344
Productivity & Workflow355
Automation & Workflow224
Software Development251
Marketing & Growth192
AI Infrastructure & MLOps174
Writing & Content Creation203
Data & Analytics141
Design & Creative170
Photography & Imaging156
Customer Support131
Sales & Outreach125
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Operations & Admin87
IBM said it fell short on sales as customers redirected budgets to AI-related servers and storage, sending the stock down about 22% in early trading.
In short: IBM said it missed expectations because customers shifted spending toward AI-related hardware, and its shares were set to drop about 22%.
IBM issued a profit warning after reporting results that came in below what analysts expected. In early trading, IBM shares fell about 22%, which would be the company’s biggest one day drop since 1987.
IBM’s chief executive, Arvind Krishna, said the company “faltered” and did not move fast enough as customer priorities changed. He said several large deals did not close when IBM expected, which caused most of the shortfall.
The main issue was in IBM’s infrastructure business, which includes big computers and related equipment. Infrastructure revenue fell 7% in the second quarter, worse than IBM’s earlier expectation of a small decline. IBM said customers rushed to buy servers and storage (think of servers as powerful work computers that run apps, and storage as the digital warehouse for data) from other suppliers ahead of expected price increases linked to the AI boom.
IBM reported total revenue of $17.2 billion, up 1% from a year earlier, but below the $17.8 billion analysts expected. Software revenue rose 5%. Earnings per share, a common measure of profit per share of stock, fell 2% to $2.27 and also missed forecasts.
IBM has been trying to shift its image from a mainframe and hardware company to a faster growing software business, including through major acquisitions like Red Hat, HashiCorp, and Confluent. The next few quarters will show whether IBM can keep growing software while customer budgets stay focused on the physical equipment needed to run new AI systems.
Source: Financial Times