Consumer Tech Drives Edge AI Growth
- Edge AI chips are becoming central to modern devices as companies shift computation away from the cloud to improve speed, privacy and energy efficiency.
- A new IDTechEx report forecasts that consumer electronics will continue to dominate this market through 2036.
- Rising hardware costs, expanding AI capabilities and growing demand for on‑device intelligence are shaping the next decade of chip development.
Edge AI Demand Accelerates Across Devices
Latency, energy use and privacy concerns are pushing AI computation from the cloud to local hardware. This shift made 2025 a breakout year for edge AI, particularly in consumer electronics where AI‑enabled smartphones and PCs drove significant revenue. IDTechEx’s latest report projects that these trends will help unlock an $80 billion market by 2036 across the U.S., Europe, China and other regions. Performing AI tasks on‑device is faster, often more energy‑efficient and reduces the need for large data transfers.
The reduced reliance on cloud connectivity also improves safety and convenience. These advantages are especially important for applications requiring consistent performance, such as autonomous vehicles and humanoid robots. For consumer devices, edge AI enables new features that manufacturers increasingly highlight as core selling points. IDTechEx expects consumer electronics to maintain more than 70% of the edge AI chip market throughout the next decade.
Smartphones Push Toward Smaller Nodes and Higher Compute
Reports that TSMC’s 2nm wafers may exceed $30,000 illustrate the rising cost of advanced chip manufacturing. Despite these increases, major smartphone makers like Apple and Samsung continue promoting AI‑focused devices powered by neural processing units. These chips enable on‑device tasks such as live call transcription, generative photo editing and personalized recommendations. IDTechEx estimates that premium smartphones accounted for roughly 25% of the 2025 market, with edge AI becoming a standard feature in this segment.
Mid‑range smartphones have also gained market share at the expense of budget models. Over the next decade, AI chips are expected to become common in mid‑tier devices by adopting architectures previously used in flagship phones. As demand for higher TOPS performance grows, manufacturers may increasingly rely on mid‑range models to balance rising hardware costs. Qualcomm continues to dominate high‑end platforms, while Mediatek remains strong in the lower mid‑range, and Apple and Google design their own chips manufactured by TSMC.
AI PCs Set to Become Standard by 2033
IDTechEx defines an AI PC as one equipped with an NPU or similar chip capable of at least 40 TOPS. New processors such as Intel’s Panther Lake and Lunar Lake meet this threshold, driving rapid adoption from 2026 onward. Lenovo stated at CES 2026 that it expects 80% of new PC sales to be AI PCs within three years. As of 2026, many PCs still lack dedicated AI hardware, but this gap is expected to close quickly.
By 2033, IDTechEx forecasts that nearly all new PCs will qualify as AI PCs. Growth will be driven not only by higher adoption rates but also by increasing AI compute per device. Rising foundry costs will further influence the market as manufacturers seek to balance performance and affordability. The report also examines edge AI chips in robotics, automotive systems and predictive maintenance sensors, offering detailed regional forecasts and technology benchmarks.
The rapid rise of edge AI is reshaping semiconductor strategy across the industry. As models grow more complex, companies are exploring hybrid approaches that combine on‑device inference with selective cloud processing. This balance could help manage costs while preserving the privacy and responsiveness that make edge AI attractive. The next decade is likely to see a wave of specialized architectures designed specifically for multimodal and generative workloads at the edge.
