AI Chip Shortage Triggers Inflation: When Innovators' Appetite Exceeds Factory Capacity

Event Background

Goldman Sachs economist Megan Peters published research indicating that the artificial intelligence wave will directly push up U.S. inflation. The core logic is not that AI causes "universal price increases," but rather that certain critical production inputs—particularly memory chips and processors—face supply shortages due to surging demand, driving prices upward.

According to Goldman Sachs estimates, by the end of 2026, AI's impact on U.S. core PCE inflation (the Federal Reserve's preferred inflation metric) could reach 50 basis points (0.5%)—more than double earlier annual forecasts.

Why Is This Happening?

Steep Demand Curve Shift

Large-scale commercialization of AI training and inference has suddenly boosted demand for high-end chips. From early 2024 through mid-2026, data center purchase orders for GPUs, tensor processing units (TPUs), and high-bandwidth memory (HBM) have grown over 300%.

NVIDIA's 2025 revenue already exceeds the combined totals of Intel and Qualcomm, illustrating this point. Yet when demand explodes, supply cannot respond synchronously.

Hard Constraints in the Supply Chain

Advanced chip manufacturing involves multiple bottlenecks: extreme ultraviolet (EUV) lithography equipment, purified silicon ingots, rare earth element refinement, and more. TSMC and Samsung's advanced process capacity requires 3-5 years from planning to mass production. This means that even if AI chip demand was foreseen in 2024, it cannot fully meet the 2026 peak today.

The result: supply shortage → price increases → data center cost rises → cloud computing fees rise → downstream enterprise costs increase → final consumer prices rise.

Why Is U.S. Impact Greatest?

Goldman Sachs' observation goes deeper: why will U.S. inflation impact exceed other regions globally?

1. Fastest AI Commercialization Speed

American tech giants (OpenAI, Google, Meta, Microsoft, and others) control over 70% of global large language model training workloads. These well-capitalized companies have the strongest incentive to scramble for chips.

2. Pricing Power Structure

American enterprises and cloud service providers (AWS, Azure, Google Cloud) control 60% of the global cloud computing market. When their costs rise, they have the most room to pass price increases downstream to customers.

3. Scope of Consumer Price Statistics

PCE inflation statistics cover all consumer-related services—including subscription software, online advertising, and AI application services. Price increases in these services transmit most sensitively through the U.S. economy.

Timeline and Policy Implications

Goldman Sachs' estimates show this inflation impact will peak in 2026-2027, then gradually ease as capacity expands. But the issues are:

• Federal Reserve's easing cycle will be interrupted: If core PCE inflation suddenly rises 50 basis points, even temporarily, it will reinforce the central bank's concern about "economic overheating," potentially triggering a repricing of rate hike expectations.

• Geopolitical risk: Chip capacity is highly concentrated in Taiwan (TSMC) and South Korea (Samsung, SK Hynix). Any cross-strait tensions will intensify supply uncertainty and further drive up prices.

• Corporate profit margins compressed: If cloud costs rise indefinitely while end consumers' willingness to pay for AI applications remains limited, profit margins for AI startups and application-layer companies will erode.

Historical Analogies

This is not the first time a technology wave has triggered specific commodity price spikes.

• 2017-2018 Bitcoin mining boom → GPU prices soared 2-3x → gaming card hardware shortages → end consumer gaming hardware costs rose
• 2010-2015 smartphone explosion → touchscreen and lithium battery demand surged → supply shortages → smartphone and tablet prices rose
• 1970s oil crisis → chemical and transportation costs skyrocketed → global inflation

The difference is that AI chip shortages have broader coverage—it affects not just specific consumer categories, but the foundational costs of the entire cloud economy.

Conclusion

Goldman Sachs' research points to a core principle: when the speed of demand curve movement exceeds the supply curve's adjustment capacity, non-linear price increases occur and eventually transmit to macro price levels.

AI's commercialization is not only a technological revolution but also a resource allocation battle. Before supply chains catch up with demand, inflation will be an accompanying phenomenon.