Even as worldwide AI spending accelerates toward historic highs, many enterprises are entering a more cautious and operationally focused phase of adoption.
According to Gartner, worldwide AI spending is projected to reach $2.59 trillion in 2026, representing a 47% increase year-over-year. Yet beneath the staggering investment numbers, Gartner analysts say CIOs are shifting their focus away from sweeping AI transformation narratives and toward smaller, more operationally grounded initiatives capable of delivering measurable business value.
John-David Lovelock, Distinguished VP Analyst at Gartner, believes 2026 will mark a turning point for enterprise AI strategy.
“This is the year that we start pruning the AI garden,” Lovelock told The National CIO Review.
The AI Garden Begins to Thin
Many technology leaders are already experiencing this firsthand: after two years of aggressive experimentation, mounting boardroom pressure, and relentless AI hype, organizations are beginning to narrow their focus.
Instead of pursuing large-scale “AI transformation” initiatives, Technology leaders are increasingly embedding AI into existing workflows, platforms, and enterprise software ecosystems.
“Projects are shifting from projects about AI to projects that include AI,” Lovelock said.
“Projects are shifting from projects about AI to projects that include AI”
That shift may ultimately prove more important than the spending forecast itself.
For much of the past two years, enterprise AI conversations have centered on disruption. However, according to Lovelock, the operational reality within organizations has been far more complex.
“On the symposium stage, Distinguished VP Analyst and Gartner Fellow Daryl Plummer said that 80% of projects failed in 2025,” Lovelock said. “When four out of five fail, you start and lose a little faith.”
From “Projects About AI” to “Projects That Include AI”
As a result, many enterprises are moving more conservatively into the next phase of AI adoption.
Rather than ripping out systems or overhauling workflows entirely, organizations are increasingly leaning on AI capabilities embedded within platforms they already trust and use.
“Salesforce has Einstein. SAP has Joule. Copilot’s on our desk,” Lovelock said. “How can we use it better this year?”
This highlights broader concerns that many CIOs continue to face around governance, security, operational readiness, and perhaps most importantly, ROI.
According to Gartner’s forecast, organizations still show “limited appetite” for using AI to drive disruptive enterprise change, instead favoring tactical initiatives focused on incremental efficiency and productivity gains.
Lovelock says that caution is not necessarily a sign of failure. “It’s not wrong to be a laggard,” he said. “I’m going to wait for use cases to come out and case studies to come out to prove that I can do this, so I know how much it costs, how long it takes, and what I get.”
The ROI Problem CIOs Still Can’t Solve
That mindset reflects a growing reality inside enterprise IT organizations: many CIOs are still struggling to quantify AI’s business impact in a meaningful way.
“In our survey work, 40% of CIOs are saying, ‘I can’t point to the value that we get from AI,’” Lovelock said.
Part of the challenge, he explained, is that AI often improves areas that traditional enterprise metrics struggle to capture.
“What’s the key performance indicator that we can say has improved because of AI?” Lovelock said. “Most companies don’t have a KPI that aligns to the improvements that AI is going to bring.”
At the same time, Gartner expects AI infrastructure spending to continue climbing rapidly over the next several years. They project that AI infrastructure, including AI-optimized servers, cloud expansion, networking, and semiconductors, will account for more than 45% of the market moving forward.
“Through the next several years, the need for capacity will make AI infrastructure the largest segment of the market,” Lovelock said in Gartner’s forecast announcement.
The Rise of Embedded and Agentic AI
Lovelock believes the long-term impact of AI may ultimately reshape the way enterprises interact with software altogether.
“We’re currently spending on information technology,” he said. “We will soon be spending on intelligence technology because everything will have AI embedded in it.”
That transition is expected to accelerate further with the rise of agentic AI.
While many CIOs remain cautious about autonomous AI systems today, Lovelock believes AI agents could eventually redefine the traditional SaaS experience by removing the need for users to directly interact with enterprise applications altogether.
“The user interface changes from keyboard and mouse to, ‘I don’t need one,’” Lovelock said. “As an end user, I interact with an AI and a series of agents and they do the work within the systems on my behalf.”
The implications could be significant not only for enterprises but for software vendors themselves.
Gartner estimates that as much as 20% of spending across some enterprise software markets could eventually shift toward third-party AI agents operating independently of incumbent platforms.
“Watch Your Partners”
For Technology Leaders, however, the more immediate concern may be the growing instability of the broader AI vendor ecosystem.
Following years of explosive startup growth and venture capital investment, Lovelock expects consolidation, acquisitions, failed partnerships, and vendor shakeups to intensify throughout the next year.
“We’ve had a thousand flowers blooming,” Lovelock said. “This year is going to be very chaotic for the AI vendor landscape itself.”
His advice to enterprise technology leaders navigating the next phase of AI adoption was direct:
“Watch your partners.”
As organizations continue investing aggressively in AI, many CIOs may find that the next phase of enterprise adoption is less about chasing the newest breakthrough and more about determining which technologies, and which vendors, are actually built to last.
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