The global market for AI chips powering data centers and cloud infrastructure is projected to exceed $453 billion by 2030, according to IDTechEx. This surge is fueled by the rise of generative AI, large-scale AI deployments, and growing performance demands from advanced models.
GPUs remain dominant, particularly in hyperscale AI data centers and supercomputers, with leaders like NVIDIA and AMD pushing performance boundaries with chips like the H100/H200 and MI300 series.
However, concerns over cost, energy efficiency, and vendor lock-in have led hyperscalers to develop custom AI ASICs, offering more efficient, workload-specific alternatives. Companies such as Broadcom and Marvell are supplying chips that provide lower TCO and tailored AI performance.
Meanwhile, major players like Intel, Qualcomm, and Huawei, along with startups such as Cerebras, Groq, and Graphcore, are introducing novel AI architectures—from processing-in-memory to wafer-scale engines—aimed at balancing scalability, energy efficiency, and cost.
As data center capacity surges globally, energy and compute efficiency become critical. With a forecasted 14% CAGR from 2025 to 2030, the AI chip market is set to redefine the semiconductor industry, enabling breakthroughs in AI, cloud, and edge computing.
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