The Benefits of AI PCs Go Beyond the NPU

Numerous organizations are moving artificial intelligence workloads and capabilities from the cloud to their own PCs. As this shift takes place, IT teams are looking to deploy computers that can handle intensive AI workloads.

Many observers associate neural processing units with AI workloads, but the truth is that all three engines in a PC — NPUs, central processing units and graphics processing units — enhance its ability to run AI workloads locally.

It’s helpful to understand how these chips work together to deliver AI experiences and to know which platforms support the AI tools that users need. For instance, Intel’s higher-end Lunar Lake processors, released in September 2024, are built with powerful processors, long battery life, RAM that can handle multitasking and exceptional core performance for advanced AI features. Lunar Lake also supports Copilot+ PC, the version of Microsoft’s AI assistant that runs on the device. At a lower price point, the Arrow Lake platform still has the NPU, GPU and CPU trio to run AI workloads while supporting a cloud-based version of Copilot.

Intel designed our newest platforms to deliver AI, improved security and faster performance.

Getting a great AI experience on a PC requires the right platform to balance various use cases and software requirements. The NPU is the engine most users think of, but that doesn’t mean it’s the best engine for every AI workload. Unlike some platform manufacturers, Intel infuses AI capabilities into all three engines. They each play a part in AI experiences, with specific engines best suited for particular types of AI capability. 

NPUs are ideal for energy-intensive workloads because they can deliver high performance while consuming less power. GPUs are more powerful than NPUs but consume a lot of energy. They’re perfect for smaller AI tasks that require fast answers or that need to happen in parallel with other applications, such as an AI-enhanced feature on a collaboration platform. CPUs are similar but best suited for single tasks requiring high-speed performance.

Software makers determine which engine an application will run on; in some cases, certain functions may run on one engine while others run on a different engine. For example, a software manufacturer may anticipate that most users will be relying on plugged-in power to use an application. That makes battery conservation less important, so it may design the application to run on the GPU for fast performance at the cost of higher energy consumption.

Intel has also collaborated with our security partners, including CrowdStrike, to enhance AI-enabled threat detection and response capabilities on endpoints. The Lunar Lake platform generates more granular telemetry about devices and usage, creating profiles so the security software can use AI to identify threats more quickly. This capability is built into the platform, optimizing the security tools that run on these PCs.

Some organizations are holding off on making the switch to AI PCs, but investing in these capabilities now offers several benefits. Employees get the advantage of AI at their fingertips, now easily integrated into everyday tasks. The performance is faster and more personalized because the AI is on the PC, not in the cloud. AI PCs also make sense for financial institutions and government agencies that cannot use cloud-based AI tools because of data privacy concerns. With exceptional performance, security protections and robust user experience, AI PCs are quickly becoming the standard.