Applied Digital Stock: A $9 Billion Bet on the AI Buildout

Applied Digital (NASDAQ:APLD) is a digital infrastructure company that designs, builds, and operates AI-first data centers and high-performance computing (HPC) facilities. The stock has surged by almost 22% over the last five trading days, and remains up by roughly 4x year-to-date. The recent rally was driven by positive movements in the overall AI sector. Moreover, the completion and Ready for Service (RFS) designation for Applied Digital’s first AI data center, a 100-megawatt (MW) building at the Polaris Forge 1 campus in North Dakota, gave investors definitive proof that the company can execute on its ambitious AI infrastructure plans. While Applied Digital’s business sits at the heart of the ongoing AI infrastructure boom, with a valuation near $9 billion and the stock trading at a lofty 33x forward revenue, investors are now asking whether the rally still has legs.

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Custom Built AI Data Centers

Applied designs its campuses from scratch to meet the extreme power density, cooling needs, and scalability requirements of accelerated computing. Its facilities use liquid cooling, advanced power architectures, and renewable energy integration to maximize efficiency and reduce operating costs. Locations are selected for access to low-cost clean power and naturally cooler climates.

This purpose-built model is Applied’s defining edge. While most colocation and cloud providers retrofit aging facilities for AI, Applied optimizes every layer—electrical systems, cooling loops, rack layout, and energy routing—specifically for GPUs and high-density compute. Its partnership with ABB on medium-voltage power systems further boosts reliability and efficiency at scale. The key project underway is Polaris Forge 2 in North Dakota, a $3 billion, 280-MW campus now under construction and scheduled to come online in early 2027.

Riding the AI Infrastructure Wave

Big Tech’s spending on AI infrastructure is exploding: Microsoft, Amazon, and Meta alone are expected to deploy over $380 billion in AI-related capex in 2025, and this is likely to rise to more than $500 billion in 2026. All this investment requires physical compute capacity, and purpose-built data centers are becoming the bottleneck in the ecosystem.

Applied is positioned squarely in this gap. The company builds, owns, and operates AI/HPC campuses and leases critical power capacity (in megawatts) to hyperscalers under long-term contracts, giving it highly visible, multi-year revenue that scales with GPU demand. A prime example is its partnership with CoreWeave. A $7 billion lease agreement signed in June was expanded by another 150 MW at Polaris Forge 1, bringing total contracted revenue to roughly $11 billion.

Beyond leasing, Applied is expanding its service layer through the Applied Digital Cloud, offering GPU-as-a-Service for enterprises that need high-performance compute but don’t want to operate their own hardware. Through collaborations with Nvidia and Super Micro, Applied deploys state-of-the-art GPU nodes tuned for AI and HPC workloads.

Valuation And Risks

While Applied’s valuation is rich, the company is likely to grow fast as its new data centers come online. See: APLD Valuation Ratios.  Consensus points to about 38% revenue growth for 2026 and about 85% growth for 2027. As AI workloads grow exponentially, demand for data centers optimized for GPU compute is surging, and this could drive profitability in the long run. The company’s multi-gigawatt capacity pipeline and committed anchor customers could position it as a prime beneficiary of this secular trend. APLD is also a relatively small company ($9 billion market cap) in a massive, rapidly expanding sector. Doubling its revenue/market cap is proportionally easier than doing so for say NVDA (over $4 trillion) or AMZN (over $2 trillion).

That said, risks remain. Applied is highly capital-intensive, with billions tied up in new campus builds, exposing the company to execution delays or cost overruns. Its valuation is already elevated, leaving little room for missteps. Additionally, the market for AI data center services is becoming increasingly competitive, with traditional hyperscalers and cloud providers expanding their own capacity, which could pressure margins or slow customer acquisition.

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