By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
The panelists agree that Applied Digital's (APLD) $36B contracted lease backlog is substantial and could translate into durable revenue growth if project delivery aligns with demand. However, they also highlight significant execution risks, customer concentration, and potential margin compression due to hyperscalers building their own capacity.
Risk: Customer concentration (CoreWeave, hyperscalers) and the risk of hyperscalers internalizing data center capacity, leading to margin compression.
Opportunity: APLD's unique 200MW+ liquid-cooling edge for high-density AI racks, which could command a 30-50% pricing premium and widen margins.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
Artificial intelligence (AI) stocks may have fallen out of favor over the past month for various reasons. However, the financial performance of companies involved in the build-out of AI data center infrastructure makes it increasingly clear that now is the time to capitalize on the pullback in AI stocks.
Goldman Sachs estimates that a whopping $7.6 trillion could be spent on AI data centers, computing hardware, and electricity between 2026 and 2031 in a base-case scenario. This historic infrastructure build-out can be attributed to AI's productivity gains. Anthropic, for instance, notes that using its Claude AI model could reduce the time taken to complete a task by 80%.
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The pure-play AI company also points out that AI could increase labor productivity in the U.S. by 1.8% annually over the next decade. That's double the growth rate seen since 2019. These potential productivity gains explain why trillions of dollars will be spent on building AI infrastructure. Applied Digital (NASDAQ: APLD) is one of the best ways to capitalize on this lucrative market.
Let's look at the reasons why.
Applied Digital is a pick-and-shovel AI play. The company designs, builds, and operates dedicated AI data centers for customers such as CoreWeave and hyperscalers. Not surprisingly, the demand for Applied Digital's services is extremely robust, as evidenced by the company's contracts to build and lease out 1.4 gigawatts (GW) of data center capacity.
Applied Digital points out that these contracts represent total contracted lease revenue of $36 billion over the long run. What's more, the potential lease revenue from these contracts balloons to $86 billion if customers decide to exercise renewal options. It is worth noting that Applied Digital generally enters into 15-year take-or-pay lease contracts with customers.
The $36 billion in contracted long-term lease revenue is a massive figure considering that Applied Digital's revenue in the recently concluded fiscal 2026, which ended on May 31, stood at $611 million. The company's top line jumped by an impressive 167% in the latest fiscal year. However, Applied Digital's fiscal Q4 revenue shot up 5x year over year to $259 million, driven by recognition of lease revenue from data center projects it has already completed.
As Applied Digital builds and delivers more data centers to customers, it will be able to convert more of its contractual lease backlog into revenue. Even better, Applied Digital isn't restricting itself to the 1.4 GW of data centers that it is currently constructing. The company is looking to expand capacity at its current campuses and is also marketing an additional 1.7 GW of capacity across multiple states.
Given the strong demand for AI data center infrastructure, it won't be surprising to see Applied Digital finding clients for the additional capacity that it plans to sell in the future. As a result, the company's long-term lease revenue pipeline could get even bigger.
We have already seen that Applied Digital's revenue growth accelerated in the final quarter of fiscal 2026. Analysts, however, are anticipating a slowdown in Applied Digital's top-line growth in fiscal 2027 to just 16%.
But as the chart above tells us, Applied Digital's revenue growth will start accelerating from the next fiscal year. However, this AI infrastructure specialist could spring a positive surprise and exceed Wall Street's expectations, given the phenomenal growth it reported last quarter.
Applied Digital claims that the company has built a track record of delivering data center capacity on time and on budget. If the company maintains its discipline, it can indeed grow faster than Wall Street's expectations. However, even if Applied Digital's revenue grows in line with consensus estimates and its revenue increases to $2.7 billion in fiscal 2029 (as per consensus estimates), its market cap could get close to $23.5 billion. That is nearly 3x its current market cap.
I am assuming a price-to-sales ratio of 8.7 to calculate Applied Digital's market cap after three years, which is in line with the U.S. tech sector's average sales multiple. However, it has the potential to deliver bigger gains due to its solid lease revenue pipeline, which should result in a stronger-than-expected top-line jump. Also, the market could reward this AI stock with a richer valuation due to its terrific growth.
All this makes Applied Digital an ideal stock to buy and hold for the long run to capitalize on the AI infrastructure build-out.
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The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Four leading AI models discuss this article
"The multibagger narrative assumes flawless execution and continued AI hype; consensus growth already prices in most of the backlog, leaving limited margin of safety."
Applied Digital (APLD) has an impressive $36B contracted lease backlog on 1.4 GW (potentially $86B with renewals) versus $611M FY2026 revenue, with Q4 jumping 5x YoY. Goldman’s $7.6T AI infra forecast through 2031 supports the secular tailwind. However, the article glosses over execution risk on a still-tiny balance sheet, customer concentration (CoreWeave, hyperscalers), and the fact that consensus already models revenue tripling to $2.7B by FY2029—implying the multibagger case is largely priced in at current levels. Power procurement, capex funding, and actual revenue recognition timing remain material unknowns.
If power costs spike, hyperscalers build their own capacity, or APLD misses even one delivery deadline on its 15-year take-or-pay contracts, the entire backlog could be renegotiated or canceled—turning the 3x upside into a 70% drawdown.
"The valuation of APLD hinges more on the credit quality of its undisclosed hyperscaler tenants and its ability to manage massive debt-funded capex than on the raw size of its long-term lease pipeline."
