AI workloads are becoming prevalent across every aspect of our work and our personal lives. AI is transforming business productivity, public and private research, analytics, content creation, and so much more. Given this explosion of AI workloads, it’s no surprise that we’re now seeing AI PCs on the market with hardware and software designed specifically to accelerate performance for AI-based applications.
If you’re evaluating AI PCs for purchase, it can be challenging to know which ones are best suited to your particular use cases. This is particularly true if you’re an IT decision-maker (ITDM) responsible for conducting a PC refresh for your organization. How can you determine which PCs will meet the needs of your productivity workers by supporting productivity assistants and enhancing collaboration? Which ones are best for handling AI-based analytics, video editing, or software development? And which ones can best support AI-based security features without dragging down performance?
Benchmarks can be useful, but traditional benchmarks aren’t focused on AI workloads. New benchmarks are in development, but they might take time to reach the levels of maturity needed to offer a reliable indication of AI performance across real, application-based use cases. In the meantime, other approaches to evaluating AI performance might be more useful, depending on your specific workloads and needs.
In this paper, sponsored by Intel, Prowess Consulting helps unravel the jargon, explains what common benchmarks actually measure, and steps through other considerations needed to make an effective AI PC purchase for yourself or your organization.
