Global AI stocks fell sharply on Monday as concerns over the risks of rapidly advancing artificial intelligence began to weigh on investor confidence. The sell-off followed warnings from senior executives at some of the world’s leading AI companies, who called for greater caution as increasingly powerful systems raise concerns about cybersecurity, misuse, financial exposure and potential threats to society.
The market reaction came after Anthropic CEO Dario Amodei urged AI companies to slow the pace at which they develop increasingly capable models. His warning was supported by OpenAI CEO Sam Altman and xAI chief Elon Musk, adding weight to growing calls for the industry to take a more measured approach to AI development. The comments have added a new layer of uncertainty to a sector that has become one of the biggest drivers of global stock market gains since the launch of ChatGPT in 2022.
Amodei argued that the risks associated with increasingly capable AI systems are becoming difficult to ignore. He wrote that within six to 12 months, AI agents “could be capable of taking over the entire internet potentially causing hundreds of billions of dollars in damage.” The warning highlights growing concern that autonomous AI systems could eventually operate across digital networks with limited human intervention, creating risks that would be difficult to contain once an attack or misuse begins.
Anthropic has also reported cases in which its Claude AI models were allegedly used in activities including weapons development, cyber operations, surveillance and fraud. Such incidents have intensified the debate over how AI companies should balance technological progress with safeguards designed to prevent malicious use.
The concerns have also emerged from within the AI industry itself. Anthropic researcher Jacob Coxon resigned while expressing fears about the possible consequences of increasingly powerful artificial intelligence. His departure added to a growing sense that some people working directly in AI development are becoming increasingly uncomfortable with the speed at which the technology is advancing.
Altman has similarly acknowledged the seriousness of the issue. In an interview, the OpenAI chief described the possibility of human extinction caused by AI as “unacceptable”. His comments were particularly significant because OpenAI has been among the companies pushing aggressively to develop more advanced AI systems and expand their commercial applications.
The uncertainty surrounding AI development was reflected almost immediately in financial markets. U.S. Nasdaq futures declined, with technology and semiconductor stocks among the biggest losers. Nvidia, one of the most important companies in the AI hardware ecosystem, fell around 3%, while Advanced Micro Devices dropped about 5.7%. SpaceX also declined, while major technology companies such as Meta and Amazon recorded losses of more than 1.4%.
The weakness was not limited to the United States. European technology stocks fell sharply, with ASML, a major supplier of semiconductor manufacturing equipment, dropping about 5.8%. Infineon declined more than 8%, while Siemens Energy, which has benefited from the growing demand for infrastructure linked to data centres and electricity generation, also suffered a significant decline.
Asian markets were affected as well. SoftBank, a major investor in OpenAI, fell as much as 13.2%. Taiwan Semiconductor Manufacturing Company slipped, while South Korea’s SK Hynix declined more than 6%. The broad-based selling showed how closely global financial markets have become tied to expectations surrounding AI investment.
For investors, the concern goes beyond whether AI companies will continue developing new models. The industry has committed enormous amounts of money to data centres, advanced chips, electricity supplies and computing infrastructure. Much of that expansion has involved borrowing, long-term contracts and complex financing arrangements.
That creates a potential financial problem if the pace of AI development or demand for computing power slows. Infrastructure projects cannot necessarily be scaled back as quickly as software development. Data centres still require electricity, leases and debt payments even if companies reduce their spending or expected AI revenue fails to materialize.
“If the AI race slows materially, the key question becomes: who pays for all that infrastructure? The leases, debt and power commitments remain even if expected compute demand and revenue growth slow. And that could bring credit risk increasingly into the AI story,” said Ipek Ozkardeskaya, senior analyst at Swissquote.
The issue is particularly important because AI-related investment has become a major component of expectations for technology companies and semiconductor manufacturers. Investors have poured money into companies connected to AI on the assumption that demand for computing power, cloud services and advanced chips will continue rising rapidly. A significant slowdown could therefore affect not only AI laboratories but also the much larger network of companies supplying them.
The debate has also moved beyond financial markets. In several parts of the United States, communities have objected to the construction of large data centres because of their electricity and water requirements. At the same time, cyberattacks involving AI tools have increased concerns about how easily sophisticated technology can be misused.
