CFOs lag in AI readiness as ROI pressures rise: EY

The findings come as CFOs face growing pressure to justify AI and other technology investments, while teams are still building the data foundations, skills and governance needed to support them.

Seventy-one percent of CFOs say traditional metrics are not sufficient to evaluate initiatives that combine people and technology, highlighting a growing mismatch between how organizations create value and how it is measured, according to the EY report.

The biggest challenge is that ROI from emerging technologies is often difficult to define or prove upfront, while a second key issue is that standard financial frameworks struggle to capture future, indirect or intangible benefits such as improved decision-making, forecasting accuracy and operational agility.

Qualitative measures tied to business outcomes could help finance leaders better assess and articulate the value of AI and other technology investments, EY said. This includes assessing how AI can improve pricing decisions, strengthen supply chain performance, or free up finance teams to focus on higher-value activities.

However, many CFOs say they are not yet equipped to develop these approaches. Almost half (47%) of those surveyed say their teams lack the ability to effectively measure value created by initiatives involving emerging technologies, new roles and new ways of working.

Beyond ROI challenges, the findings point to broader gaps in AI readiness.

Just 5% of respondents described their finance team’s AI maturity as “leading,” where the technology is fully integrated into their operations and actively driving pricing, resource allocation and growth decisions. Sixteen percent classified themselves as “advanced,” with strong data and analytics capabilities and the readiness to use AI in decision-making.

Most CFOs were concentrated in the middle tiers. Some 27% described their capabilities as “functional,” meaning they have the data, tools and personnel to apply AI but still have work to do to optimize its use, while 30% were “developing,” with early foundations in place but significant gaps remaining. A further 15% said they were still at an “early-stage” level, and 8% reported having limited ability to use AI for value creation.

AI readiness varied by company size. Finance teams at larger businesses were significantly more likely to be AI-ready, with 25% of respondents at companies generating more than $10 billion in revenue describing their capabilities as “advanced” and 10% as “leading,” compared with just 12% and 2% respectively among smaller firms below that threshold.

EY said CFOs can improve AI readiness by prioritizing data quality, governance and cross-functional integration to reduce ongoing barriers to investment.

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

Finance leaders were also advised to adopt a growth-led approach to AI — rather than a defensive or cost-focused one — by applying the technology to areas such as market expansion and pricing strategy where it can create competitive advantage.

“Most CFOs prioritize defensive use cases such as fraud detection and risk assessment, with fewer than half applying AI to growth areas such as forecasting or pricing,” the report said.