AI In The Storage Industry—an Interview With Seagate Technology's Chief Commercial Officer B.S. Teh

B.S. Teh is Seagate Technology's Chief Commercial Officer, responsible for the company's global commercial strategy development and operation (which encompasses all business, sales, and marketing). He is also responsible for product line management across the portfolio of storage devices and systems, with a focus on driving business, market development, and access across key market and customer segments in cloud, edge and consumer markets.

As AI continues to influence the tech ecosystem, B.S. sat down with Douglas Tsang, one of AlixPartners' Silicon Valley leaders, to discuss how AI has brought storage back to the center of enterprise infrastructure and the industry's outlook for 2026.

Setting the stage: The last few years have been transformative—AI and cloud seem to have brought storage right back to the center of enterprise infrastructure. From your vantage point, what really triggered this resurgence in demand?

AI hasn't just changed content creation—it's fundamentally changed how organizations value their data. More than ever, companies see all types of data as a potentially critical asset for fueling growth. AI is projected to support the generation of 394 zettabytes by 2028—400 times more than in 2005.

Quite simply, once data has value, it must be protected and stored. AI requires speed, accessibility, and scalability, and every AI prompt involves retrieval, revision, and storage. AI is fundamentally redefining how organizations generate, organize, and value their data because of this simple truth: AI doesn't exist without data and data doesn't exist without storage. If you don't have high-capacity, performance data storage at the core of your foundation, you can't compete in the era of AI.

Beyond AI and cloud: Most of the demand story has been AI-driven, but are you seeing other emerging forces—maybe around edge, 5G, or sovereign data—starting to shape growth in interesting ways?
Yes—AI may be the headline, but it's not the whole demand story. As companies place higher value on their data as a critical asset to fuel future growth, hybrid cloud is growing for enterprises alongside hyperscaler growth.

We're seeing a shift where data is living closer to where insight, value, and innovation are created. That's true in hyperscale cloud, and it's increasingly true at the edges of networks and across sovereign environments.

As innovation becomes more distributed—across regions, industries, and jurisdictions—cloud providers and emerging clouds are prioritizing data sovereignty to protect the long-term value of end-user insight. Put simply: As data both proliferates and accumulates, we see momentum not just in hyperscale AI factories, but in sovereign clouds, regional availability zones, and edge-adjacent infrastructure.

Moving beyond capacity: Storage used to be all about TBs and price per GB. Now we're hearing more about "intelligent storage." How does Seagate see its role evolving toward more software-driven, automated, or analytics-enabled value?

Storage will always be about scale—not capacity for its own sake, but for what it enables: democratized innovation, from individual creators to global enterprises. If innovation is going to compound, the foundation must scale reliably and economically. We think that means shifting the focus to increasing the number of exabytes per hard drive vs. increasing the number of hard drives. Our new heat-assisted magnetic recording technology (HAMR) is engineered to more than double the storage capacity we're delivering today. It's why our focus is to continue our evolution of the HAMR technology—pushing capability far beyond what it is today.

The storage stack mix: When you look across the stack—hot vs. cold HDDs, SSDs, high-bandwidth memory (HBMs), and maybe even compute express link (CXL)-based designs—how do you see demand and margin trends shaping up?

When you look across the stack today, there's broad alignment on where the industry is headed. Scaled architectures are designed around access patterns over time, with data moving dynamically across complementary layers to support long‑term growth. As those systems move from pilot to production, the focus shifts from proving performance to sustaining massive data footprints reliably and economically.

Innovation hotspots: There's so much happening in this space. Where do you personally see the most exciting innovation: materials, firmware optimization, or architectural rethinking for AI workloads?

AI is not only disrupting the software industry, it's forging innovation in the hardware sector, too. Hardware is central to the AI story, and AI cannot replace hardware. We're seeing innovation across the ecosystem, in materials sciences and how materials intersect with AI in R&D and manufacturing. All of these innovations have implications for supply chain management and operations.

