Only 13% of CIOs Say Their Enterprise Has Realized Significant or Transformational Value from AI: Gartner

• 23 Oct 2026
• TM Team
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Only 13% of CIOs reported their enterprise has realized significant or transformational value from AI so far according to Gartner, Inc., a business and technology insights company. While AI use cases have accelerated over the past two years, the likelihood of use case success remains one-in-five.

Alicia Mullery, VP Analyst at Gartner, said, “Volume is not value. AI is creating a reckoning for organizations that lack fundamental disciplines, such as defining use-case value ahead of time and establishing criteria for when to walk away.”

The Gartner 2027 CIO and Technology Executive Agenda survey of 2,002 CIOs and technology executives from May to July 2026 found that vanguards, defined as CIOs who are delivering better performance on business outcomes while also reporting high CEO-perceived AI value, are more likely to establish stopping rules at two points in the lifecycle: pilots and production. Defining these guidelines becomes essential as organizations rapidly transition from initial experimentation to active deployment across GenAI, traditional AI and AI agents.

Organizations with guidelines for determining when an AI pilot should not move to production are 2.3 times more likely to be vanguards, while those with guidelines for abandoning low-value AI initiatives already in production are 2.6 times more likely to be vanguards. However, only 31% and 17% of CIOs, respectively, reported having these practices in place.

“Establishing and adhering to these criteria is a team sport,” said Mullery. “CIOs need business partners who are willing and ready to walk away from low value investments.”

CIOs Must Be Responsible for AI Economic Stewardship

Funding for AI is increasing, and 58% of CIOs said they have increased pressure to deliver cost improvement from AI. At the same time, 51% of CIOs expected AI to increase the total cost of ownership of technology solutions (see Figure 1). CIOs need to help their organizations govern AI economics across the full lifecycle, not simply approve an initial technology purchase.