Gartner to AI-Happy CDOs: Stop Experimenting, Start Delivering

If you’re a chief data officer who’s been celebrating your org’s AI adoption numbers, Gartner has some bracing news for you: adoption isn’t value. And in 2026, value is all that matters.

At the recent Gartner Data & Analytics Summit in Orlando, analysts took the stage for an opening keynote that felt less like a conference talk and more like an intervention. The message, delivered with the calm authority of people who’ve seen every tech bubble inflate and pop: data & analytics (D&A) and AI leaders are running fast but not necessarily forward.

The numbers don’t lie and can sting

While AI deployment has exploded — jumping from two in five organizations in 2024 to four in five today — only 44% of organizations have adopted financial guardrails or AI FinOps practices. That means the majority of enterprises are sprinting into AI spend without a seatbelt.

And yet, only one in five D&A or AI leaders are actually worried about uncertain costs limiting AI value, according to a Gartner survey of 353 D&A and AI leaders conducted in November through December 2025. Optimism is admirable; fiscal recklessness is not.

“D&A leaders must realize they are responsible for delivering real value in the midst of all this AI hype and fears of an AI bubble that might burst,” said Adam Ronthal, vice president analyst at Gartner. It means the “we’re learning a lot” defense has an expiration date.

Three ways to derive value

Gartner's prescription comes in the form of three strategic imperatives for D&A leaders navigating what the analysts called “turbulent AI value waters.”

Set AI ambition. This is about more than declaring yourself an AI-first company. Ronthal explained, “D&A leaders may be experimenting with AI and learning a lot, but that also means they risk falling behind because everyone is experimenting.” The path forward requires rethinking AI’s impact on D&A, setting a shared vision, taking AI leadership, and managing unpredictable and hidden costs early. The payoff, in Gartner’s framing: a return on intelligence.

Strengthen AI foundations. This is where Gartner gets clinical. “Expecting AI or GenAI to compensate for delayed upgrades, siloed teams and years of technical debt is wishful thinking,” said Georgia O'Callaghan, director analyst at Gartner. For CDOs hoping a shiny LLM layer will paper over their data swamps, it won’t. Strong foundations mean AI-ready data, airtight governance as a value accelerator, and a single unified context layer to prevent the hallucinations and misunderstandings that end careers. The payoff: a return on integrity.

Empower people for AI transformation. The pillar most CDOs underinvest in and later regret. AI readiness, Gartner argues, grows far faster than human readiness — a mismatch that can hollow out even the best-architected AI initiative. “D&A leaders must make the shift from thinking about roles to focusing on skills,” said Ronthal. The playbook: substantially budget for change management, prioritize mindset and skillset over toolset, address employee concerns with a skills-development roadmap, and pilot fusion teams where blended units of human and artificial intelligence work in concert. The payoff: a return on individuals.

The question we can’t avoid

The era of AI as a corporate science fair project is over. Boards want ROI, CFOs want guardrails and employees want clarity. Gartner’s framework won’t do the work for you, but it does offer D&A leaders a vocabulary and a roadmap for the conversation already happening in boardrooms: what, exactly, are we getting for all this AI spend?

The organizations that answer that question with data are the ones that will still be standing when the hype clears.

Image credit: iStockphoto/Aree Sarak