Gartner’s survey of 2,002 CIOs and technology executives highlights gaps in AI governance, cost accountability and workforce redesign, as successful AI adoption increasingly depends on measurable business outcomes rather than deployment volume.
Only 13% of CIOs say their organisations have realised significant or transformational value from artificial intelligence (AI), according to Gartner’s 2027 CIO and Technology Executive Agenda survey. Despite the rapid expansion of AI use cases over the past two years, the likelihood of an individual use case succeeding remains just one in five.
The survey, conducted from May to July 2026 among 2,002 CIOs and technology executives, suggests that organisations achieving stronger business outcomes are more disciplined in deciding which AI initiatives to pursue, scale or abandon.
Gartner identifies these high-performing leaders as “vanguards”—CIOs who deliver better business performance while also reporting high CEO-perceived value from AI. They are more likely to establish clear stopping rules at both the pilot and production stages.
“Volume is not value. 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.” — Alicia Mullery, VP Analyst, Gartner
Organisations with guidelines for preventing unsuccessful AI pilots from progressing to production are 2.3 times more likely to be vanguards. Those with criteria for abandoning low-value AI initiatives already in production are 2.6 times more likely to belong to this group. Yet only 31% of CIOs have guidelines for stopping pilots, while just 17% have formal criteria for discontinuing underperforming production initiatives.
“Establishing and adhering to these criteria is a team sport,” said Mullery. “CIOs need business partners who are willing and ready to walk away from low value investments.”
AI Economics Demand New Governance Models
Cost management is emerging as another challenge. While AI funding is increasing, 58% of CIOs report greater pressure to deliver cost improvements through AI. At the same time, 51% expect AI to increase the total cost of ownership of technology solutions.
Gartner argues that conventional funding and governance models designed for cloud and software-as-a-service investments may not adequately address AI’s economics. Unlike many traditional technology costs, AI expenditure can vary at runtime, making lifecycle oversight, cost accountability and continuous evaluation increasingly important.
Workforce Redesign Remains a Major Gap
The survey also points to a significant gap in workforce planning. Organisations with explicit plans to redesign roles for a human-agent workforce are 2.4 times more likely to be vanguards. However, only 4% of CIOs say their organisations have such plans in place.
Rather than focusing solely on reducing headcount, Gartner sees workforce redesign as a way to expand human responsibilities as AI takes on specialised tasks. Roles may increasingly overlap, with designers taking on testing activities and testers contributing to design.
Reflecting this shift, 40% of respondents expect their IT headcount to increase in 2027, particularly in cybersecurity and data and analytics. Gartner’s findings suggest that AI may reduce the effort required for individual technology tasks while increasing overall demand for technology work.
For CIOs, the priority is therefore to connect AI investment with measurable business value, establish clear criteria for ending underperforming initiatives, govern costs across the AI lifecycle and prepare employees for evolving responsibilities. The findings position disciplined execution—not the sheer number of AI deployments—as a key differentiator in enterprise AI performance.
