Storage Titans Outpace GPU Giants: Why WD and Seagate Are Leading the AI Expansion Wave

A striking shift has emerged in AI infrastructure winners. While traditional GPU leaders lagged, storage giants dominated short-term market performance. Western Digital's stock surged 173% in 2024, while Seagate Technology reported gains exceeding 200% in 2025, both fueled by booming demand for high-capacity data storage behind AI and cloud applications. This outperformance contrasts sharply with Nvidia's 30% gain YTD 2025 and AMD's 45% rise, despite Nvidia still posting massive $44 billion quarterly revenue. Analysts note Western Digital trades at a notable 26.9% discount to its calculated intrinsic value, while its 22.2x P/E ratio sits below peers, suggesting potential undervaluation in the storage sector.

The performance gap stems from differing demand drivers and supply dynamics. AI's explosive data generation created urgent need for storage capacity, particularly for high-density solutions like Seagate's HAMR technology, which secured multi-year purchase agreements extending through 2027. Seagate projects its AI-related storage revenue will reach 50% of total exabytes by mid-2026, potentially outpacing Western Digital in technology adoption. Meanwhile, Nvidia and AMD faced distinct headwinds; AMD benefited from diversified product lines and lower China exposure, while Nvidia absorbed a $4.5 billion inventory charge due to regulatory export controls impacting its China shipments.

Despite the storage surge, GPU leaders maintain structural advantages. Nvidia's massive scale and dominant market position in AI chips could allow it to regain momentum later in 2025, especially if demand for compute power accelerates beyond storage needs. Analysts warn storage gains may face pressure if 2025 AI capital spending slows, though current demand trends remain robust. The divergence highlights how AI infrastructure investment is spreading beyond chips to include critical storage layers, though GPU performance leaders retain substantial long-term momentum.

The Storage Bottleneck in the AI Boom

The massive AI infrastructure buildout is heating up, but a critical pinch point is emerging: storage. While GPUs grab most headlines as the engines of AI, the sheer volume of data these systems consume and generate is exposing a fundamental constraint. The entire 2024 data center infrastructure market hit $290 billion according to IoT Analytics, yet storage itself only represents about 6.5% of IT infrastructure spending – roughly $14.7 billion. This seemingly small slice, however, is becoming crucial as AI workloads explode.

AI's voracious appetite for data is fundamentally changing data center demands. While GPU investments dominate headlines for their computational power, the data storage layer struggles to keep pace. Training large language models and processing massive datasets requires not just compute, but lightning-fast access to petabytes upon petabytes of information. This creates immense pressure on existing storage architectures, which weren't designed for the constant, high-volume read/write cycles of AI training and inference.

Looking ahead, the imbalance between compute and storage needs will only widen. Projections indicate 70% of future data center capacity will be dedicated specifically to advanced AI workloads. This shift underscores how storage isn't just an add-on; it's becoming the scaling bottleneck for the entire AI ecosystem. Companies specializing in high-density, high-performance storage solutions are positioned to benefit significantly from this infrastructure shift.

Western Digital and Seagate, traditional leaders in data storage hardware, are poised to capture substantial value from this AI-driven surge. The increasing demand for AI-optimized storage directly aligns with their core expertise and product portfolios. As hyperscalers and cloud providers race to deploy more AI capacity, their need for robust storage solutions will grow in tandem.

However, the rapid expansion isn't without friction. The intense demand for AI infrastructure is straining global supply chains, particularly for components critical to both storage and compute. This strain is contributing to rising costs and potential delays in deploying new capacity. Furthermore, the escalating power requirements for these dense AI clusters add another layer of complexity and expense, potentially slowing the pace of storage infrastructure upgrades needed to match compute growth. Investors see strong potential, but must remain mindful of these near-term execution and cost challenges.

Financial Momentum and Market Positioning

Building on the AI-driven data explosion, Q1 2026 results reveal strong financial momentum for key storage providers. Western Digital reported a 27% year-on-year revenue surge to $2.82 billion in the first quarter of fiscal 2026, with net income soaring 140% to $1.18 billion. This growth was fueled by surging demand for nearline HDDs in AI and cloud environments, reflecting broader market trends. The company outpaced Seagate by 7.2% in quarterly revenue, a widening from 6.8% previously, thanks to its focus on automation, higher-capacity drives, and HAMR technology development without new factory investments. Multi-year purchase orders from hyperscalers through 2027 have solidified Western Digital's market leadership despite Seagate's HAMR expertise.

Seagate is making rapid progress, with 50% exabyte crossover targeted for mid-2026, outpacing Western Digital in HAMR deployment and securing its position. The company's stock surged over 200% in 2025 amid AI-related revenue growth, and analysts see sustained margins and pricing power. However, risks remain if 2025 AI spending slows, which could dampen demand.

The market context shows broader growth, with data center demand projected to expand 19-27% annually through 2030, and 70% of future capacity will focus on advanced-AI workloads. This has strained supply chains, driving colocation prices up 35% since 2020 and intensifying competition. Both Western Digital and Seagate benefit from high-density, AI-optimized storage solutions, but supply constraints and rising power costs may delay capacity expansion, creating execution risks. HAMR technology offers long-term advantages by enabling higher storage densities, though scaling challenges like production delays and cost pressures require careful management.

Risks and Guardrails for Sustainable Performance

Seagate's impressive upside potential hinges critically on continued AI infrastructure spending growth. While AI data center demand is projected to surge 19-27% annually through 2030, creating massive storage needs, any slowdown in corporate or hyperscaler AI budgets directly threatens this growth engine. The company's ability to capitalize on this opportunity is currently squeezed by supply chain strains; 70% of future capacity is earmarked for advanced-AI workloads, yet infrastructure bottlenecks and soaring colocation costs (up 35% since 2020) risk delaying Seagate's own capacity expansions needed to meet demand. This creates execution risk, as scaling production to match surging demand requires overcoming complex manufacturing and component sourcing hurdles.

Even with strong analyst sentiment suggesting 45–75% stock upside according to Yahoo Finance, investors must view Seagate's valuation cautiously. The significant projected gains imply market pricing has already heavily discounted substantial future growth, leaving little margin for error. If AI spending growth decelerates or supply chain constraints prove more persistent than anticipated, the stock could rapidly re-rate downward, eroding the anticipated upside. Furthermore, Seagate faces intensifying competitive pressure in high-density storage, particularly from rivals like AMD expanding into adjacent AI infrastructure markets and Western Digital, whose own stock surged 173% in 2024 on similar demand according to Simply Wall St. Sustaining share gains against these well-resourced competitors requires not only scaling production but also maintaining technological edge and pricing power, both of which are vulnerable to market saturation or margin pressure as the AI storage market matures.