- Combined device AI computing could surpass 1,000 TOPS by end of decade
- Smartphones, wearables and headphones become key distributed AI processors
- Average users probably carry hundreds of TOPS across multiple personal devices
Personal electronics is heading toward a point where combined AI computing on everyday devices rivals systems that once filled dedicated installations, a study suggests. Future source CE analysis tracking cutting-edge AI silicon trends through 2030.
The report examines how neural processors are spreading among smartphones, wearables, and audio devices, and how performance growth in these categories could change our expectations for personal computing power.
Smartphones are naturally at the heart of it all, with flagship chips from companies like Qualcomm, MediaTek, Samsung and Apple now offering up to 100 TOPS of neural processing capability.
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Increasing NPU performance
Predictions suggest that smartphones alone could nearly triple their NPU performance by the end of the decade.
Smartwatches are also no longer lagging behind smartphones, as dedicated neural processors are starting to appear in smartwatch chips, a step forward from earlier designs that relied heavily on shared processing blocks.
Smartwatch shipments reached around 94 million units worldwide in 2025, showing how widespread they are now.
Wireless headphones are also growing in popularity, with 360 million units shipped each year. Each earbud is equipped with its own chip, so the silicon footprint reaches well over 700 million units each year.
This distribution of AI-enabled hardware across multiple devices supports a broader vision often described as the “walking supercomputer.”
“These are not speculative scenarios,” said Simon Forrest, head of core technologies at Futuresource Consulting. “They are the logical product of chip design trends already in motion. Edge AI delivers real benefits in speed, privacy and cost, and traditional coded algorithms are replaced with machine learning versions that increase efficiency while expanding capabilities. For CE brands, understanding where AI computing is headed and what silicon enables is becoming a fundamental strategic necessity.”
Forrest told us it would be possible for someone in 2030 to carry personal electronic devices with a combined AI exceeding 1,000 TOPS (1 POPS), although it wouldn’t be common.
He said: “Futuresource’s forecast modeling shows that the average will likely be between 450 and 550 TOPS by the end of the decade, assuming a person carries a smartphone, a laptop, a smart watch, as well as smart glasses and perhaps another wearable device. Nonetheless, this is still a significant amount of distributed AI computing capacity positioned in and around the body.”
When combined with advances in laptops, smart glasses and wearable devices, the overall computing figure is increasingly widely discussed alongside the performance of a single device.
Marketing language often relies on TOPS numbers, even though raw numbers alone do not reflect actual performance. Architecture design, memory bandwidth, and software optimization remain equally important when translating theoretical computing into practical AI tasks.
Moving toward distributed processing across multiple devices reduces reliance on cloud services, improves response times, and keeps sensitive data closer to the device itself.
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