Credo's Supercycle Appeal Misses the Long-Term Penetration Play

Credo Technology Group's momentum accelerated sharply in early 2026, fueled by hyperscaler demand for AI connectivity. Q1 revenue jumped 274% year-over-year to $223.1 million, then surged another 20.2% sequentially to $268.0 million in Q2 according to financial results. Management projects Q3 revenue between $335 million and $345 million, signaling sustained optimism.

This growth stems directly from hyperscalers expanding AI training and inference clusters, requiring Credo's energy-efficient solutions. Their stable 67.7% non-GAAP gross margin demonstrates they're scaling efficiently despite rapid growth. The market values this trajectory highly, pricing in perpetual hyperscaler demand that could justify premium multiples.

However, concerns linger in the broader data center ecosystem. REITs, beneficiaries of earlier AI demand, face 2025 headwinds from oversupply risks and end-users building in-house facilities. Rising development costs and Microsoft's scaled-back data center plans suggest the environment could cool. Credo's valuation, while reflecting strong fundamentals, assumes hyperscaler demand remains resilient even as sector dynamics shift.

Growth Mechanics & AI Infrastructure Traction

Hyperscaler demand is accelerating at an unprecedented pace, yet physical infrastructure constraints are creating major bottlenecks. BloombergNEF projects U.S. data center power demand will double to 78 gigawatts by 2035, driven primarily by AI training clusters requiring multi-gigawatt capacity. This surge is already evident: data centers consumed 183 terawatt-hours (TWh) in 2024, with the International Energy Agency forecasting a 133% jump to 426 TWh by 2030 due to AI's energy-intensive workloads.

Despite this growth, supply chains face severe limitations. Construction lags of seven years from planning to operation create supply shortages. Ownership concentration compounds this, with AWS, Google, Meta, and Microsoft controlling 42% of U.S. capacity. Suburban site preferences and grid bottlenecks further strain expansion efforts, particularly in high-demand regions like Virginia where data centers consume up to 26% of state electricity.

The tension between escalating demand and infrastructure delays creates double-edged risks. While AI growth fuels current demand, grid reliability concerns and potential oversupply could emerge if projects overextend before demand materializes. For hyperscaler-dependent suppliers, execution risks around permitting timelines and energy costs could temper near-term growth trajectories.

Penetration Risks & Substitution Threats

The impressive AI-driven expansion of data centers faces growing headwinds from substitution threats and operational frictions. Major cloud providers are accelerating in-house infrastructure development, eroding third-party demand prospects beyond 2027. This shift reflects hyperscalers' vertical integration strategy to control AI compute resources directly. According to market analysis, Microsoft's recent data center plan adjustments signal market saturation concerns. The company scaled back expansion timelines as hyperscaler capacity now accounts for 42% of U.S. data center resources, reducing competitive pressure for new developments. Rising construction costs and regulatory hurdles have further tempered investment enthusiasm across the sector.

Lower AI training costs compound spending pressures. Models like DeepSeek's R1 demonstrate that advanced AI development requires significantly fewer compute resources than previously assumed, reducing the demand intensity for massive data center investments.

These trends collide with physical constraints. Power grid bottlenecks and suburban site limitations continue to delay new developments, while the shift toward tertiary markets creates uncertain demand patterns. Construction lead times averaging seven years mean oversupply risks could materialize if demand growth slows, particularly since BloombergNEF projects capacity may outpace requirements once the current development cycle concludes.

Concentration among hyperscalers further complicates the landscape. With AWS, Google, Meta and Microsoft controlling most new capacity, third-party providers face limited expansion options while grid constraints restrict geographic flexibility. This combination of substitution threats and operational bottlenecks suggests an overoptimistic growth trajectory for data center real estate investment.

Valuation Risks and Decision Triggers

Credo Technology Group's blistering revenue growth highlights massive AI infrastructure demand, but this momentum faces critical valuation pressures. Hyperscaler vertical integration poses a direct threat to Credo's cost/performance ratio. As AWS, Google, Meta, and Microsoft control 42% of U.S. data center capacity, their in-house silicon and optics development could gradually displace third-party connectivity solutions. This substitution risk intensifies if hyperscalers achieve parity in performance while locking in lower unit costs through proprietary designs.

Simultaneously, BloombergNEF's projection of US data center demand doubling to 78 gigawatts by 2035 assumes sustained AI compute expansion. Yet the industry's seven-year construction timeline creates a dangerous mismatch. If hyperscalers accelerate internal capacity building or AI efficiency gains outpace demand (as seen with lower-cost models like DeepSeek's R1), the projected demand surge could stall. This would expose oversupply in data center REITs, directly impacting Credo's end-market health. Indeed, REIT performance shifted from a 77% five-year return in 2024 to caution in 2025 amid oversupply fears and end-users moving in-house.

Investors must monitor three key catalysts. First, hyperscaler capital allocation: Microsoft's recently scaled-back data center plans signal potential moderation in AI infrastructure spending, which could ripple down to suppliers like Credo. Second, regulatory approvals for grid upgrades and new facilities face delays that could either squeeze timelines or force hyperscalers into less efficient expansions. Third, widespread adoption of efficient AI architectures could indefinitely defer new capacity needs. The critical demand sustainability indicator here is Credo's own guidance: projecting $335–345 million in Q3 revenue reflects strong near-term demand, but its ability to maintain this growth trajectory hinges on navigating the substitution risk and infrastructure deployment realities.