TSMC Projects $1.5T Chip Market as U.S. Clears Nvidia H200 Sales to China

TSMC projects AI will dominate a $1.5 trillion chip market by 2030 as the Trump-Xi Beijing summit produces a reported H200 clearance for 10 Chinese firms.

🗄️ TSMC Projects AI Will Drive Global Chip Market to $1.5 Trillion by 2030

Decoded: TSMC Deputy Co-COO Kevin Zhang announced at the company's 2026 Taiwan Technology Symposium on May 14 that AI is projected to drive global semiconductor output to $1.5 trillion by 2030 — nearly double the current market size. Speaking in Hsinchu, Zhang said AI and high-performance computing will account for 55% of that market, displacing smartphones — which have anchored semiconductor demand for a decade — to a 20% share. The global foundry sector alone is expected to reach $500 billion by 2030, up from roughly $130 billion today. Zhang projected demand for AI accelerator wafers to increase 11-fold between 2022 and 2026, and noted TSMC is expanding its CoWoS advanced packaging capacity at an accelerated pace to meet that demand. He described AI as potentially "the most important and influential technology in human history." TSMC separately projects compound annual growth of 70% for its most advanced process nodes between 2026 and 2028. (Focus Taiwan/CNA, Reuters, Digitimes, May 14, 2026)

Why it matters: TSMC's official forecast assigns a concrete number — $1.5 trillion — to the AI semiconductor wave and confirms that chips, not software, remain the binding constraint on AI growth. The 55% AI and HPC share projection signals a structural shift: volume smartphone geometry is being replaced by power-dense accelerator wafer production. For TSMC (TSM), a 70% CAGR on advanced nodes means its most profitable revenue stream is compounding faster than any prior technology cycle. Advanced packaging — CoWoS — remains the near-term bottleneck; TSMC's accelerated expansion is the primary reason Nvidia's Blackwell rack systems can ramp at the pace they are.

🏛️ U.S. Reportedly Clears Nvidia H200 Sales to 10 Chinese Firms at Trump-Xi Summit

Decoded: The U.S. government is clearing Nvidia H200 AI chip sales to approximately 10 Chinese companies as part of the ongoing Trump-Xi summit in Beijing, CNBC reported May 14 — the most significant relaxation of AI chip export controls since restrictions were first imposed in 2022. Trump and Xi met at the Great Hall of the People on Thursday; Xi warned Trump that disputes over Taiwan risk "clashes and even conflicts," while the two sides discussed tariffs, semiconductor restrictions, rare earth exports, and a proposed bilateral AI dialogue channel, according to Reuters and The Guardian. Goldman Sachs analysts said they expected China to commit to purchases of U.S. agricultural products, energy, and Boeing aircraft in exchange for avoiding further tariff escalation — but did not expect a sweeping deal. A Barclays analyst described compute access as "the greatest bottleneck in AI" and called Nvidia chip access "the most important competitive arena" between the two countries. Nvidia CEO Jensen Huang, who joined Trump's delegation for the Beijing trip, has lobbied both governments for over a year to restore H200 access. (CNBC, Reuters, The Guardian, May 14, 2026)

Why it matters: A U.S. clearance of H200 sales to Chinese firms — even limited to 10 companies — reverses the core restriction that has blocked Nvidia's China business since 2023. China represented approximately 20% of Nvidia (NVDA) data center revenue before export controls; even partial restoration would add billions in annual revenue while reducing concentration risk in U.S. hyperscalers. The proposed bilateral AI dialogue channel would create the first formal mechanism for coordinating AI development norms between Washington and Beijing — a structural step that matters beyond trade, as it is a prerequisite for any future agreement on autonomous weapons, AI infrastructure standards, or AI-enabled surveillance. Chinese technology equities were expected to rally on any positive signal from the summit.

Stay decoded. See you tomorrow.

— The Get AI Decoded Team