Advances in AI chips and health features are driving rapid adoption of on-device intelligence in wearables.
Artificial intelligence is rapidly transforming smartwatches from fitness trackers into intelligent health companions, with Edge AI-capable smartwatch shipments growing 70% year-on-year in the first quarter of 2026.
According to Counterpoint Research, Edge AI smartwatches now account for 25% of global smartwatch shipments, reflecting rising consumer demand for real-time, personalized health insights without relying on smartphones or cloud connectivity.
The shift is being enabled by low-power neural processing capabilities that allow AI models to run directly on the device. By processing health data locally, smartwatches can deliver instant alerts for events such as falls and irregular heart rhythms, while improving privacy and reducing latency. Counterpoint estimates Apple accounted for nearly 90% of global Edge AI smartwatch shipments during the quarter, highlighting its early lead in the segment.
Health monitoring remains the primary driver of Edge AI adoption. Rather than transmitting biometric data to cloud servers, AI-enabled smartwatches can analyze heart rate, sleep patterns, body temperature and other physiological signals on-device to detect conditions such as atrial fibrillation, sleep apnea and elevated blood pressure. As a result, shipments of smartwatches equipped with blood pressure monitoring doubled year-on-year in Q1 2026, while devices supporting sleep apnea detection tripled. Manufacturers are also investing in AI-powered features aimed at early diabetes monitoring.
The hardware ecosystem is evolving alongside software innovation. Apple’s Neural Engine-powered S9 chip, Huawei’s Kirin W80 paired with the Celia assistant, Qualcomm’s newly announced Snapdragon Wear Elite platform with a dedicated neural processing unit (NPU), and Google’s upcoming Tensor-based wearable chip are all designed to accelerate on-device AI capabilities. Meanwhile, chipmakers such as Ambiq are enabling AI inference through software optimization on vector-core processors, broadening access to Edge AI without dedicated NPUs.
Counterpoint expects Edge AI penetration in smartwatches to reach nearly 32% during 2026 as smaller AI models, operating system-level optimization and improved silicon enable richer health monitoring, gesture recognition and more personalized user experiences directly on wearable devices.
