AI initiatives are accelerating across state and local government, but many agencies are still constrained by limited staff, tight budgets, and rising expectations for secure, responsive services. At the same time, cloud costs and data governance requirements make it harder to scale AI in a way that is both affordable and defensible. This thought leadership paper from Government Technology, in partnership with HP Inc., explains what AI PCs are, why onboard neural processing units matter, and how agencies can run more AI workloads on the device to improve performance, reduce costs, and keep sensitive data closer to where it is created.

AI PCs are designed to handle more AI processing locally, instead of pushing every task to the cloud. For government teams, that shift can translate into faster everyday work, better user experiences for staff in the field, and a clearer path to scaling AI without adding unnecessary complexity. The paper also shares practical considerations for planning and deployment, so you can move from curiosity to an implementation roadmap.

In this paper, you will learn:

• What defines an AI PC and how an NPU supports faster, more efficient AI tasks
• How shifting workloads from the cloud to the endpoint can help reduce costs and latency
• Where on device AI can strengthen security and data handling for government environments
• Real public sector use cases that support frontline staff with faster insights and easier access to information
• How to identify the best starting points, including which roles and workflows benefit most
• Best practices for deployment planning, change management, and driving adoption across teams

Download the paper to evaluate where AI PCs can deliver measurable impact across your agency.