The industry is fixated on the GPU shortage, but the proliferation of AI agents will create massive demand for general-purpose compute, leading to a CPU bottleneck. As millions of agents perform tasks, the availability of CPU cores—not just specialized processors—will become the primary constraint on growth for compute providers.

While GPUs dominate AI hardware discussions, the proliferation of AI agents is causing a significant, often overlooked, CPU shortage. Agents rely on CPUs for web queries, data processing, and other tasks needed to feed GPUs, straining existing infrastructure and driving new demand for companies like Arm and Intel.

While GPUs train models, CPUs are essential for two key workloads: running reinforcement learning environments and executing the code generated by AI. This has created a massive, often overlooked demand spike, making CPUs a critical, sold-out component in the AI infrastructure stack and a hidden bottleneck.

The rise of agentic AI, which runs multiple parallel processes, is elevating the CPU's role from a secondary component to a critical 'conductor' for orchestrating GPU tasks, creating new demand and design considerations.

The focus on GPUs for AI overlooks a critical bottleneck: CPU shortages. AI agents require massive CPU power for non-GPU tasks like web queries and data prep. This demand is straining existing infrastructure and creating new market opportunities for CPU makers like ARM.

While GPUs are key for model training, the next AI wave of autonomous agents relies more on CPUs. The task of controlling and orchestrating multiple agents and tool calls is fundamentally a CPU-based process. This is creating a new hardware bottleneck and shifting focus to CPU manufacturers.

The current AI boom focuses on GPUs for "thinking" (Gen AI). The next phase, "Agentic AI" for "doing," will rely heavily on CPUs for task orchestration and memory for context, creating new investment opportunities in this previously overshadowed hardware.

The AI compute narrative is shifting from GPUs for training to CPUs for agentic workflows. This creates a massive new demand for processors to orchestrate tasks, manage inference, and coordinate data centers, directly fueling Intel's comeback and flipping the expected CPU-to-GPU ratio.

The AI narrative has focused on GPUs for training, but the proliferation of AI agents for task execution is creating a massive, overlooked demand for CPUs. This shift to inference and orchestration is reversing Intel's recent decline.