Jensen Huang keeps saying the next era of computing will be built around “AI factories” but every agentic workload creates a massive amount of CPU-bound work around the GPU.
The best way to think about this is the GPU will still continue being the engine but CPU will now become the traffic controller. If AI agents are going to run inside enterprises all day across millions of workflows then the CPU layer becomes a much more important part of the AI infrastructure stack.
1.
AMD is the cleanest way to play the agentic AI CPU bottleneck through EPYC where they just posted record Q1 data center revenue of $5.8B (+57% YoY) and biggest gem was AMD capturing ~46% of server CPU revenue despite only 27% unit share (AMD is winning higher-value server CPU dollars that AI infrastructure actually needs).
CEO Lisa Su also raised the server CPU TAM forecast to $120B+ by 2030, guided Q2 server CPU revenue to grow more than 70% YoY and layered on the $Meta Platforms, Inc.(META)$ 6GW Instinct deal which also makes Meta one of the first customers for next-gen Venice and Verano EPYC processors. Intel's Diamond Rapids was also delayed to mid-2027 which means AMD has effectively zero competitive response during the steepest part of the agentic AI buildout.
2.
Arm is the most interesting of the three because the story is no longer just “Arm collects royalties” since they're now becoming a direct silicon supplier through the Arm AGI CPU which it says can deliver more than 2x performance per rack versus x86 platforms while reducing AI data center capex by up to $10B per gigawatt.
Arm said customer demand for the AGI CPU has already reached more than $2B across FY27 and FY28 which now gives Arm two ways to win from the same bottleneck: royalties on custom hyperscaler CPUs and direct sales into AI infrastructure.
3.
Intel is the most controversial of the three because the market still treats it like a permanent AI-cycle loser but agentic AI could lift every credible x86 supplier and Intel now has two ways to capitalize on it: product and foundry.
On the product side, AI-driven businesses now account for 60% of total revenue and are growing 40% YoY while Xeon 6 was selected as the host CPU for $NVIDIA(NVDA)$ DGX Rubin NVL8 systems giving Intel a role inside the next generation of Nvidia AI deployment.
On the foundry side, Intel agreed to manufacture chips designed by $Apple(AAPL)$ while Nvidia's $5B investment and commitments from Musk-linked companies validate Intel's manufacturing roadmap at the exact moment AI infrastructure needs more advanced domestic chip capacity.
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