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Racks, Risk, and ROI: A New Framework for Evaluating AI Server Vendors

As AI server demand surges toward a projected US$523 billion market by 2030, enterprises and hyperscalers must weigh performance, cost, and sustainability challenges when choosing OEM partners.

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Evaluating AI Server Vendors in a High-Stakes Market

Artificial Intelligence (AI) servers are fast becoming the backbone of digital infrastructure. ABI Research forecasts the market to reach US$245 billion in 2025 and more than US$523 billion by 2030. Hyperscalers, enterprises, and emerging neocloud providers are scaling GPU and ASIC clusters to support GenAI training, inference, and agentic workloads—while grappling with power constraints, tariffs, and intensifying global competition. This whitepaper outlines a new framework for evaluating AI server vendors, providing guidance on performance, risk, and return on investment.

 

Topics Covered

  • Market Outlook: Growth trajectories across hyperscalers, private clouds, neoclouds, and community clouds

  • Regional Trends: U.S. and China lead in CAPEX, with the Middle East rising as a sovereign AI hub

  • Workload Diversification: Scaling medium-to-heavy inference, agentic AI training, and light inference deployments

  • Demand Drivers: GenAI adoption, hyperscaler infrastructure expansion, and neocloud differentiation

  • Critical Risks: Power availability, tariffs, silicon challengers, and Chinese decoupling

  • Competitive Landscape: Strengths, differentiators, and strategies of top AI server OEMs

  • Recommendations for OEMs: Speed to market, education on power/cooling, silicon partnerships, and lifecycle services

 

Download the whitepaper today to discover how enterprises and hyperscalers can evaluate AI server vendors, mitigate risks, and optimize return on infrastructure investments.

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