The AI Compute Supply Chain

The rapid expansion of AI is creating a concentrated, multi-layered supply chain in which bottlenecks extend beyond chip design.

• The AI accelerator market is expected to exceed $400 billion by 2030, while NVIDIA is estimated to hold 80–90% of the accelerator market.
• More than 90% of advanced AI chips rely on TSMC’s manufacturing ecosystem, making wafer fabrication highly concentrated.
• Advanced packaging is a key constraint because CoWoS integrates GPU dies with high-bandwidth memory; NVIDIA is estimated to use about 60% of available CoWoS capacity.
• HBM can represent more than 50% of the cost of an advanced AI chip, and nearly all advanced HBM supply comes from SK hynix, Samsung, and Micron.
• The broader stack also depends on silicon, copper, gallium, germanium, cloud providers, networking, and other inputs that must scale together.

Takeaway: Investors should view AI as a supply-chain opportunity spanning design, manufacturing, packaging, memory, networks, and raw materials rather than as a single-chip market, while recognizing that concentration creates potential constraints.