July 15, 2026, (Inside AI) — IBM issued a stark warning that the artificial intelligence boom is compressing traditional software budgets, sending its shares sharply lower in after-hours trading. The computing giant said it had "faltered" in adapting to a rapid shift in enterprise spending, as clients redirect funds from conventional software to data-center infrastructure needed for AI workloads.
The announcement marks one of the most explicit acknowledgments from a legacy technology firm that the AI revolution is reshaping the industry's financial landscape. IBM expects a significant earnings hit in the second quarter, directly tied to this spending realignment.
Chief Financial Officer James Kavanaugh told analysts on a conference call that the company was caught off guard by the velocity of the change. He noted that clients are prioritizing investments in high-performance computing and cloud capacity to train and run AI models, often at the expense of long-term software contracts.
"We faltered in keeping pace with a shift in corporate spending from software to data-center infrastructure," Kavanaugh said. The admission sent IBM's stock down more than 7% in extended trading.
The Infrastructure Grab Reshapes IT Budgets
The warning from IBM underscores a broader industry trend that has been building for months. Enterprises across sectors are racing to secure graphics processing units, networking gear, and specialized storage to support generative AI applications. This infrastructure-first mentality is leaving less room for traditional software licenses and services.
Analysts say IBM's predicament is particularly acute because its software portfolio, which includes middleware, databases, and analytics tools, is facing direct competition from AI-native alternatives. Meanwhile, its mainframe and consulting businesses are not growing fast enough to offset the software slowdown.
Data from Gartner shows that worldwide IT spending is projected to reach $5.26 trillion in 2026, with data center systems growing at 15.5%, while software growth has slowed to 8%. The gap highlights the reallocation that IBM is now grappling with.
"We are seeing a fundamental reprioritization of IT budgets," said John-David Lovelock, distinguished VP analyst at Gartner. "AI infrastructure is consuming a disproportionate share of new spending, and that comes at the expense of other categories."
A Legacy Player's AI Dilemma
IBM has been trying to pivot toward AI through its watsonx platform and consulting services, but the company's reliance on large, multiyear software deals makes it vulnerable when clients pause renewals to fund hardware purchases. The second-quarter earnings hit is expected to be in the range of $200 million to $300 million in lost software revenue.
The situation is not unique to IBM. Rival Oracle has also seen slower cloud license growth as customers experiment with open-source AI frameworks. However, IBM's heavy exposure to on-premise software and its slower transition to a cloud-native model amplify the pain.
"IBM's warning is a canary in the coal mine for legacy software vendors," said Dan Ives, managing director at Wedbush Securities. "The AI spending wave is a rising tide, but it's lifting boats that are already in the AI harbor, not those anchored in the old software dock."
Despite the setback, IBM executives stressed that they are accelerating investments in AI consulting and infrastructure services. The company recently announced a $500 million venture fund to back AI startups and plans to hire 10,000 new consultants specializing in AI deployment.
The warning comes just a week after IBM reported mixed first-quarter results, with software revenue up only 2% year-over-year. The company will report full second-quarter earnings on July 24, where it is expected to provide a revised outlook for the fiscal year.
Investors are now bracing for similar warnings from other enterprise software firms as the AI infrastructure spending cycle shows no signs of abating. The shift is forcing a reckoning across the tech industry, where the line between software and hardware is blurring faster than many incumbents can adapt.
