How Dell Became One Of The Biggest Winners Of NVIDIA's AI Boom

The AI boom has largely been driven by NVIDIA's rise. But between an NVIDIA GPU and a functioning enterprise AI system sits an entire infrastructure layer of servers, storage, networking and systems integration.

Dell has emerged as one of the biggest beneficiaries of that layer.

In Q1FY26, Dell’s AI server revenue from the products that were shipped was about $1.88 billion. A year later, that figure reached $16.13 billion—an increase of 757% year over year, reflecting a jump of more than $14 billion in quarterly AI server revenue in just twelve months.

Dell is a household name in the tech ecosystem today, having garnered widespread popularity in personal computing since the 1990s. 

But alongside its consumer-facing business, the company spent decades building out its enterprise infrastructure and server operations, establishing itself as one of the world's largest suppliers of data centre hardware.

Much like GPUs became the engine of NVIDIA's growth in the AI era, servers and related infrastructure have emerged as Dell's biggest opportunity, placing the company at the heart of the AI buildout as demand for computing capacity continues to surge.

Servers and allied products are where Dell's biggest focus now lies in the AI infrastructure market, as revenues and its stock continue to grow. Over the last year alone, Dell's shares have surged by more than 300%, as investors increasingly view the company as a key beneficiary of the global AI infrastructure buildout.

The company remains at the forefront of packaging cutting-edge compute innovations into usable infrastructure and continues to be one of NVIDIA’s closest partners. 

One of the clearest examples of this came recently when Dell delivered and validated the world's first operational NVIDIA Vera Rubin NVL72 rack at AI cloud provider CoreWeave, becoming the first company to bring NVIDIA's next-generation AI architecture into a production-ready deployment. 

The company offers a spectrum of infrastructure. At one end are its PowerEdge AI servers, which combine CPUs and GPUs to power large-scale AI training and inference workloads. It also offers the Dell AI Factory with NVIDIA, which bundles compute, storage, networking, software and services into a ready-to-deploy enterprise AI stack. 

For customers with more specific requirements, Dell also develops custom infrastructure tailored to individual workloads. 

More recently, it unveiled PowerRack, a pre-integrated rack-scale system that can be deployed and running AI workloads in as little as 6.5 hours, significantly reducing the time and complexity involved in bringing new AI infrastructure online.

Dell’s Lead Over Supermicro And HPE

While competitors like Supermicro remain neck-and-neck with Dell in overall, traditional global server shipments, the high-margin AI infrastructure sector is a different story entirely. 

According to reports citing estimates from Technology Business Research (TBR), Dell commands approximately 46.7% of the specifically AI-optimised OEM server market, giving it a lead that is nearly double that of its closest competitor, Supermicro, at 25.0%

Other competitors, such as Hewlett Packard Enterprise (11.7%) and Lenovo (1.7%), remain significantly behind.

To understand Dell’s scale, one would need to compare its AI division directly to the total operations of its competitors. 

In the most recent quarter, Supermicro generated $10.24 billion across its business, including traditional servers, storage systems, and edge infrastructure. Dell’s AI-specific server revenue alone outpaces Supermicro's total global operation by nearly $6 billion.

Dell’s lead has also coincided with turbulence at Supermicro, as earlier this year, U.S. prosecutors charged three individuals associated with the company, including its co-founder, in an alleged $2.5 billion export-control scheme involving AI servers destined for China. 

While Supermicro itself was not charged, the episode has added a layer of uncertainty at a time when enterprise customers are making long-term infrastructure commitments. 

The contrast with Hewlett Packard Enterprise (HPE) is just as stark. While HPE remains a formidable enterprise player with over $10.7 billion in total quarterly revenue, it has increasingly pivoted toward networking—cemented by its $14 billion acquisition of Juniper Networks. HPE is effectively betting its AI future on the networking fabric that connects data centres.

But in the trenches of pure compute, the gap is massive. HPE reported $5.5 billion for its entire server division, a figure that includes both traditional and AI hardware. 

Dell’s AI-specific server revenue alone ($16.13 billion) dwarfs HPE’s total compute footprint by nearly 3x. Furthermore, even if one removes AI from the equation, Dell’s traditional, non-AI server business ($8.5 billion) still out-earns HPE’s entire combined server division.

