Companies

IBM's AI Squeeze

7/16/2026

IBM's AI Squeeze
IBM's AI Squeeze

Tech Blue Chip in a Historic Tailspin

IBM saw its shares plunge over 25% on Tuesday, the steepest decline at least since the 1960s. This was after the American tech stalwart issued a profit warning, saying that second-quarter revenue and earnings would miss Wall Street expectations. 

Revenue is expected to reach $17.2 billion, up just 1% from a year ago and below the $17.9 billion analysts expected. Adjusted earnings of $2.93 per share also fell short of forecasts.

The weak link is IBM's infrastructure business. Software revenue continues to grow, with consulting largely steady, but sales of z17 mainframe systems, the powerful, high-margin business computers that are among IBM's oldest product lines, declined more sharply than management anticipated.

AI Spending Crowds Out Other Priorities

According to IBM, many customers redirected technology budgets late in the quarter toward servers, storage equipment, and memory chips. Companies building artificial intelligence capacity moved quickly to secure hardware that has become increasingly important and, in some cases, harder to source.

That shift weighed on demand for IBM's traditional infrastructure products and contributed to several large enterprise deals slipping beyond the quarter's end. IBM's own leadership pointed to a second cause, too: CEO Arvind Krishna told investors the company "did not adapt and move quickly enough" on some of those deals.

The Market Is Getting More Selective

Investors have rewarded almost anything connected to artificial intelligence for the past two years, but IBM's results are putting that pattern to the test. Constellation Research analyst Holger Mueller said the pullback in mainframe spending "shows the AI pull" reshaping enterprise budgets.

Companies supplying the memory chips, servers, and storage that AI systems run on continue to benefit from the spending surge. Businesses tied to older technology cycles, such as mainframes, now face growing competition for technology budgets as companies prioritize AI projects.

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