Gartner has identified three key pillars organizations must focus on to derive measurable value from artificial intelligence, cautioning that without the right strategy and foundations, AI will remain an expensive experiment for many enterprises. The guidance comes at a time when AI adoption is accelerating, but many organizations are still struggling to demonstrate clear return on investment.
According to a Gartner survey of 353 data, analytics, and AI leaders conducted between November and December 2025, AI deployment has increased significantly, growing from about two out of five organizations in 2024 to nearly four out of five today. Despite this rapid adoption, only 44% of organizations have implemented financial guardrails or AI FinOps practices, raising concerns about cost control and long-term value realization.
Gartner said the first step to achieving value is to set a clear AI ambition. Organizations must define how AI will support business outcomes instead of pursuing isolated experiments. This includes aligning AI initiatives with enterprise goals, establishing leadership accountability, and planning for unpredictable costs associated with scaling AI. A clear ambition helps organizations move toward what Gartner describes as a “return on intelligence,” where AI-driven insights directly influence decision-making and performance.
The second pillar is to strengthen AI foundations. Many organizations expect AI or generative AI to compensate for outdated systems, siloed data, and years of technical debt, which often leads to inaccurate results and low trust. Gartner recommends ensuring that data is AI-ready, applying strong governance, and creating a unified context layer so that AI systems can access reliable, secure, and well-structured information. Strong foundations help reduce risk while improving accuracy, compliance, and overall effectiveness.
The third pillar focuses on empowering people for AI transformation. Gartner noted that while technology adoption is moving fast, workforce readiness is not keeping pace. Organizations need to invest in skills development, change management, and new ways of working that combine human expertise with AI capabilities. Building teams that can effectively collaborate with AI will improve productivity, increase engagement, and help organizations adapt to continuous change.
Gartner emphasized that enterprises that align AI ambition, technical foundations, and workforce readiness will be better positioned to move beyond experimentation and achieve sustainable, business-driven value from their AI investments.