Gartner’s latest AI spending forecast projects worldwide AI expenditure to climb 49.5% in 2026, reaching $2.7 trillion, then grow another 36.2% the following year as AI usage keeps expanding.
But according to Gartner Distinguished VP Analyst John-David Lovelock, the surge isn’t coming at the expense of other IT categories. Instead, he describes a wave of “rebranding” that is quietly reshaping how companies think about every dollar they spend.
What the AI spending forecast actually shows
Gartner refreshes its spending projections four times a year, and this latest update pushes AI growth numbers well ahead of broader IT. On the infrastructure side, AI infrastructure spend is forecast to grow 51.2% this year, while AI software is expected to climb 60.2%.
A couple of categories are accelerating even faster. Spend on AI agents and assistants — which Gartner tracks separately from general software — is projected to jump 77.3%, and AI security spending is expected to nearly double.
Development platforms are also gaining momentum. Gartner raised its 2026 growth forecast for AI development platforms from 28% in its May report to 39%, crediting enterprises and software and service providers for building custom AI applications.
Then there are the models themselves. With domain-specific language models gaining traction against enterprise use cases, Gartner lifted its 2026 growth rate for generative AI models to 117%.
Rebranding, not diversion
The most counterintuitive part of the forecast is what it says about where the money comes from. Lovelock says there has been no meaningful diversion of funds from other IT areas to pay for AI.
“CIOs got some net new money for AI back in 2024, and a little in 2025,” he said, noting that “there wasn’t a diversion, and now more of their spending is about rebranding than diversion.”
In practice, that transformation shows up everywhere. Companies that once bought a plain laptop now buy one with AI chips built in. Enterprise software now ships with AI embedded. And strategy projects that used to ask “how should we grow?” increasingly open with “how might AI change our strategy?”
“In one way, it’s kind of rebranding,” Lovelock said. “Net new spending is going more towards AI, and existing spending is being transformed towards AI.”
The hyperscaler buildout
The same logic applies to the companies running the world’s data centers. Lovelock points out that the hyperscalers — AWS, Google, Microsoft, and Meta — haven’t pulled a single dollar away from their cloud businesses to fund AI.
“They’re all continuing to build out their cloud infrastructure at the same rate they were in 2022,” he said, characterizing the AI infrastructure buildout as “the largest infrastructure project humanity has ever undertaken.”
By 2030, Lovelock predicts the line between AI and everything else will have blurred entirely. “Every dollar is going to be an AI dollar in one way or another,” he said.
The semiconductor surprise
If one number surprised Lovelock, it’s semiconductors. For roughly three decades, he said, the chip market followed a steady, predictable long-term curve.
Back in 2015, Gartner projected semiconductor spending would reach about $1 trillion by 2030 — a call Lovelock says drew real pushback at the time from people who doubted the firm understood Moore’s law and chip fabrication.
“Well, turns out both myself and the people giving the criticism were wrong,” he said. With AI, chips are now projected to push $2 trillion by 2030, doubling what the firm originally expected.
The culprit, he said, is memory. AI servers need more memory and, since storage is also memory, more storage as they become more capable.
People often misread this as a memory shortage, Lovelock warned. “There is a massive over-demand towards memory, and that’s pushed these chip prices incredibly high” — a demand spike that doubled the 2030 semiconductor forecast.
What this means for you
For most consumers, these are macroeconomic figures that won’t show up on your next receipt. But if you run IT for a business, manage a budget, or simply watch the tech industry, the forecast carries a few practical takeaways.
First, AI is no longer a separate line item — it’s becoming the lens through which most IT spending is viewed. That means budgets once labeled “software” or “hardware” will increasingly read as AI, even when the underlying tools barely change.
Second, prices may stay volatile. The memory-driven semiconductor surge suggests the cost of AI-enabled hardware could keep shifting, sometimes sharply, over the next few years.
Lovelock’s closing message to CIOs is a caution against overconfidence. The next two to three years, he said, contain “at least three major transitions.”
“If you think you know what will happen with AI based on what is happening with AI, you’re wrong,” he said, noting that the technology is changing too quickly for anyone to have “assurances or certainty on what can be done and at what price point.” His advice: treat the balance between risk and reward as your “number one priority,” and expect the ground to keep moving under you.
Source: Computerworld
Over to you: Do you think AI budgets will keep growing at this pace, or is much of the ‘rebranding’ masking a slowdown in real, net-new spending?
