How Should CFOs Measure the Value of AI—When ROI Falls Short?

AI is rapidly becoming one of the largest line items in enterprise investment—but for many CFOs, it remains one of the hardest to justify. Despite hundreds of billions in global AI spending, fewer than half of AI initiatives are perceived by finance teams to deliver tangible value. The problem isn’t the technology. It’s how we measure it.

In this article, Aarif Nakhooda, CFO of CoreAI and Client Success at Keystone.ai, examines why traditional ROI frameworks break down when applied to AI—and why continuing to rely on them may be holding organizations back. Drawing on real-world experience at the intersection of finance, AI, and enterprise operations, he explores how AI creates value differently: through learning, compounding returns, and improved decision-making that resists simple attribution.

This piece challenges finance leaders to rethink how they evaluate AI investments—shifting from short-term cost justification to long-term capability building—and outlines emerging approaches CFOs are using to assess AI on its own terms.

Download the article to explore:

• Why conventional ROI fails to capture AI’s true impact
• How leading CFOs are evolving financial frameworks for AI
• What it means to treat AI as a compounding enterprise capability
• The hidden cost of delaying AI investment

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