Gartner Says CFOs Need to Rethink the ROI of AI Investments

CFOs are misjudging AI investments by treating them as a single ROI problem rather than as a portfolio of very different bets, according to Gartner, Inc., a business and technology insights company.

“AI does not follow one cost curve, and it does not produce one uniform type of value,” said Twisha Sharma, Senior Principal, Research in the Gartner Finance practice. “CFOs need to stop looking for a single ROI formula and instead build a balanced portfolio that includes productivity use cases, targeted process improvements, and selective transformational bets.”

Speaking at the Gartner Finance Symposium/Xpo 2026 in Sydney today, Sharma told attendees to think about AI projects like different types of travel that have distinct purposes and economic identities. An AI portfolio should contain projects with routine use cases that automate repetitive tasks, those with more advanced use cases that improve analysis and decision making, and larger transformational use cases aimed at innovation or competitive disruption (see Figure 1).

“The economics of AI differ sharply from one use case to another, making it difficult for a standard value approach to capture the full picture, especially as the cost difference between various types can be significant,” said Sharma, “Each use case will have different timelines, different ambitions, different risk profiles and different ongoing costs. If finance teams don’t dissect cost models with precision, they will face budget surprises later.”

Sharma also warned that CFOs risk undervaluing AI if they focus too narrowly on immediate financial returns, such as revenue growth, cost reduction or cash flow improvement alone. Many AI initiatives create important nonfinancial value first — including better decision support, stronger business agility, wider organizational reach, innovation capacity and even a shift in finance’s role within the enterprise — long before those benefits are fully visible in the P&L.

“The value of AI is not always captured first in traditional financial metrics. In many cases, it appears earlier in better decisions, faster adaptation and stronger organizational capability. CFOs need to account for that if they want a complete picture of what AI is really delivering,” said Sharma.

The companies that get the most value from AI will not be the ones chasing a single breakthrough or forcing every initiative through the same ROI lens. They will be the ones that treat AI like a portfolio — balancing routine productivity gains, targeted process improvements and selective transformational bets, while scaling winners and cutting weak ideas early.

This press release was adapted from the session Cracking AI's Value Code: From Uncertain Cost Driver to Value Engine at the Gartner Finance Symposium/Xpo 2026 in Sydney today. Gartner clients can read more in the report Tailor AI Funding Models to Accelerate Enterprise Value and nonclients can read The CFO Report.