Dell Bulks Up Hardware As AI Infrastructure Shifts To On-Premises
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Dell Bulks Up Hardware As AI Infrastructure Shifts To On-Premises
Jeff Burt
Jeff<br>Burt
Published<br>tue 19 May 2026 // 17:08 UTC
The first day of the Dell<br>Technologies World 2026 conference in Las Vegas this week had a faintly<br>familiar vibe to it, an echo from several years ago, before the broad adoption<br>of cloud computing had OEMs talking as much about optimization software and<br>similar tools as they did hardware.<br>But AI – particularly agentic AI and inferencing – has<br>changed the game, swinging the pendulum back to infrastructure, in the<br>datacenter and at the edge. And Dell founder and chief executive officer<br>Michael Dell let it be known that his company is ready for the moment.
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“In companies across every industry, AI is accelerating from<br>proof-of-concept into production,” Dell said during his keynote address. “It's<br>flipping the traditional buy-vs-build<br>equation. For years, the trend was off-the-shelf software and public cloud. But<br>now, AI is collapsing the cost and time to express your competitive advantage<br>through software. So guess what? There's going to be way more software<br>everywhere.”<br>This is a position Dell started to lay<br>out at last year’s show. And, editor’s note butting in here, what it<br>amounts to is an admission that for many enterprises, the cloud is too costly<br>compared to squeezing five, six, or seven years out of hardware that you buy.<br>We have been saying this as long as Amazon Web Services existed, that in the<br>fullness of time, everybody will not move everything to the cloud. Certainly<br>not legacy back office workloads.<br>This year, Dell, the man, pointed to a Dell, the company, survey<br>about AI adoption that found that 67 percent of AI workloads run outside the<br>cloud – either on premises, on devices, at the edge, or in co-location facility<br>– and 88 percent of those surveyed said they are running at least one AI<br>workload on premises. This trend is being driven by the surging use by<br>organizations of AI agents – “They have memory and credentials and access and<br>the ability to take action, and this requires a new architecture for work<br>itself,” Dell said – enterprise demand for sovereign AI, and the desire to<br>bring AI closer to where the data is being created and stored.<br>The expected sharp growth in AI infrastructure spending is backing<br>up this vision. Dell said that projections say spending could rise to $3<br>trillion to $4 trillion by 2030, though others show an even broader range, from<br>$1.4<br>trillion to as<br>much as $7 trillion by that year. (Another editor’s note: We believe<br>these are cumulative numbers from 2025 or 2026 through 2030. That is not the<br>spending rate for a single year in 2030.)
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“CIOs are aggressively pivoting to hybrid AI,” the CEO said.<br>“The risk is not the cloud. The risk is losing control of your data, your cost,<br>your security, your intellectual property, and your speed. In the agent era,<br>lock-in does more than slow innovation. It actually limits what your company<br>can become. Soon, every company will deploy fleets of agents, composing<br>workflows on infrastructure that they control.”<br>Dell, of course, is big on selling on-premises AI<br>architecture, since that is in fact what it does for a living. None of the<br>hyperscalers and major clouds buy its PowerEdge and PowerStore iron, and they<br>never will. They can design and have made their own gear for a lot less money,<br>and keep the gap between what iron costs and what cloud charges as profit.<br>A few years back, the company introduced the Dell AI Factory<br>with Nvidia, which provides its riff on the racks and servers and storage for<br>Nvidia AI systems, aimed at companies looking to create a sovereign AI<br>environment. The company now has some 5,000 customers running Dell AI workloads<br>in their Dell AI factories that include not only the technology but design and<br>innovation, engineering, supply chain, services, support, and financing.<br>Dell featured three companies that are using its AI<br>technologies at scale and on premises. Pharmaceutical giant Eli Lilly in<br>February launched its LillyPod supercomputer, a Nvidia DGX SuperPOD powered by<br>1,016 Blackwell GPUs (below) that generates more than 9,000 petabytes of<br>performance. The system, used for drug discovery, also includes Dell storage<br>systems that provide almost 2 TB/sec of read bandwidth for the massive data<br>sets is uses.
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Samsung is using Dell AI technology in its semiconductor<br>design, manufacturing, and automation work, while Honeywell began partnering<br>with Dell and Nvidia last year for some of its AI operations.<br>“AI is fueling a renaissance in enterprise hardware, a shift<br>from bits back to atoms,” Dell said. “The question is, how do you deploy the<br>world's best models, where you need them with security and governance built in?”<br>Dell laid out his company’s plan to answer that question, a<br>collection of moves that ranged from new...