# Marvell Stock Soars Amid AI Demand, Projects 30% Revenue Growth

> Marvell beat on AI demand, with $2.22B revenue, $0.80 EPS, and shares jumped 16%. Guides 30%+ to ~$11B; sellers should tie to faster capacity, throughput, and time-to-deploy.

- Type: AI news
- Page: https://completeaitraining.com/news/marvell-stock-soars-amid-ai-demand-projects-30-revenue/
- Published: 2026-03-07
- Updated: 2026-03-08
- Author: Jeroen Erne
- Jobs: Sales
- Reading time: 2 min

### Marvell's AI-Fueled Beat and Raise: What It Means for Your Sales Strategy

Marvell Technology raised its outlook after an earnings beat tied to strong AI demand. Shares jumped more than 16% even as broader markets slipped, pulling the stock back into positive territory for the year.

The company reported adjusted EPS of **$0.80** on record fourth-quarter revenue of **$2.22 billion**, up **22%** year over year. Management now expects revenue to grow **30%+** in the year ahead to nearly **$11 billion**, versus the prior **$9.5 billion** projection made in September. The fiscal 2028 revenue outlook also rose to **$15 billion**, up **$2 billion** from last quarter's forecast.

#### The numbers that move budgets

On the call, CEO Matt Murphy said the higher forecast is "**all being driven by our data center business**," as tech giants continue to scale AI infrastructure. For the current quarter, Marvell guided revenue to **$2.28-$2.52 billion** and adjusted EPS to **$0.74-$0.84**, both above consensus.

Translation for sellers: AI infrastructure spend is alive and accelerating. Budget holders are prioritizing capacity, throughput, and time-to-deploy.

#### Why this matters if you carry a quota

- Budgets are opening for AI infrastructure. Tie proposals to faster model training, higher GPU utilization, and reduced bottlenecks.
- Decision speed is increasing. Bring short, clear business cases with deployment timelines, not just feature lists.
- Buying groups are bigger. Multi-thread across IT, data, infrastructure, finance, and security to keep momentum.
- Proof beats pitch. Lead with reference architectures, pilots, and measurable outcomes within 30-60 days.
- Address risk early. Acknowledge vendor concentration concerns and show contingency plans, interoperability, and phased rollouts.

#### Who to target next quarter

- Cloud providers and hyperscalers expanding AI training and inference clusters.
- Colocation and data center operators adding high-density capacity.
- Systems integrators and OEM partners standardizing AI-ready stacks.
- Enterprises with live LLM or computer vision projects that are power, network, or storage constrained.

#### Signals to qualify fast

- Backlog of AI workloads waiting on infrastructure.
- GPU delivery commitments with networking or storage gaps.
- Power and cooling upgrades in flight, plus rack-space constraints.
- Board-level mandate to scale AI use cases this year.
- Line items for data center networking, interconnects, or accelerated storage.

#### Talk tracks that win budget

- Time-to-capacity: how your solution gets GPUs productive weeks faster.
- Throughput per dollar: more tokens/images per watt, per port, or per rack.
- Risk and reliability: redundancy, service SLAs, and migration plans that keep training on schedule.
- Finance-first: clear TCO, payback periods, and levers to stagger spend by milestone.

#### Your action plan

- Audit pipeline for AI-adjacent deals you can accelerate with pilot-based closes.
- Add a mutual action plan to every stage-3+ opportunity: dates, owners, proof points, and acceptance criteria.
- Create a one-page ROI template aligned to GPU utilization and training time reductions.
- Partner up: co-sell with integrators and data center operators already in the customer's plan.

#### Further context and resources

For additional company updates and materials, see [Marvell Investor Relations](https://investor.marvell.com/?ref=completeaitraining.com).

Want to sharpen your approach as AI budgets grow? Explore [AI for Sales](https://completeaitraining.com/tag/sales/) or follow the [AI Learning Path for Sales Representatives](https://completeaitraining.com/learningpath/ai-for-sales-representatives/) to operationalize prospecting, qualification, and CRM automation around AI-driven accounts.

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