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Edge AI Inference & Training Chipset Shipment by Architecture: 2026 to 2031

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Artificial Intelligence and Machine Learning: Edge AI

Market Data | 2Q 2026 | MD-AIMLOD-104

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Total shipments of AI chipsets in edge AI (excluding personal and work devices) are set to increase to around 1.6 billion by 2031 at a CAGR of 17%. Application-Specific Integrated Circuit (ASIC) architectures continue to be the dominant architecture, driven by their energy efficiency and Total Cost of Ownership (TCO) benefits, crucial for edge AI, where  

Field-Programmable Gate Arrays (FPGAs) will continue to be used in industrial, medical, and aerospace applications, as evidenced by the AI silicon portfolios of EFINIX, Lattice Semiconductor, Altera, and AMD. Central Processing Unit (CPU) shipments for AI workloads will grow at a lower CAGR of 5%, although they have increased in importance since the emergence of Agentic AI workloads that require additional orchestration capabilities are best served by CPUs.