The artificial intelligence boom continues to change not only the semiconductor and cloud computing markets, but also infrastructure segments that until recently were considered relatively calm. The market reaction to Seagate’s statements offered further confirmation of this trend. The storage manufacturer has effectively acknowledged that global demand for data storage is already beyond the industry’s capacity, while building new factories is not viewed as the optimal solution.
It was the comments of Seagate CEO Dave Mosley that triggered a sharp decline not only in Seagate’s own shares, but also in the shares of several memory and storage manufacturers. Seagate shares fell by almost 7%, Samsung Electronics and SK hynix dropped more than 5%, and Nanya Technology lost almost 10%. Investors reacted negatively to the management’s statement that the company does not plan to actively expand production facilities, despite the persisting shortage. Additional pressure on the broader market stemmed from macroeconomic factors, such as an increase in Treasury yields due to surging oil prices and the ongoing U.S.-Iran conflict.
At the same time, Seagate’s approach seems quite pragmatic. The company believes that building new factories is too capital intensive and takes too long, while the AI market remains cyclical and potentially prone to overheating. Rather than pursuing large-scale production expansion, Seagate is relying on improving data storage density and developing HAMR technologies that allow it to expand storage capacity without proportionally increasing the number of production lines.
This strategy reflects a broader shift across the AI industry. The largest market participants are increasingly trying to optimize infrastructure efficiency, rather than simply expand capacity endlessly. However, this is where the main paradox of the current cycle becomes apparent. Demand for computing and data storage is growing so fast that even cautious rhetoric of suppliers is perceived by the market as a potential threat to the entire supply chain.
Seagate itself confirmed the scale of the problem. The company admitted that it already understands customer needs for about five quarters ahead, but cannot fully meet this demand. Moreover, orders from cloud providers for HDD have been allocated until the end of 2027, and negotiations on supplies for 2028 have already begun. This is an extremely rare situation for the storage market, which has historically been characterized by strong cyclicality and regular phases of overproduction.
The company’s financial results demonstrate how much the infrastructure AI boom has changed the economics of the data storage segment. Seagate’s revenue for the quarter increased by 44% to $3.11 billion, and the server sector — primarily related to data centers — now accounts for 80% of the company’s business. Revenue in the data center segment increased by 55%, and storage shipments in capacity terms reached 199 exabytes.
The growth in profitability is particularly significant. Seagate’s gross margin increased to a record 47%, operating margin rose to 37.5%, and free cash flow approached $1 billion. For a company that was considered a representative of a mature and slow-growing market a few years ago, this effectively marks its transformation into one of the key infrastructure beneficiaries of the AI cycle. A few days after the initial decline, the company had already appeared among the top stock gainers.
At the same time, demand extends not only to SSDs and expensive accelerated storage, but also to classic hard drives. With SSDs in short supply and AI models requiring ever more storage, hyperscalers and cloud providers are increasingly purchasing HDDs for archiving, analytics, and less speed-sensitive workloads. Generative AI infrastructure requires huge amounts of data to train models, and therefore even traditional HDDs have once again proved to be a strategically important asset.
This is already reflected in prices. Since last fall, the cost of hard drives has increased by about 46%, while NAND memory prices have risen severalfold in some segments. As a result, drive manufacturers have begun moving customers to long-term contracts of up to five years, which was previously more of an exception in this market.
In fact, the data storage market is beginning to resemble the energy or raw materials market, where long-term obligations are becoming an insurance tool against infrastructure shortages. AI is gradually turning computing power, memory, and data storage into strategic resources with their own supply and demand economy.
Against this backdrop, Seagate’s position is particularly interesting, as the company is avoiding participation in a new capital expenditure race on a scale familiar to the market. It is clearly afraid of a repeat of previous overproduction cycles, when, after a sharp increase in demand, the industry faced excess capacity and a collapse in margins. However, the problem is that the current AI cycle may turn out to be much longer and more structural than previous technological waves.
That is why the reaction of investors turned out to be so painful. The market already perceives infrastructure manufacturers as direct participants in the AI economy, and any signals about potential supply constraints as a risk factor for the entire ecosystem. Especially in a situation where the largest technology companies continue to invest hundreds of billions of dollars in data centers, computing clusters, and model training.