, and capital allocation.
Above all, Rodgers emphasizes that boards require trust. For AI to be successful, it must be embedded into core processes in a way that is transparent, explainable, and fully auditable.
While productivity gains are the “low-hanging fruit” of AI, Rodgers believes the most meaningful impact is felt in decision support. In an uncertain macroeconomic environment, he argues that scenario planning has evolved from a back-office task into a genuine competitive advantage.
By utilizing AI to move from static reports to dynamic, real-time views of performance, finance leaders can respond faster to volatility. This elevates the CFO from a reactive partner to a forward-thinking strategic advisor.
Rodgers notes that CFOs are approaching AI investment differently than traditional tech spending. They recognize that AI is only as good as the data it consumes. Consequently, the focus has shifted to building a trusted, governed data foundation. As the industry moves toward Agentic AI where systems begin to act on information rather than just analyze it Rodgers insists that a single source of truth is non-negotiable. This requires a deepening partnership between the CFO and the CIO/CTIO to ensure that AI outputs are secure and accurate.
As the technology evolves, Rodgers warns that the human element must keep pace. We are witnessing a “collision” between tech, finance, and strategy teams. He believes the modern finance professional must pair a traditional financial foundation with the technical mindset required to challenge and interpret AI-driven insights.
“CFOs must empower teams to bridge the gap between interpreting data and taking strategic action,” Rodgers says. Success in this new era depends on the ability to turn AI outputs into enterprise growth.
Finally, Rodgers predicts that the gap between AI leaders and laggards will soon become a chasm. He believes that organizations seamlessly embedding AI into their operations are already outperforming their peers.
As AI maturity grows, Rodgers concludes that those with high-quality data and mature processes will see their advantages compound, leading to better capital allocation, improved resilience, and ultimately, superior financial performance.