Global technology intelligence firm ABI Research forecasts that TinyML AI chipset shipments, excluding personal and work devices, will grow at a 37% CAGR through 2031, surpassing 4.1 billion units. Related revenue is projected to exceed US$7.8 billion. The growth reflects embedded AI moving from experimentation to scaled deployment, particularly in industrial IoT and far-edge environments.
“The AI chipset market is fragmented but maturing at the same time,” said Paul Schell, Senior Analyst at ABI Research. “TinyML is gaining real traction as enterprises push intelligence closer to sensors and endpoints, while cloud and premium device segments continue to absorb the most advanced AI workloads.”
Within the TinyML segment, MCUs will lead shipments through the decade, while NPUs are expected to post the fastest growth at a 90% CAGR. In edge AI, Europe is projected to grow at a 17% CAGR, North America at a 16% CAGR, and Asia-Pacific at an 18% CAGR, with the latter exceeding 721 million AI chipset shipments by the end of the decade.
In cloud AI, training demand remains strong with increasing cluster sizes, while inference grows driven by rising token generation, multimodal generative output, reasoning models, and agentic AI workloads.
In personal and work devices, medium- to low-priced smartphones face near-term pressure from higher DRAM prices, with manufacturers such as Xiaomi, vivo, and OPPO reducing 2026 sales forecasts. Premium smartphones are expected to remain more resilient. Heterogeneous SoC architectures are gaining share as vendors including Qualcomm, MediaTek, Apple, AMD, and Intel optimize AI workloads across CPUs, GPUs, and NPUs.
“Over the next several years, competitive advantage in AI semiconductors will come from architectural fit, not just raw compute,” said Schell. “The strongest suppliers will be those that align silicon roadmaps with deployment realities, whether that means ultra-low-power inference at the far edge, premium on-device AI experiences, or scalable cloud platforms for training and orchestration.”
These findings are from ABI Research’s Artificial Intelligence & Machine Learning Market Data Overview: 2Q 2026.
