AI-related stocks experienced a significant slide on Monday, September 14, 2026, after leaders from prominent AI companies, including Anthropic CEO Dario Amodei and OpenAI CEO Sam Altman, publicly advocated for a slower pace in AI development. Amodei penned an essay calling for this slowdown, which was subsequently supported by Altman and other tech figures like Elon Musk. This call to action follows escalating concerns about the risks posed by rapidly advancing AI capabilities, highlighted by recent resignations and warnings from researchers about the potential dangers of uncontrolled AI development.
The market reaction was swift and widespread. In Asia, major South Korean chipmakers SK Hynix and Samsung Electronics saw their shares fall by more than 6% and 4% respectively. SoftBank, a key investor in OpenAI, experienced a sharp 10% decline in Japan. European semiconductor companies also felt the impact, with ASML dropping over 4%, Nokia down around 5%, and Infineon losing more than 6%. Companies tied to data center infrastructure, such as Siemens Energy and Schneider Electric, also saw their stock prices decrease. In U.S. premarket trading, memory chipmaker Micron fell by approximately 5%, Intel dropped nearly 6%, and Nvidia was down over 2%. Hyperscalers like Microsoft, Amazon, and Alphabet also registered slight declines.
Investors are expressing anxiety that an industry-wide slowdown in AI development could create ripple effects across the technology sector, potentially curbing the adoption of new AI solutions and impacting the substantial capital expenditure allocated to build out computing power. Zoe Gillespie, a senior director at RBC Brewin Dolphin, noted that the recent equity market rally has been heavily reliant on anticipated AI growth and productivity gains, and any derailment of this trajectory could negatively affect future equity performance. Ben Barringer, global head of technology research at Quilter Cheviot, however, suggested that while training and rollout might slow, the demand for AI inference (running AI applications) still far outstrips supply, indicating that company revenues might not be significantly impacted despite a slower pace of development. Amodei and Altman clarified that "pacing" does not mean "stopping" AI progress, but rather making it slower than it could otherwise be, with an emphasis on safety and monitoring.
