An "AI PC" is a laptop with an NPU, a neural processing unit designed to run AI tasks efficiently on the device instead of in the cloud. Microsoft's Copilot+ PC programme set the bar that most of the market now follows: an NPU capable of at least 40 TOPS (trillion operations per second). Apple's M-series Macs have had their own Neural Engine for years.
What the NPU actually does
- Runs small AI models locally, like background blur, live captions, transcription, image tools and on-device search, using far less battery than the CPU or GPU.
- Keeps data on the device, which matters for privacy-sensitive work.
- Frees up the CPU and GPU for everything else you're doing.
What it doesn't do: run the biggest frontier models. ChatGPT-class assistants still run in the cloud.
Who benefits now
Clear yes:
- People who live in video calls: better noise suppression and captions without draining the battery.
- Anyone handling sensitive documents who wants AI features that stay on the device.
- Developers experimenting with small on-device models and embedding models.
Can wait:
- Typical office work, browsing and email. A good non-AI laptop is still fine.
- Heavy local model work, where a strong GPU or Apple's unified memory matters more than NPU TOPS.
A developer's take
For web development, RAM and a fast SSD still matter more than the NPU. I'd prioritise at least 16 GB of RAM (32 GB if you run Docker and local models), then treat the NPU as a bonus. Where NPUs get interesting is on-device AI in products: smaller models running in the browser or on a phone, so features work offline and cost nothing per request.
Building on-device and cloud AI
At NextGen Fusion, our AI and web development company in Lucknow, we decide per feature whether AI runs in the cloud, in the browser or on the device, based on cost, privacy and speed.
