Gartner Identifies Three Pillars for Deriving Value from AI

Only one out of every five data and analytic (D&A) or AI leaders are concerned that uncertain costs will limit AI value according to Gartner, Inc., a business and technology insights company.

A Gartner survey of 353 D&A and AI leaders from November through December 2025 found that this has led to only 44% of organizations adopting financial guardrails or AI FinOPs practices.

“Where adoption rates for AI deployment have grown from just two out of five organizations in 2024, to four out of five organizations today, D&A leaders must achieve clarity and focus on ROI to better achieve the growing AI goals and ambitions of their organizations,” said Adam Ronthal, VP Analyst at Gartner. “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.”

“Getting to value is often measured using ROI, which D&A leaders need to think of as more than just a financial measure,” said Georgia O’Callaghan, Director Analyst at Gartner. “There are three ways to approach value that will help D&A leaders steer their organizations safely and effectively through the turbulent AI value waters.”

During the opening keynote at the Gartner Data & Analytics Summit, taking place here through Wednesday, Gartner analysts discussed these three ways to derive value from AI.

Set AI Ambition

Increased acceleration and uncertainty, combined with concerns about trust and control, drive the need for continuous learning and adaptation.

“D&A leaders may be experimenting with AI and learning a lot, but that also means they risk falling behind because everyone is experimenting,” said Ronthal. “D&A leaders should set their AI-ambition to help them maximize value from the insights their data provides, together with the knowledge and intuition of their team. This provides a return on intelligence.”

To set this level of ambition, D&A leaders must radically rethink the impact of AI on D&A, set a shared vision and determine their level of AI ambition, take AI leadership, decide their role and manage the unpredictable and hidden costs of AI early.

Strengthen AI Foundations

Without strong foundations, AI will remain what it is for most organizations today; an expensive experiment.

“Expecting AI or GenAI to compensate for delayed upgrades, siloed teams and years of technical debt

is wishful thinking,” said O’Callaghan. “D&A leaders must make sure their data is AI-ready, prevent exposing the wrong data to the wrong people and avoid inaccuracies, misunderstandings and hallucinations with a well-designed context layer. This provides a return on integrity.”

To create strong AI foundations and reduce risk, D&A leaders should align their foundational initiatives with their AI ambition level, make governance a value accelerator and create a single, unified context layer.

Empower People for AI Transformation

While organizations change at a rapid pace, humans have a finite capacity to incorporate change. AI readiness grows much faster than human readiness.

“D&A leaders must make the shift from thinking about roles to focusing on skills with respect to AI,” said Ronthal. “D&A leaders will get value from their investments in developing their workforce. By focusing on skills, mindset, and behavioral change, they can unlock both individual and collective potential. This will increase employee engagement and productivity, making their organization more adaptive to change. Ultimately, this provides a return on individuals.”

To empower people for AI-driven transformation, D&A leaders must substantially budget for change management, prioritize mindset and skillset over toolset, address employee concerns with a skills-development roadmap and also pilot fusion teams of blended human and artificial intelligence.