Jan 27 - Seagate Technology said it expects third-quarter revenue and adjusted profit to top Wall Street forecasts, a result the company attributes to accelerating demand for its data storage devices as enterprises expand artificial intelligence initiatives.
Seagate provided a third-quarter revenue outlook of $2.90 billion, plus or minus $100 million. That compares with consensus estimates of $2.77 billion compiled by LSEG. For adjusted earnings, the company projected $3.40 per share, plus or minus $0.20, versus analysts' expectations of $2.96 per share.
The firm pointed to a wave of investment by technology companies into data centers and supporting infrastructure to train and operate large language models. Those models consume and generate massive datasets, and Seagate says its hard disk drives are among the hardware products used to house that information.
"As AI applications amplify the creation and economic value of data, modern data centers increasingly need storage solutions that combine performance and cost-efficiency at exabyte-scale," Seagate CEO Dave Mosley said.
The company also highlighted that industry analysts see a structural demand tailwind. Earlier this month, Morningstar analysts said they expect the hard disk drive industry to grow at a "low-teens average rate over the next several years, as prices fall but the amount of storage shipped increases."
For the second quarter, Seagate reported revenue of $2.83 billion, ahead of estimates of $2.73 billion. Adjusted earnings in the quarter were $3.11 per share, compared with expectations for $2.81 per share.
In after-hours trading the company's shares were down about 1%. The stock had climbed 6% in the week leading up to the earnings release after rising more than threefold in 2025 amid investor enthusiasm around AI infrastructure.
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Overall, Seagate's guidance and recent quarterly results reflect stronger demand for bulk storage capacity as enterprises increase spending on AI-related data infrastructure. The company is positioning its hard disk drives as a cost-effective option for data centers operating at very large scale.