Key takeaways:

  • A recent EY study found that only 21% of CFOs rate their AI readiness as "leading" or "advanced."
  • Finance teams with stronger AI readiness are more likely to recognize the technology's potential value in core business functions. According to the report released earlier this month, among CFOs who said they are fully ready to adopt AI, 71% believe the technology has significant potential in growth forecasting—that is, using AI to predict demand and explore new growth paths.
  • The report states: "This highlights that building AI capabilities and conducting experiments are prerequisites for recognizing its full potential, with advanced teams demonstrating a broader and more consistent understanding of AI's value across various use cases."

Deeper insights:

These findings come as CFOs face increasing pressure to justify investments in AI and other technologies, while teams are still building the data foundations, skills, and governance structures needed to support these investments.

The report shows that 71% of CFOs say traditional metrics are insufficient to evaluate projects that combine people and technology, highlighting a growing misalignment between how organizations create value and how they measure it.

The biggest challenge is that the return on investment for emerging technologies is often difficult to clearly define or justify in advance; the second key issue is that standard financial frameworks struggle to capture future, indirect, or intangible benefits, such as improved decision-making, enhanced forecasting accuracy, and increased operational agility.

EY notes that qualitative metrics tied to business outcomes may help finance leaders better assess and articulate the value of AI and other technology investments. This includes evaluating how AI improves pricing decisions, strengthens supply chain performance, or frees up finance team capacity to focus on higher-value activities.

However, many CFOs say they do not yet have the capabilities to develop these approaches. Nearly half of respondents (47%) say their teams lack the ability to effectively measure the value created by initiatives involving emerging technologies, new roles, and new ways of working.

Beyond the ROI challenge, these findings also reveal broader gaps in AI readiness.

Only 5% of respondents describe their finance team's AI maturity as "leading," meaning technology is fully integrated into operations and actively drives pricing, resource allocation, and growth decisions. Another 16% classify themselves as "advanced," possessing strong data and data analytics capabilities and being ready to use AI for decision-making.

Most CFOs fall in the middle tiers. About 27% describe their capabilities as "functional," meaning they have the data, tools, and people to apply AI but still have work to do in optimizing its use; 30% are in the "developing" stage, with early foundations in place but significant gaps remaining; another 15% say they are still at an "early" level, and 8% report limited ability to create value with AI.

AI readiness varies by company size. Finance teams at larger enterprises are significantly more likely to be AI-ready: among companies with revenue exceeding $10 billion, 25% of respondents describe their capabilities as "advanced" and 10% as "leading," while at smaller companies below that threshold, these figures are only 12% and 2%, respectively.

EY says CFOs can improve AI readiness by prioritizing data quality, governance, and cross-functional integration, thereby reducing persistent investment barriers.

The firm also advises CFOs to move from experimentation to execution, focusing on a small number of high-value use cases that can be scaled across the enterprise and produce measurable outcomes.

Finance leaders are also advised to adopt a growth-oriented approach to AI—rather than a defensive or cost-focused one—applying the technology to areas such as market expansion and pricing strategies to create competitive advantage.

The report states: "Most CFOs prioritize defensive use cases, such as fraud detection and risk assessment, while fewer than half of CFOs apply AI to growth areas like forecasting or pricing."