Over a century ago, Henry Ford transformed manufacturing with the mass production of car engines, making transportation accessible to millions. Today, a new kind of factory is emerging—one that produces intelligence, not automobiles. As artificial intelligence (AI) moves from experimentation to enterprise-scale implementation, the global demand for AI infrastructure is surging. Leading technology companies are racing to build the powerful servers—“engines of AI factories”—that will fuel this new era of growth and innovation.

Dell Technologies at the Center of the AI Infrastructure Boom

Dell Technologies has positioned itself as a leader in this technological renaissance. In partnership with NVIDIA, Dell is accelerating the pace of AI innovation, delivering next-generation servers and infrastructure designed to meet the world’s exploding appetite for AI. According to Michael Dell, Chairman and CEO, “We’re on a mission to bring AI to millions of customers around the world. With the Dell AI Factory with NVIDIA, enterprises can manage the entire AI lifecycle across use cases, from training to deployment, at any scale”.

Dell’s AI server business is projected to grow by at least $15 billion this year, reflecting the company’s aggressive push to supply the backbone of AI factories worldwide. In the first quarter of fiscal 2025, Dell’s Infrastructure Solutions Group reported a 22% increase in revenue, driven by record AI server orders and a growing backlog—clear signals of robust, structural demand.

Next-Generation AI Servers: Power, Scale, and Speed

The latest Dell AI servers, powered by NVIDIA’s Blackwell architecture, represent a leap in performance and efficiency. These systems deliver up to 50 times more AI reasoning inference output and five times greater throughput compared to previous platforms. Customers are leveraging this power to generate tokens for new AI applications addressing challenges from disease prevention to advanced manufacturing.

Dell’s new PowerEdge XE9780 and XE9785 servers, available in both air- and liquid-cooled versions, support up to 192 NVIDIA Blackwell Ultra GPUs per rack, with custom configurations scaling to 256 GPUs. This enables enterprises to train large language models up to four times faster than before. The company’s PowerCool technology and advanced networking further enhance efficiency and scalability, making these servers ideal for the most demanding AI workloads.

Manufacturing the Engines of Intelligence

Inside Dell’s U.S. facilities, the scale and complexity of modern AI server production is staggering. The NVIDIA GB200 NVL72 servers, for example, contain 1.2 million parts and were designed in just a year. Dell’s assembly lines are engineered for speed and precision: racks are grouped by assembly phase, with employees installing GB200 trays and NVLink Switch networking before rigorous system testing. The company boasts the ability to build, test, ship, and even re-test racks on-site at customer locations—all within 24 hours.

This rapid production capability is critical as demand for AI infrastructure accelerates. Dell has shipped thousands of NVIDIA Blackwell GPUs in a single week, and recently fulfilled an order to deploy 100,000 NVIDIA GPUs in just six weeks for a major customer.

The Global Race for AI Factories

The need for AI infrastructure is not limited to the U.S. or a handful of tech giants. The European Union has announced plans for seven AI factories, while countries including India, Japan, Saudi Arabia, the UAE, and Norway are also investing heavily in AI data centers. These facilities require enormous resources: a single data center can contain 27,000 miles of network cable, six miles of water pipes, and circulate 100,000 gallons of water per minute for cooling.

Full-Stack Solutions and Managed Services

Dell’s strategy extends beyond hardware. The Dell AI Factory with NVIDIA offers a full-stack solution, including managed services, advanced storage, and software optimized for AI workloads. The company’s hybrid and on-premises solutions are designed to help enterprises reduce cloud costs, improve data security, and accelerate time to value for AI projects.