At the core of the hardware disruption cycle is a dynamic where AI is reshaping data access patterns, scale requirements, and data flows, and that's driving meaningful architectural rethinking across the hardware stack.

Seagate's own focus: If we look internally at Seagate, where are you doubling down on innovation—manufacturing, supply chain resilience, commercial models, or R&D? What's driving those changes?

We're delivering on increased data valuation and storage demand with a proven strategy for increasing storage exabyte capacities per hard drive.

Today, the digital economy operates on up-to-30TB drives in the data center, and we're on track to introduce 100 TB hard drives by 2033. To do this, we're doubling down on AI-driven manufacturing innovations, infusing predictability into our business model and supply chain operations to inform forecasting models that align with the innovation demands of our biggest, trail-blazing customers.

From an R&D perspective, we're looking 10+ years down the road at pioneering new thinking in materials sciences, and new atomic and nanophotonic engineering breakthroughs to take us beyond 100TB drives.

Disruptions ahead: Given how intertwined storage is with AI infrastructure, what kinds of disruptions or inflection points do you think we might see—and on what horizon?

We're now seeing speculation that AI is the new tech bubble, driven largely by financial markets that want immediate and predictable returns, understandably. Like the big tech trends that we've seen transform our world—adoption of the internet, PCs, cloud computing, and big data—AI innovation and adoption is less of a bubble and more of a staircase. With AI, we're experiencing bursts of innovation that take us to the next step, where we plateau and the innovation cycle begins again.

Each step up in AI innovation will require a breakthrough that sits on the backbone of high-capacity storage, engineered to be an AI workhorse: durable, reliable, scalable, dynamic. Each plateau of the staircase is a kind of inflection point with an unknown duration.

Big questions for the next few years: Every industry has its open questions. What are the ones that keep you up at night — the things everyone's trying to figure out in storage but haven't yet cracked?

When I look ahead, I think one of the most important and still underdiscussed questions is how the industry continues to scale digital innovation responsibly over the long term.

Every sector is becoming more data‑driven at the same time—AI, science, healthcare, climate modeling, national infrastructure — and the challenge isn't whether demand grows, it's how we design systems to sustain that growth. That's not something any one technology or company can solve in isolation.

What's encouraging is that the answer is increasingly architectural and collaborative. We're seeing cloud providers, semiconductor companies, system designers, and storage vendors working together to rethink efficiency at the system level: higher density, better utilization, longer lifecycles, smarter data placement, and architectures that avoid constant replacement.

Sustainability, in that sense, isn't a tradeoff against progress—it's a precondition for it. If we want innovation to reach more people, in more places, for longer periods of time, the infrastructure underneath it must become more efficient per unit of insight delivered, not just more powerful.

This is an industry moment. The most meaningful breakthroughs won't come from any single layer, but from ecosystems aligning around designs that scale economically, operate predictably, and endure.

The unexpected: If you had to make one bold prediction—something that might surprise the market—what would that be?

As AI becomes more and more ingrained in society and culture, at work and in our personal lives, it will actually create more opportunities for innovation, for creativity and job development than it will eliminate. Every disruptive innovation has eliminated some jobs and functions but ultimately spurs new opportunities for human purpose. I think this phase will take about a decade.

Closing reflection: Finally, when you zoom out, what's the one story about the storage industry's future that you think deserves more attention but isn't being talked about enough?

One of the most under‑discussed shifts in our industry is that demand is no longer shaped just by how much data we create, but by how we interact with the world. As we move beyond keyboards and text to glasses, sensors, video, and voice, data is generated more continuously, retained longer, and used in new ways. And with that shift comes the recognition that every byte has value to someone, somewhere. It is worthy of being protected and stored. The promise of stored data is its ability to carry the world's memory forward, economically and at scale, as the way we see, hear, and create continues to expand. That's a pretty exhilarating vision of the future to me.

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