Dell Technologies’ AI-optimized server business reached $16.4 billion in fiscal 2027 second-quarter revenue, doubling from a year earlier, as the company recorded $60.9 billion in quarterly AI server orders and finished the period with a $95 billion backlog. The figures place Dell among the clearest beneficiaries of the race by cloud providers and large enterprises to expand computing capacity for artificial-intelligence workloads.
Dell said total quarterly revenue rose 58% year over year to $47 billion, while non-GAAP diluted earnings per share climbed 203% to $7.04. GAAP diluted EPS was $6.34, up 273%. The company’s results and sharply higher outlook indicate that AI infrastructure demand is moving beyond isolated hardware deployments into sustained, large-scale purchasing programs.
The $95 billion AI server backlog is equivalent to roughly 5.8 quarters of shipments at the latest quarterly revenue rate. Backlogs do not guarantee that every order will convert into revenue on the same timetable, but the scale gives Dell substantial visibility into future deliveries and places manufacturing capacity, advanced processors, networking equipment, and data-center power systems under continued pressure.
Dell lifts outlook well above consensus
Dell raised its fiscal 2027 revenue forecast by $25 billion to $192 billion, implying annual growth of 69%, according to the company. It also lifted its full-year non-GAAP EPS outlook from $17.90 to $25.50 and set a target of $74 billion in AI-optimized server revenue for the year, representing projected growth of 200%.
For the fiscal third quarter, Dell forecast revenue of $49 billion, or 81% year-over-year growth. That is well above the $41.42 billion consensus estimate cited in the supplied figures. The company projected non-GAAP EPS of $6.50, compared with the $4.48 consensus figure, and GAAP EPS of $6.10.
The guidance suggests Dell expects its AI server order book to translate into deliveries more rapidly than previously anticipated. Hardware makers have faced a difficult balance: customers want accelerated-computing systems quickly, while supply chains must coordinate specialized chips, memory, high-speed networking components, cooling equipment, and physical data-center space.
Jeff Clarke, vice chairman and chief operating officer of Dell Technologies, said the depth of the order backlog reflects supply constraints around the computing hardware required for AI systems. The bottleneck extends beyond processors. Large AI clusters require racks of servers, dense networking, power distribution equipment and cooling systems that can support far higher electricity loads than conventional corporate data centers.
Infrastructure division drives revenue surge
Dell’s Infrastructure Solutions Group, which includes servers, networking and storage, generated $31.8 billion in quarterly revenue, up 89% from a year earlier. Operating profit in the segment rose 225% to $4.8 billion, according to Dell.
Traditional servers and networking contributed $10.5 billion in revenue, up 122%, showing that spending has not been confined to systems marketed specifically for AI. Storage revenue rose 26% to $4.9 billion. That mix matters because AI deployments require supporting infrastructure to move, store and manage the data used to train and operate models.
The company’s Client Solutions Group, which houses its PC business, reported $15 billion in revenue, up 20%. Commercial client revenue increased 22% to $13.2 billion, while consumer revenue rose 7% to $1.8 billion. Segment operating profit grew 42% to $1.1 billion.
Dell returned $4.3 billion to shareholders through dividends and share repurchases during the quarter, a record amount for the company. Cash flow from operating activities moved in the opposite direction, declining 12.5% to $2.225 billion from $2.543 billion a year earlier. Rapid revenue growth can require heavier working-capital commitments as a manufacturer purchases components and builds systems before completing deliveries.
Power demand becomes a practical constraint
The expansion of AI computing is increasingly tied to electricity availability. BloombergNEF has warned that U.S. data-center electricity demand could reach 78 gigawatts by 2035. The research organization said global power capacity serving AI-related computing systems had reached 30 gigawatts late last year, comparable to New York state’s peak electricity demand.
Those estimates frame a constraint that hardware revenue alone cannot solve. A server can be shipped once components are available; a data center may take years to connect if transmission lines, substations, generation capacity, or local permits lag behind construction plans. In markets such as Virginia, where data-center development is concentrated, power-access questions have become central to project timelines.
The pressure may also affect proof-of-work cryptocurrency mining in regions where miners and data centers compete for large blocks of power. Mining facilities can be flexible loads in some cases, reducing consumption when electricity prices rise or grids are strained. Yet they also depend on reliable, competitively priced energy, making them exposed to utility decisions, interconnection delays and changing regional demand.
A shift by some graphics-processing-unit owners from crypto mining toward AI leasing is plausible where AI contracts generate higher returns, but the economic calculation differs by hardware type, electricity cost, token price and the availability of customers. Bitcoin mining, for example, relies predominantly on application-specific machines rather than the GPUs used in many AI workloads.
Claims that traders should move funds into proof-of-stake assets by a particular deadline, or use options as a blanket hedge against AI-related power shortages, go beyond the evidence in Dell’s earnings report and BloombergNEF’s power projections. Network transaction fees and hash rate are shaped by several variables, including token prices, mining profitability, block-space demand and protocol design.
Dell’s results offer a more concrete signal: spending on AI infrastructure is arriving at a scale large enough to reshape equipment supply chains and intensify competition for data-center capacity. The next test will be whether power grids and construction pipelines can expand quickly enough to support the server orders already sitting in manufacturers’ backlogs.
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