IT spend mounts as CIOs build out enterprise AI capacity – CIO Dive

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The analyst firm expects tech spending to reach $5.74 trillion next year, driven in part by exponential growth in server sales.
Even as enterprise enthusiasm for generative AI spiked over the last year, CIOs exercised caution. Unresolved safety concerns, data security issues and regulatory uncertainty coupled with budgetary constraints put the brakes on rapid adoption.
“We were at the peak of inflated expectations and we’ve been coming out on the other side in 2024, with lots of CIOs doing proof-of-concept work and, universally, not faring all that well,” Lovelock told CIO Dive. “Failure rates were much higher than we’d like to see.”
Nevertheless, the tech sector took a bullish attitude toward AI adoption, pouring billions upon billions into infrastructure to support model building and a proliferation of enterprise software add-ons and emerging use cases.
The sums were staggering. Microsoft reported $19 billion in capital expenditures during the three-month period ending June 30, mostly on cloud and AI, the company’s EVP and CFO Amy Hood said in July. Not to be outdone, AWS committed more than $50 billion to current and future U.S. data center buildouts in the first half of the year.
As the hyperscale building boom snowballed, Dell’Oro Group said it expected infrastructure spend to surpass $400 billion this year, a bit above the $318 billion Gartner forecasted Wednesday. The segment is expected to add another $50 billion in 2025, as enterprises add AI processing capacity, according to Gartner.
“In the next four years, the industry is going to spend more on AI-optimized servers than it spent on CPU-based servers in the last 20 years,” Lovelock said. “Not having GenAI in your product will be an extinction-level event.”
The spending spree doesn’t reflect a sunnier CIO disposition toward the technology. Executives will be lowering, not raising their expectations for generative AI, according to Lovelock. The reality is, what enterprises can accomplish with current generative AI models won’t meet today’s lofty expectations, he said.
Some larger organizations with established AI practices will invest heavily in infrastructure, but Gartner recommends most enterprises set a measured pace for adoption.
“Your vendors are going to be bringing you lots of opportunities,” Lovelock said. “Being successful is going to mean navigating through the options and finding products and services that will bring your company the best ROI.”
As generative AI features become table stakes for enterprise vendors over the next several years, Gartner expects the global IT market to add $500 billion annually and cross the $7 trillion threshold in 2028, according to the report.
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Moving too slowly can give competitors the advantage, but rapid deployment brings its own set of challenges. 
Businesses need better security, quality and flexibility from their data foundations to meet generative AI goals, a Hitachi Vantara report found.
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Moving too slowly can give competitors the advantage, but rapid deployment brings its own set of challenges. 
Businesses need better security, quality and flexibility from their data foundations to meet generative AI goals, a Hitachi Vantara report found.
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