Apple is reshaping the technical heart of its phones, a move that company executives and industry analysts say could accelerate a shift toward deeper on‑device artificial intelligence. According to CNBC, Apple will take control of all core chips in the forthcoming iPhone Air and will deploy an A19 Pro system‑on‑chip that integrates neural accelerators directly into each GPU core, a structural change aimed at prioritizing AI workloads.

The new architecture was on display alongside the iPhone 17 Pro during Apple’s presentation at Apple Park on September 9, 2025, where the company highlighted enhanced 3D rendering and real‑time processing capabilities attributed to the A19 Pro. The chip features six GPU cores equipped with dedicated neural accelerators, an arrangement Apple says increases parallel compute power for machine‑learning tasks. “It’s actually positioned in concert with where the system on a chip, the A19 Pro is positioned,” Kaiann Drance, Apple’s vice president of worldwide iPhone product marketing, said at the event.

Embedding neural accelerators across GPU cores departs from the more common design in which a single, centralized neural engine handles inference. By dispersing AI hardware across multiple graphics cores, Apple aims to lower latency for tasks such as image synthesis, augmented reality overlays and computational photography, enabling features to run predominantly on the device rather than relying on cloud servers. That, in turn, promises privacy benefits because sensitive user data no longer needs to be routinely uploaded for processing.

The decision also has clear commercial and strategic dimensions. Bringing design control of all core chips for the iPhone Air in‑house reduces Apple’s reliance on third‑party suppliers for critical silicon, a point that could change dynamics with longstanding partners including Qualcomm and Broadcom. Analysts say the move could accelerate a trend in which Apple internalizes more of the smartphone value chain, from chip design to modem integration, giving the company tighter performance and feature cohesion but also concentrating risk.

Technical trade‑offs remain. Distributing neural accelerators can increase thermal density and complicate power management, forcing Apple’s engineers to balance peak performance with battery life and device temperature. Developers will also face new constraints and opportunities: optimizing apps to tap many small neural blocks is a different programming model than leveraging a single large neural engine, creating a transitional period for toolchains and frameworks.

There are regulatory and ethical considerations as well. Greater on‑device intelligence may reduce data flows to the cloud, a potential win for user privacy, but it could also make opaque automated decision‑making harder to scrutinize. As smartphones grow more capable of producing realistic synthetic content, questions about misinformation, consent and content provenance will intensify.

For consumers, the immediate promise is snappier, more capable phones that can run sophisticated AI features without an internet connection. For competitors and regulators, Apple’s step to control more of the silicon stack signals a new chapter in the race for compute at the edge — one that will shape how devices balance power, privacy and performance in the years ahead.