February 2026
PYMNTS Data Books

CFOs Take Control of Enterprise Gen AI

Effectiveness is up and errors are down—yet CFOs are doubling their timelines to ensure they scale correctly.

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    Enterprise use of generative artificial intelligence has moved past experimentation and into daily finance operations. Using data from the February edition of The Enterprise AI Benchmark Report, “What Happens When CFOs Get Serious About Gen AI,” this PYMNTS Intelligence Data Book captures how gen AI is being adopted, governed and measured across large organizations. The findings show a clear shift from early uncertainty toward disciplined deployment, with finance leaders focusing less on whether the technology works and more on how to scale it responsibly, measure its value and manage its risks over time.

    CFO Use and Views on Gen AI

    Core Adoption

    Businesses have now embedded gen AI across core finance functions, including capital management, financial reporting and risk oversight. By December 2025, 86.7% of CFOs reported using the technology for capital management, more than double the share who did so in July. Importance ratings have climbed sharply across nearly every core finance activity, including traditionally conservative areas such as treasury, risk and compliance. This shift signals growing confidence in governance and controls, as finance leaders increasingly treat gen AI as a standard operating tool rather than an experimental technology.

    Rising Effectiveness of Gen AI

    CFOs now view gen AI as highly effective across almost all enterprise use cases. Effectiveness ratings surged into the 80% to 100% range by December, with 96.4% of CFOs saying the technology is very or extremely effective at generating new content. Tasks such as automated workflows, real-time customer responses and cybersecurity management now show overwhelming satisfaction. Neutral or dissatisfied responses have largely disappeared, reflecting growing hands-on experience and operational confidence.

    Fewer Drawbacks

    Perceived risks and drawbacks from gen AI are shrinking as experience in using the technology grows. The average number of reported drawbacks fell from 6.92 last July to 4.23 last December. Declines were consistent across industries and revenue bands, with the largest improvements coming at the biggest companies. Rather than uncovering new problems, increased use appears to be helping organizations resolve early concerns tied to governance, risk and change management.

    Operational Friction

    Day-to-day challenges in implementing gen AI are easing rapidly. Common pain points such as errors, integration issues and cost concerns declined sharply over the last six months. Errors and output issues dropped from 80% of CFOs citing them in July to 35% in December, while cost and maintenance concerns fell to just 23.3%. Remaining challenges center on talent readiness and data security, signaling a shift from technical fixes to organizational scaling.

    Gen AI Integration Timelines

    CFOs are resetting expectations for full gen AI integration. Finance leaders now expect the technology to take an average of 6.3 years to be fully embedded across the enterprise, nearly double earlier estimates. This recalibration reflects a more realistic view of the complexity involved in scaling gen AI across systems, workflows and controls. Rather than slowing adoption, longer timelines underscore a shift toward deliberate, enterprise-wide integration.

    About

    PYMNTS INTELLIGENCE

    PYMNTS Intelligence is a leading global data and analytics platform that uses proprietary data and methods to provide actionable insights on what’s now and what’s next in payments, commerce and the digital economy. Its team of data scientists includes leading economists, econometricians, survey experts, financial analysts and marketing scientists with deep experience in the application of data to the issues that define the future of the digital transformation of the global economy. This multi-lingual team has conducted original data collection and analysis in more than three dozen global markets for some of the world’s leading publicly traded and privately held firms.

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