CFOs Bet Big on AI—but RGP Finds Most Finance Teams Aren’t Ready to Cash In

Artificial intelligence is rapidly becoming the centerpiece of finance transformation. But according to new research from RGP, most organizations are trying to build that future on shaky ground.

In its latest flagship report, The AI Foundational Divide: From Ambition to Readiness, the global professional services firm lays out a stark disconnect: while 66% of CFOs expect AI to deliver significant ROI within the next two years, just 14% say they’re seeing meaningful value today. The gap isn’t about enthusiasm—it’s about execution.

Based on a survey of 200 U.S. CFOs across technology, healthcare, financial services, and CPG/retail, the study paints a picture of finance leaders racing toward AI adoption while being held back by fragile data, aging systems, immature governance, and widening workforce capability gaps.

AI Optimism Is High. Readiness Is Not.

The most striking takeaway is how confident CFOs remain despite structural constraints. Only 10% of respondents say they fully trust their enterprise data, and 86% report that legacy systems are actively limiting AI readiness. Yet expectations for near-term AI payoff continue to climb.

That tension defines what RGP calls the “foundational divide”—a growing mismatch between AI ambition and the operational basics required to scale it responsibly.

Scott Rottmann, President of Consulting Services at RGP, sums it up bluntly: finance leaders are being asked to orchestrate AI-driven transformation without the systems, data, or talent to support it. In other words, strategy is outpacing infrastructure.

CFOs Are Now the De Facto AI Leaders

One of the more telling findings is who owns AI success. Nearly half of CFOs (48%) say they are ultimately responsible for ensuring AI delivers measurable value—more than any other C-suite role.

That influence now stretches well beyond budgets. CFOs report growing authority across investment prioritization, enterprise risk, talent strategy, and digital transformation. As AI reshapes forecasting, compliance, and decision-making, finance has become the connective tissue tying technology to performance.

The problem: accountability is rising faster than readiness.

Data: The Biggest Bottleneck—and the Least Fixed

If there’s a single thread running through the report, it’s data. More than one-third of CFOs (35%) cite data trust as the top barrier to AI ROI, making it the most commonly named inhibitor.

Yet investment hasn’t followed awareness. Many organizations acknowledge data quality issues but continue to underfund modernization efforts, increasing the odds that AI pilots stall before reaching scale. Without clean, reliable, and well-governed data, AI initiatives struggle to move beyond experimentation.

The result is a familiar pattern: promising proofs of concept that never become production-grade capabilities.

Governance Is Improving—but Inconsistently

AI governance is no longer an afterthought, but maturity varies widely. While 69% of CFOs say they have advanced or established AI risk frameworks, nearly one-third still rely on developing or informal approaches.

That inconsistency becomes riskier as AI moves deeper into core operations, financial decision-making, and customer-facing workflows. Without coordinated ownership and clear standards, organizations expose themselves to compliance, reputational, and operational risks that can quickly outweigh AI’s benefits.

In short, governance progress is real—but uneven and far from complete.

Talent Is the Quiet Crisis

Technology may get the headlines, but people remain the limiting factor. More than two-thirds of CFOs (68%) point to skills gaps as a major obstacle to achieving AI ROI. At the same time, collaboration between CFOs and CHROs is weakening in one out of four organizations.

That erosion matters. AI transformation depends as much on reskilling, role redesign, and change management as it does on algorithms. When finance and HR fall out of sync, the talent foundation required for AI adoption erodes—slowing progress just as expectations rise.

Big Companies Are Pulling Ahead

The report also highlights a widening divide between large enterprises and mid-market firms. CFOs at organizations with $10B+ in revenue report stronger data foundations, more mature governance, faster AI adoption, and earlier returns.

For smaller firms, the implication is clear: without deliberate investment in foundations, the AI gap will become a competitive gap. Scale alone doesn’t guarantee success—but it does make it easier to fund modernization and attract scarce AI talent.

What CFOs Can Do Now

RGP doesn’t just diagnose the problem—it outlines a path forward. The firm urges CFOs to focus less on AI hype and more on fundamentals, including:

• Modernizing data architecture and reducing technical debt

• Establishing clear ownership for AI governance and risk

• Building cross-functional talent strategies across finance, IT, and HR

• Shifting from cost-focused metrics to performance-driven outcomes like forecast accuracy, decision speed, and risk reduction

The message is pragmatic: AI readiness is not a single initiative, but an operating model change for finance leadership.

The Bottom Line

AI may be inevitable in finance—but value is not. RGP’s research makes one thing clear: organizations that fail to strengthen their foundations risk falling permanently behind, no matter how ambitious their AI strategy sounds.

As Rottmann puts it, the next phase of AI won’t be defined by experimentation, but by execution. CFOs who modernize intentionally and lead cross-functional change won’t just adopt AI—they’ll define how it reshapes enterprise performance over the next decade.

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