Sustaining that kind of lead requires a set of advantages that competitors have struggled to replicate.

But Why is Dell Winning? 

“Once you’ve found power and compute, the next big constraint is how quickly you can get your GPUs and the equipment running,” says Arunkumar Narayanan, senior vice president of server and network products at Dell, in an interaction with AIM. “Dell can solve this better than anybody,” he says. 

The time to first token, often viewed as the moment infrastructure begins generating real value, is where Narayanan believes Dell stands apart from the competition. 

Underpinning this strategy is Dell's attempt to own more of the infrastructure stack surrounding the GPU. The company has spent the last year expanding the Dell AI Factory with NVIDIA, rapidly incorporating new software releases while also adding support for ecosystems from Google, Hugging Face and OpenAI. 

Alongside this, Dell has continued to invest in its own software, including its ObjectScale storage platform, which the company says can improve time-to-first-token by up to 19 times. 

“We’re really good at not just on the day zero of getting GPUs up and running—we’re also good at day one and day two—making sure GPUs are optimised for performance and reliability at scale,” says Narayanan. 

Narayanan also points out a historical advantage that Dell has had over the decades. 

The Supply Chain Strength

“The kind of untenable competitive advantage we have had in the supply chain for the last twenty-five years helps us a lot,” says Narayanan, adding that the company’s core business model is built around supply chain innovations. 

This goes back to reports from the early 2000s where Dell pioneered the build to order model and held an average of fewer than four days worth of inventory, down from 11 days in 1998, owing to numerous supply chain innovations and optimisations. 

That advantage appears to extend into the AI era. In a recent Reuters report, analysts at S&P Global Visible Alpha cited Dell's scale, supplier relationships and ability to prioritise demand during periods of component shortages as factors helping the company gain market share in the AI infrastructure market.

Dell's latest quarter offers perhaps the clearest illustration of that advantage. The company booked $24.4 billion in AI orders and ended the period with a record $51.3 billion AI backlog, highlighting both the scale of current demand and the volume of future deployments already committed to its infrastructure.

According to a CRN report, several partners described supply-chain management as one of Dell's ‘superpowers’, pointing to more consistent pricing and better product availability than rival vendors. 

One partner, Ahead, reported a 63% year-on-year increase in Dell server sales and attributed part of that growth to Dell's ability to deliver systems reliably amid surging demand.

Another partner, SNS Networks, a Malaysia-based sovereign AI infrastructure company, reflects a similar view. 

Kelvin Pah, the co-founder, tells AIM one reason his company chose to work with Dell over the competition was the breadth of its infrastructure portfolio.

“Under one vendor, you can get everything,” he says, referring to the combination of compute, storage and networking available through Dell's ecosystem.

Pah argues that the decision was influenced by more than the technology itself. “Besides the whole ecosystem, there are also the go-to-market advantages,” he says. 

He also describes Dell as being “very channel-centric today”, pointing to the company's long-standing relationships with partners as a factor in SNS’s decision to build on Dell infrastructure. 

He also credits Dell for the support the company received pre- and post-deployment of the infrastructure, which Narayanan suggests is a core factor in the company’s growth. 

Focus and Forward Deployment 

“We built out a forward deployment engineering capability two and a half years ago,” says Narayanan, suggesting how Dell bet early on the forward-deployed engineering model before it became popular today. 

Narayanan adds that a deep customer touch point, helping them evaluate solutions, especially in terms of not investing in overkill infrastructure, is where Dell has built a specialisation. 

While the company has aggressively expanded its AI infrastructure business, Dell has largely remained focused on its core strengths: servers, storage, networking and systems integration. 

Rather than pursuing custom AI chips, foundation models, or large-scale data-centre development projects, the company has focused on packaging technologies developed by partners such as NVIDIA into enterprise-ready infrastructure. 

Focus is increasingly proving to be an underrated advantage in the AI era. Several technology companies have been tempted to expand beyond their traditional strengths, often with mixed results. 

“The focus of Dell is always to be the essential infrastructure company of the world,” says Narayanan. “Be it NVIDIA, Intel, AMD, Broadcom, or Marvell—our goal is to work with our partners, and not replace them.”