The AI boom has created enormous attention around GPUs and high-bandwidth memory. But building AI infrastructure requires much more than powerful processors. Data must be stored, chips must be tested, and entire systems must operate reliably at scale.
That makes Seagate and Teradyne worth watching as their earnings arrive.
Seagate: The storage side of AI
AI models generate and process huge volumes of data. Training datasets, enterprise information and archived data all require storage capacity.
Seagate specialises in hard disk drives, which remain important for large-scale, cost-efficient data storage. If cloud providers continue expanding their data centres, demand for storage could benefit alongside demand for computing power.
The key question is whether stronger demand translates into better pricing and sustainable margins. Higher sales alone will not guarantee stronger profitability.
Teradyne: Testing the growing complexity of chips
Teradyne operates in semiconductor test equipment and industrial automation. As chips become more complex, testing their performance and reliability becomes increasingly important.
If AI-related semiconductor production continues expanding, testing equipment suppliers could benefit from greater manufacturing activity and more demanding testing requirements.
However, equipment orders can be uneven. Customers may delay purchases, and strong demand does not automatically mean every supplier will enjoy the same level of growth.
The bigger picture: Is the AI cycle broadening?
Recent gains in memory-related stocks have helped keep attention on the hardware supply chain. Seagate and Teradyne offer another way to assess whether investment is spreading into storage and testing.
Three signals matter in these earnings:
• Revenue growth: Are orders improving beyond a narrow group of AI components?
• Margins: Can companies turn stronger demand into better profitability?
• Forward guidance: Do management teams expect demand to continue, or are customers simply bringing orders forward?
Customer concentration is another risk. A small number of large technology companies account for significant infrastructure spending, so changes in their investment plans can affect suppliers across the industry.
The important distinction is between a temporary surge in orders and a sustained expansion of the AI hardware market.
If storage and testing companies report stronger demand alongside healthy margins and confident guidance, it would support the case that the AI investment cycle is reaching more parts of the supply chain. If revenue rises but margins weaken or future orders disappoint, the picture becomes less convincing.
AI infrastructure is an ecosystem, not just a GPU market. These earnings may help show how much of that ecosystem is benefiting from the current spending wave.
For discussion purposes only
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