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Global Market for Computing and AI for Data Centers 2026-2040: AI ASICs is the Fastest-growing Processor Category, As Companies Including Google, Amazon, Microsoft, Meta Invest Heavily

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GOOGL Google is investing heavily in AI ASICs (TPU series) for data centers, indicating a strong focus on and growth in this rapidly expanding market segment. AMZN Amazon Web Services (AWS) is investing heavily in AI ASICs (Trainium and Inferentia) and developing custom silicon for data centers, showing strong commitment to this growing AI compute market. MSFT Microsoft is heavily investing in AI ASICs (MAIA) and Arm-based CPUs (Cobalt) for its data centers, highlighting its significant role and growth in the AI compute infrastructure market. META Meta is investing heavily in its own AI ASICs (MTIA) for data centers, demonstrating a strong strategic push into custom silicon development for AI workloads. NVDA Nvidia continues to dominate the GPU market for AI workloads with successive generations of processors, holding an overwhelming share and driving growth in the AI data center space. AMD AMD provides competition in the AI accelerator market with its MI-series, but faces pressure from hyperscalers developing custom silicon and Nvidia's dominance. INTC Intel maintains a leading position in the server CPU market with its x86 architecture but faces increasing pressure from Arm-based alternatives and emerging RISC-V architectures. MU Micron is a key supplier of High Bandwidth Memory (HBM), which has emerged as a critical bottleneck in the AI chip supply chain, indicating its importance but also potential supply constraints.

Global Market for Computing and AI for Data Centers 2026-2040: AI ASICs is the Fastest-growing Processor Category, As Companies Including Google, Amazon, Microsoft, Meta Invest Heavily Dublin, April 16, 2026 (GLOBE NEWSWIRE) -- The "The Global Market for Computing and AI for Data Centers 2026-2040" report has been added to ResearchAndMarkets.com's offering.

The Global Market for Computing and AI for Data Centers 2026-2040 is a comprehensive strategic intelligence report covering the full landscape of data centre processor technology, market dynamics, competitive positioning, and long-range forecasting through to 2040.

Produced for technology executives, semiconductor investors, strategic planners, and policy analysts, the report provides the depth of quantitative rigour and qualitative insight required to navigate one of the most rapidly evolving markets in the global economy.

The report opens with a set of preliminary materials including a detailed glossary of technical terms and abbreviations, a clear articulation of research objectives and scope, biographical profiles of the authoring team, and a candid retrospective on previous forecast accuracy. This is followed by a three-page summary and a full executive summary designed for senior readers who require rapid orientation to the report's key findings without sacrificing analytical depth.

The global market for computing and artificial intelligence in data centers represents one of the most dynamic and capital-intensive segments of the semiconductor industry. Driven by the rapid proliferation of generative AI, large language models, and agentic AI systems, demand for specialised data center processors - encompassing GPUs, AI ASICs, CPUs, and FPGAs - has entered a period of extraordinary and sustained growth. From a market valued at approximately $215 billion in 2025, the sector is projected to scale dramatically through 2040, as hyperscalers, cloud providers, and enterprises race to build the compute infrastructure required to train, fine-tune, and serve increasingly powerful AI models.

At the core of this expansion is the GPU, which remains the dominant processor architecture for AI workloads due to its unmatched parallel processing capability and mature software ecosystem. Nvidia continues to hold an overwhelming share of this segment, with successive generations - from Hopper to Blackwell to Rubin and beyond - each delivering step-change improvements in compute density, memory bandwidth, and energy efficiency. AMD provides meaningful competition with its MI-series accelerators, while the broader landscape is being reshaped by hyperscalers developing their own custom silicon to reduce dependency on merchant chip vendors and lower total cost of ownership.

AI ASICs represent the fastest-growing processor category, as companies including Google, Amazon Web Services, Microsoft, and Meta invest heavily in purpose-built chips optimised for specific workloads such as inference, recommendation, and training. These internally developed accelerators - including Google's TPU series, AWS Trainium and Inferentia, Microsoft MAIA, and Meta's MTIA - are increasingly displacing third-party GPUs for certain use cases, fundamentally altering the competitive dynamics of the market and creating a parallel ecosystem of chip co-designers and advanced packaging specialists.

The server CPU market, though more mature, continues to evolve rapidly. Intel and AMD maintain leading positions with their x86 architectures, but face mounting pressure from Arm-based alternatives championed by hyperscalers such as AWS with Graviton, Google with Axion, Microsoft with Cobalt, and Nvidia with Grace and Vera. RISC-V is also emerging as a credible contender for specific workloads, particularly as open-source hardware ecosystems mature. Meanwhile, FPGAs continue to serve niche roles in low-latency and specialised inference applications.

Underpinning all of this is a complex and increasingly strained supply chain. Advanced semiconductor manufacturing is concentrated at TSMC, Samsung, and Intel Foundry, with leading-edge nodes below 5nm commanding the majority of AI chip demand. High Bandwidth Memory, supplied primarily by SK Hynix, Samsung, and Micron, has emerged as a critical bottleneck, while advanced packaging technologies such as CoWoS are operating at near-full capacity. Hyperscaler capital expenditure continues to flow into data centre construction, power infrastructure, and silicon procurement at a scale that is reshaping global semiconductor supply chains.

Geopolitics adds a further layer of complexity. US export controls on advanced AI chips have accelerated China's drive toward semiconductor self-sufficiency, with domestic players such as Huawei HiSilicon, Cambricon, Biren, and Hygon developing increasingly capable alternatives. The bifurcation of the global AI compute market into US-aligned and China-domestic supply chains is one of the defining structural trends of the decade, with profound implications for technology strategy, investment allocation, and national industrial policy.

Report Highlights

Global AI infrastructure and investment landscape

Market Forecasts (2021-2040)

Market Trends

Technology Trends

Outlook

81 Individual Company Profiles, Covering Strategy, Products, Financials, and Roadmap

For more information about this report visit https://www.researchandmarkets.com/r/f2esqy

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