ots of companies are still racing to embrace as much AI as possible, but new data shows how much enterprises are struggling to show measurable business outcomes from AI.

This week at Gartner IT Symposium/Xpo, the company's annual flagship event, the analyst house revealed contrarian data on AI investment from surveys of CEOs and CIOs and other Gartner research:

• 81% of CIOs are increasing AI spend
• 44% of CEOs struggle to demonstrate AI-driven financial returns to stakeholders
• 13% of CIOs say their organizations have realized significant or transformational value from AI
• 11% of CFOs see clear returns from AI
• 4% of CIOs have plans in place to redesign roles for a human-agent workforce
• 58% of CIOs face increased pressure to deliver cost improvements from AI

These numbers highlight the fact that AI is rapidly shifting from experimental mode into a place where it has to show accountability for impact and ROI. Leaders are going to have to be able to articulate not just what AI can accomplish but how those benefits can justify the costs for both deployment and on-going operations.

"Volume is not value," said Alicia Mullery, Gartner analyst. "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."

Gartner analyst David Furlonger further extrapolated, "The AI value problem will not be solved by simply adding more AI to existing ways of working."

In other words, if companies rely on AI to simply automate individual tasks then the economic upside is likely to remain limited and the pressure on executives will continue to increase. Instead, they're going to have to think bigger. Enterprises will need to do the harder work of redesigning workflows, reimagining decision-making processes, and rethinking organizational structures.

That's a lot to ask and it takes investment and organizational buy-in, but that's what will be required to drive the kind of transformations that match the rhetoric and the level of investment we're seeing around AI. It also requires bringing AI down from the clouds and thinking of it like all of the other technology shifts and changes from the past. Even if it's a more powerful and capable technology than what's come before, it still needs to earn its stripes in the same way and live by the same economic laws.

"AI is an enabler of outcomes, not an outcome itself," said Gartner analyst Joseph Provenza

Our Deeper View

The bottom line is that AI spending and adoption continue to accelerate but business outcomes tied to AI are coming under intense pressure to justify the enormous investments that have been made in recent years. The bigger opportunity has to come from enterprises changing how they operate rather than simply making existing operations more efficient. That nets out to the fact that winning with AI as an organization depends far less on deploying the latest models and AI tools than it does on organizational discipline, workforce redesign, and rethinking how the organization creates value. Again, that's the kind of hard work that the best organizations will have to master when it comes to implementing AI.