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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, presented separately in MD-AIMLED-104) are set to increase to around 1.6 billion by 2031 at a CAGR of 17%. 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 cost, thermal, and power constraints have a strong 
influence.

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. 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.