Dell Technologies raised its full-year revenue and profit forecasts Wednesday after AI infrastructure demand pushed quarterly sales to a record $47 billion - a 58% jump from the same period last year that beat Wall Street estimates by more than $2 billion. For sales teams, the numbers signal where enterprise budgets are moving and which conversations will dominate the second half of 2026.
The company now expects full-year revenue of $192 billion, up from its previous $167 billion forecast. Adjusted earnings-per-share guidance rose to $25.50 from $17.90. Shares climbed nearly 10% in premarket trading.
Orders and backlog point to sustained demand
Dell reported $60 billion in orders during the quarter. Its backlog reached $95 billion. Both figures reflect heavy investment in data centre infrastructure capable of running large language models and other AI workloads.
AI cloud providers including Nscale and CoreWeave are buying Dell servers equipped with advanced chips to build computing clusters for training and operating AI models. Analysts at J.P. Morgan said Dell's "AI momentum remained strong," pointing to the record orders and sizeable backlog as evidence of sustained demand.
Storage business gets an AI lift
Growth extended beyond servers. Dell's storage business - one of its most profitable units - also expanded. Analysts at Melius Research said AI adoption was supporting that growth, as customers need storage systems that can handle the data volumes AI workloads generate.
The stronger results lifted shares across the sector. Super Micro Computer gained 0.7% and Hewlett Packard Enterprise rose 5.4%. If Dell holds its gains around $465 per share, it would add roughly $26 billion in market value. Dell trades at 18.12 times expected earnings, compared with 12.56 for HPE and 8.06 for Super Micro Computer, according to LSEG data.
Why this matters for sales professionals
When infrastructure spending accelerates at this pace, it reshapes procurement priorities across industries. Companies buying AI servers and storage are the same organisations evaluating AI tools for sales workflows, customer analytics, and pipeline management. Understanding the infrastructure layer helps sales teams speak credibly about AI adoption - and spot where their own prospects are investing. For representatives who want to connect these dots with buyers, an AI Learning Path for Sales Representatives provides practical grounding in the technology driving these deals. Broader trends in AI for Sales continue to shift how teams qualify leads, forecast revenue, and engage accounts.
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