AI Hardware Demand Resilient Amid Macro Headwinds; Power, Cooling, and Networking Suppliers Poised to Benefit

Core Conclusion

Structural demand for AI servers is accelerating, creating multi-year growth tailwinds for key supply chain components undergoing significant technological upgrades, particularly in power delivery, cooling, and high-speed networking. Investment returns will accrue to suppliers with high exposure to these AI-driven segments, defensible market positions, and valuations not yet fully pricing in the upgrade cycle.

What the Market May Be Underpricing

The market likely underestimates the magnitude of value uplift per rack from next-generation AI hardware transitions, such as the shift to 800V HVDC power architectures and advanced liquid cooling. Furthermore, the stark divergence between resilient AI infrastructure demand and weakening consumer electronics (PCs, smartphones) is not adequately reflected in the relative valuations across the hardware sector.

Evidence Chain

AI Server Demand Remains Structurally Strong vs. Slumping Consumer Electronics. Server shipments are forecast to grow 2% in 2026e and 5% in 2027e. This contrasts sharply with PC shipments forecast to decline -2% in 2026e and smartphones forecast to decline -12% in 2026e. The rollout of next-gen platforms like the GB200/300 NVL72 is accelerating, with projected deliveries surging from ~29K racks in 2025 to ~70K in 2026e. The investment implication is clear: selective exposure to the AI infrastructure supply chain is critical, while broad-based hardware exposure is challenged.

Technology Upgrades Are Driving a Step-Change in Component Value Per Rack. Next-gen platforms require more sophisticated power and cooling solutions, dramatically increasing their dollar content. For example, the power solution value for a Vera Rubin rack with an 800V HVDC architecture is ~$398k, over 5x the value of a standard 110kW power shelf. Cooling component value for a Vera Rubin compute tray is 18% higher than for GB300 due to fanless designs and higher TDPs (up to 2300W). This translates to superior revenue growth and potential pricing power for component specialists leading these transitions, such as Delta Electronics and AVC.

Specific Suppliers Are Highly Leveraged to High-Growth AI Segments. Company-specific growth trajectories validate the thesis of asymmetric opportunity. Accton is projected to achieve a 2024-27e revenue CAGR of 70% for its network appliances business, driven by AI data center switch demand and a 41% share in the ODM switch market. King Slide, with ~90% share in server slide rail kits, is forecast to grow revenue at a 37% CAGR, benefiting from larger rack sizes. Investors should focus on companies with such clear AI-driven growth algorithms and leading market positions.

Valuation Premiums Are Tied to AI Profit Exposure. The market is rationally awarding higher multiples to companies with greater AI-related earnings. For 2026e, key AI profit exposures are: Accton (75-80%), Quanta (46%), and Hon Hai (35%). This is reflected in 2026e P/E multiples: Accton trades at 24.1x, while Quanta trades at 11.4x. The valuation gap between high-growth component specialists and ODMs presents opportunities where rising AI profit contribution may drive a valuation re-rating.

Key Divergences & Risks

• Consumer Electronics Downturn: A sharp downturn in smartphones and PCs, exacerbated by memory cost inflation, poses a drag on sector sentiment and the non-AI segments of diversified companies.
• Supply Chain & Cost Pressures: Bottlenecks in substrates (e.g., ABF from 2027e) or inflation in raw material costs (copper, nickel) could delay AI hardware rollouts or compress supplier margins.
• Valuation Risk: For companies where high AI growth expectations are already fully priced in, there is limited room for multiple expansion, increasing sensitivity to execution delays.

Valuation & Trade Implications

Focus should be on companies with: 1) High and growing exposure to AI server/data center spend, especially in power, cooling, and connectivity; 2) Defensible market share in a growing segment; and 3) A valuation (P/E, PEG) not fully reflecting the multi-year growth trajectory. Opportunities may exist in names like Quanta and Wistron where AI profit contribution is rising rapidly but valuation re-rating appears incomplete. Avoid broad-based hardware exposure given the diverging fundamentals.

Appendix: Data Summary

Selected Greater China Tech Hardware Coverage

Demand Forecast – Diverging Trajectories