Applied Digital (APLD) is being sold as a 'pick-and-shovel' play, but investors must distinguish between contracted backlog and realized cash flow. While the $36 billion revenue pipeline sounds transformative, these are 15-year take-or-pay contracts that depend entirely on the creditworthiness of hyperscalers and the successful execution of massive capital-intensive builds. APLD’s transition from a crypto-mining-adjacent firm to a data center operator involves significant execution risk and heavy debt financing. Relying on an 8.7x price-to-sales multiple for a 2029 valuation is aggressive; if interest rates remain elevated or if the power-grid infrastructure bottlenecks delay delivery, that multiple will compress, potentially trapping capital in a low-margin, high-leverage utility play.
The massive demand for AI-ready data centers is so supply-constrained that APLD's ability to secure power and build capacity may provide a permanent competitive moat, rendering current valuation concerns moot.
"APLD has genuine revenue visibility but faces structural margin pressure from hyperscaler self-sufficiency and power infrastructure bottlenecks that could halve the multibagger thesis."
Applied Digital's $36B contracted lease backlog is real and material—that's 59x current annual revenue. The 5x Q4 YoY jump confirms execution. But the article conflates two separate theses: (1) AI infrastructure spending will be massive (likely true), and (2) APLD will capture outsized returns (unproven). The valuation math assumes 8.7x P/S by 2029—reasonable for tech, but APLD trades higher now. Execution risk is underweighted: power grid constraints, customer concentration (CoreWeave dependency?), and whether 1.7GW pipeline actually materializes. The article also ignores that hyperscalers (AWS, Google, Meta) are building their own capacity, which compresses margins for third-party operators.
If hyperscalers internalize 70%+ of AI capex and APLD's customer base narrows to secondary players, the $36B backlog becomes a liability—long-term contracts lock in low margins during a deflationary hardware cycle.
"Applied Digital could deliver outsized upside if its secured lease pipeline translates into timely, high-margin revenue, but the odds hinge on project delivery, customer credit, and a favorable AI capex cycle."
Strong case: the AI infrastructure wave is real, and Applied Digital sits as a builder with a long, take-or-pay lease backbone that could translate into durable revenue growth if project delivery aligns with demand. The 1.4 GW contracted capacity and $36B backlog, with optional renewals pushing potential to $86B, imply a high-margin, long-duration revenue stream. In a secular AI capex cycle, even moderate execution can unlock outsized upside, especially if the 2029 revenue target of ~2.7B materializes and the stock re-rates on rising visibility. Risks: backlog is not cash; realisation depends on deliveries, financing, and customer credit; valuation may be optimistic.
Backlog is not cash and 1.4 GW may not translate into timely revenue; a few customer delays or credit issues could materially shrink realized earnings and derail the bull case.
"APLD's liquid-cooling specialization creates a moat and pricing power overlooked by the panel."
Claude's hyperscaler internalization point is directionally right but incomplete: even if they build 70% internally, the residual 30% plus enterprise demand still exceeds near-term supply. Nobody has flagged APLD's unique 200MW+ liquid-cooling edge for high-density AI racks, which could command 30-50% pricing premiums and widen margins versus generic colocation plays.
"Hyperscalers will likely force cost-plus pricing on third-party operators, compressing the margins necessary to justify APLD's current valuation."
Grok, your focus on liquid-cooling premiums ignores the commoditization risk inherent in data center REITs. When hyperscalers face power constraints, they don't just pay premiums; they force cost-plus pricing models on operators, capping potential upside. Claude's concern about internalization is the real threat here. If APLD is relegated to a 'landlord' role, they lose the pricing power required to justify their current valuation. We are looking at a utility-like margin profile, not a high-growth tech multiple.
"APLD's moat is scarcity, not technology; when supply normalizes, the backlog becomes a margin trap, not an upside lever."
Gemini's cost-plus pricing concern is real, but misses that APLD's scarcity—1.4 GW of immediately available, power-secured capacity—gives temporary pricing power regardless of margin structure. The actual risk isn't margin compression; it's that hyperscalers solve power constraints faster than APLD can build, collapsing utilization and backlog conversion rates. Grok's liquid-cooling premium is defensible near-term, but Gemini's utility-like trajectory becomes inevitable if supply catches up within 3-5 years.
"Backlog-to-cash conversion risk could derail the bull case even if capacity is secured."
Claude, your internalization worry is valid, but the real vulnerability is conversion, not capacity. 1.4GW backlog is secured capacity, yet revenue realization depends on interconnection timelines, capex financing, and client credit. A 12–18 month grid delay or a single large counterparty issue could push cash-flow timing far beyond a user-friendly horizon, forcing renegotiations on 15-year take-or-pay terms and pressuring leverage. CoreWeave/hyperscaler concentration remains the Achilles’ heel.
The panelists agree that Applied Digital's (APLD) $36B contracted lease backlog is substantial and could translate into durable revenue growth if project delivery aligns with demand. However, they also highlight significant execution risks, customer concentration, and potential margin compression due to hyperscalers building their own capacity.
APLD's unique 200MW+ liquid-cooling edge for high-density AI racks, which could command a 30-50% pricing premium and widen margins.
Customer concentration (CoreWeave, hyperscalers) and the risk of hyperscalers internalizing data center capacity, leading to margin compression.