Setting AI ambition, strengthening AI foundations and empowering people for AI transformation are the three approaches organizations can use to derive value from artificial intelligence, according to Gartner.
The approaches were highlighted by analysts Adam Ronthal and Georgia O’Callaghan during the opening keynote at the Gartner Data & Analytics Summit recently in Orlando, US.
The insights follow a Gartner survey of 353 data and analytics (D&A) and AI leaders conducted between November and December 2025. The survey found that only one in five respondents is concerned that uncertain costs will limit the value they derive from AI. As a result, only 44 percent of organisations have adopted financial guardrails or AI FinOps practices.
According to Ronthal, AI deployment has expanded significantly in the past year.
“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,” he said. “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.”
O’Callaghan noted that organizations often measure value through return on investment but said leaders should view ROI beyond financial metrics.
“Getting to value is often measured using ROI, which D&A leaders need to think of as more than just a financial measure,” she said. “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.”
Setting AI ambition
The first approach focuses on defining a clear level of AI ambition within organisations.
Gartner said increased acceleration and uncertainty around AI, combined with concerns around trust and control, require organizations to continuously learn and adapt.
“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, Gartner recommends that leaders rethink the impact of AI on data and analytics, establish a shared vision, determine their role in AI leadership and manage unpredictable or hidden AI costs early.
Strengthening AI foundations
The second approach focuses on building strong foundations for AI initiatives.
Without these foundations, AI may remain an expensive experiment for many organisations, according to Gartner.
“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 stronger foundations and reduce risk, Gartner recommends aligning foundational initiatives with AI ambition levels, making governance a value accelerator and creating a single unified context layer.
Empowering people for AI transformation
The third approach focuses on preparing employees for AI-driven transformation.
While organizations may change rapidly, Gartner noted that people have a limited capacity to absorb change, and human readiness often lags behind technological 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.”
Gartner added that this approach can increase employee engagement and productivity while helping organisations adapt to change.
To support AI transformation, Gartner recommends budgeting for change management, prioritizing mindset and skillset development over tools, addressing employee concerns through skills development roadmaps and piloting fusion teams that combine human expertise with artificial intelligence.
