International Business Machines experienced a severe stock decline on Tuesday, with shares dropping 25% after the company released preliminary second-quarter results that fell short of market forecasts. The decline represented the worst trading day in the company’s history since records began tracking activity in 1968, surpassing the previous record set on October 19, 1987, when shares fell 23.7%.
The company reported adjusted earnings of $2.93 per share on revenue of $17.2 billion, both figures undershooting analyst expectations of $3.01 per share and $17.86 billion in revenue, according to FactSet data. Chief Executive Arvind Krishna attributed the shortfall to weakness in the software and infrastructure segments, explaining that clients had redirected spending toward hardware purchases including memory chips and servers during the final weeks of June.
In a letter to investors, Krishna noted that clients prioritized infrastructure purchases to secure supply-constrained materials ahead of anticipated price increases. He acknowledged that while the company had anticipated some supply chain impacts, the magnitude of the shift in capital expenditure priorities exceeded internal projections. He further stated that execution failures contributed to the miss, including delays in closing large deals and insufficient agility in adapting to changing market conditions.
The results contrasted sharply with IBM’s first-quarter performance, when software revenue grew 11% to $7.05 billion and the company delivered adjusted earnings of $1.91 per share against analyst expectations of $1.81, along with revenue of $15.92 billion versus forecasts of $15.62 billion. During a Tuesday television interview, Krishna dismissed concerns that artificial intelligence tools would disrupt IBM’s software business, referencing recent developments in AI-powered cybersecurity. The earnings miss occurred amid broader market concerns about AI’s potential impact on major software companies, while memory chip manufacturers such as Micron have benefited from increased demand related to AI infrastructure development.
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