Although enterprise adoption of AI PCs took a hit this year due to geopolitical and macroeconomic headwinds, demand for AI-enabled devices continues to grow.
AI PC shipments will reach 31% this year, up from 15% in 2024, according to Gartner estimates. The Windows 10 end-of-support deadline in October also fueled global PC shipment growth, which increased 8.2% year over year, the analyst firm found.
The core value proposition of AI PCs is enabling AI experiences – such as running machine learning algorithms or processing information from large language models – directly from the device, said Forrester VP and Principal Analyst Michele Pelino.
An AI PC is a device embedded with AI chips and algorithms designed to improve the AI workload experience across central, graphics and neural processing units, according to Forrester’s definition.
Top PC manufacturers including Intel, Microsoft, HP and Lenovo have been steadily adding AI computing capabilities to devices. Intel stacked its AI processor portfolio last year, while HP anticipates AI PCs will make up more than half of its PC business by 2027.
AI PCs can benefit an enterprise by providing a pathway for remote and hybrid employees to work directly with AI tools, Pelino said during a virtual session from Forrester’s Technology & Innovation Summit on Monday. Other benefits include bolstered security, optimized battery performance and energy efficiency.
However, enterprises don’t need AI PCs to run generative AI applications on a computer because a lot of processing is done in the cloud, Pelino said. That means companies will need to be selective about which employees receive an AI PC.
Employee expectations for running AI on devices are rising and 47% of IT organizations plan to increase their PC refresh rates in 2026 to deploy AI PCs with NPUs, Pelino said.
As IT leaders consider PC refresh cycles and how employees might benefit from an AI PC, Pelino recommended taking three steps for AI PC deployment within an enterprise:
1. Selectively identify individuals for AI PC deployments.
Initial AI PC deployments should focus on employees who would benefit most from an on-device AI function, Pelino said.
That could include IT developers automating code production, marketing teams creating AI-generated campaigns or operations teams streamlining processes with AI-enabled automations, Pelino added.
“Segments of the employee population could certainly benefit from using AI PCs, but not everybody is going to need one,” Pelino said.
2. Showcase use cases requiring on-device AI functionality.
Use cases for AI PCs range from real time video analysis to on-device LLM applications, Pelino said.
“Make sure you understand the value proposition, the types of AI applications, functions and features that are going to be most valuable to those end users and showcase them so they understand the real benefits that they can achieve using these devices,” Pelino said.
3. Quantify AI PCs’ return on investment.
IT teams will need to identify employee productivity benefits as part of the ROI for AI PCs, Pelino said.
Justifying device costs also means determining ongoing support the IT team will need to provide for AI PCs in the context of other devices within the organization, Pelino added.
