Dell Hikes Outlook as AI Server Backlog Hits $18.4B, Shares Jump

Dell's AI Server Bet: What Sales Teams Can Do With It Right Now

Dell lifted its fourth-quarter outlook and its stock popped 4% after hours. The driver: accelerating demand for AI-optimized servers, many built around Nvidia chips.

The company also named David Kennedy as its permanent CFO. For sellers, this signals confidence from the top and a clear go-forward plan around AI infrastructure.

Quick numbers that matter

• Q4 revenue guide: $31B-$32B (above consensus of $27.59B).
• Q4 adjusted EPS: $3.50 (above estimates of $3.21).
• Raised full-year revenue: $111.2B-$112.2B; adjusted EPS to $9.92.
• Q3: $27.01B revenue (slightly below $27.13B est.); adj. EPS $2.59 (beat $2.47).
• AI server revenue target: $25B in fiscal 2026 (up from $20B prior).
• Backlog: $18.4B; new AI server orders: $12.3B; shipped: $5.6B.
• Customers include the U.S. Department of Energy, G42, xAI, and CoreWeave.

Why buyers are moving now

Big Tech and AI-native companies are building capacity fast, which is pushing up prices on memory (DRAM and NAND) and stretching lead times. Dell's COO noted costs are moving faster than usual and some pricing impact may flow to customers, even as the company tries to limit it.

In short: demand > supply. Sellers gain leverage-if you can connect value to speed, availability, and time-to-deploy.

Sales plays to run this quarter

• Use urgency honestly: Lead with supply constraints, memory price trends, and backlog realities. Tie delay to lost model training time and missed product milestones.
• Price confidence (with options): Socialize potential price moves early. Offer phased configs, trade-up paths, or planned expansions to protect budgets without stalling the deal.
• Anchor on outcomes: Frame ROI around faster training cycles, higher utilization, and quicker inference deployment-not just GPU counts.
• Handle margin objections: If buyers bring up AI server competition (e.g., Super Micro Computer), steer to availability, validated designs, service SLAs, and total cost over 3-5 years.
• Bundle smart: Memory and storage are the pinch points; package them with servers to secure allocation and stabilize pricing.
• Lock in capacity: Push multi-quarter capacity plans, structured pre-orders, or framework agreements to guarantee delivery windows.
• Finance to win: Offer leasing or consumption-like models to match cash flow with deployment milestones.

Who to target (and what to say)

• AI-native startups (xAI, CoreWeave-style): Pitch speed-to-GPU and predictable scale. Offer pilot-to-production ramps with reserved capacity.
• HPC and public sector (e.g., U.S. DOE): Emphasize validated architectures, compliance, and program timelines. Reference wins carefully without naming sensitive details.
• Enterprise IT building internal AI platforms: Sell standardized racks, proven reference designs, and services for data, MLOps, and maintenance.
• Cloud and co-lo partners: Focus on co-selling and pipeline sharing. Secure joint forecasts for allocation priority.

Competitive notes

• Differentiation: Quality of integration, global service, and delivery assurance can matter more than raw list price during tight supply.
• Proof points: Reference major deployments and backlog scale as signals of reliability and ecosystem maturity.

Useful context

• Nvidia's data center GPUs remain at the core of most AI builds. See Nvidia data center overview.
• Public sector demand is real and growing. U.S. Department of Energy innovation.

Action checklist

• Update your talk tracks with current pricing signals on DRAM/NAND and realistic lead times.
• Bring 2-3 pre-baked configurations (good/better/best) that balance performance and ship dates.
• Create a "capacity lock" one-pager with terms for pre-orders and phased deliveries.
• Bundle memory and storage with explicit price-hold periods.
• Use mutual action plans tied to model training calendars, not just procurement dates.
• Set weekly allocation reviews with partners to protect your top deals.

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Bottom line: demand is hot, supply is tight, and budgets are opening for AI compute. Lead with availability, outcomes, and clear paths to scale-and close while momentum is on your side.