URGENT UPDATE: Investor Michael Burry, renowned for predicting the 2008 financial crisis, has raised alarms about the impact of artificial intelligence (AI) on Big Tech profitability. In a newly published Substack post, Burry claims that the AI boom may transform giants like Microsoft, Google, and Meta into less profitable entities.
Burry’s analysis indicates that returns on invested capital (ROIC) in these companies are declining as they shift from asset-light models to capital-intensive operations. He states that the era of transforming minimal investments into massive profits is coming to an end due to AI.
According to Burry, the critical metric for investors should not be revenue growth or market size, but rather ROIC. “The measure to beat all measures is return on invested capital (ROIC),” he emphasized. “Now that they are becoming capital-intensive hardware companies, ROIC is sure to fall, and this will pressure shares in the long run.”
In this context, Burry compares the current AI landscape to the late-1990s dot-com bubble, noting that despite the expansive market AI promises, the transition could lead to significant declines in stock prices over the coming years. His hedge fund, Scion Asset Management, has already made substantial bets against AI companies like Nvidia and Palantir Technologies, as revealed in a regulatory filing last September.
Leading AI firms, including OpenAI, Anthropic, and others, are heavily investing in infrastructure to support their data-intensive projects. However, the lack of significant profit returns on these investments has sparked concerns from investors like Burry, who warn that the AI sector risks becoming a bubble poised to burst.
“At some point, this spending on the AI buildout has to have a return on investment higher than the cost of that investment, or there is just no economic value added,” Burry asserted in his Substack piece.
Burry’s warnings resonate particularly as companies scramble to enhance their AI capabilities. The rapid shift toward more capital-intensive models raises questions about the sustainability of these investments and the potential for a major market correction.
As the AI landscape continues to evolve, stakeholders are left pondering the future of profitability in Big Tech. Burry’s insights suggest a turbulent road ahead, with many AI companies potentially facing bankruptcy if returns do not improve.
Investors and market watchers are urged to keep a close eye on these developments, as the ramifications could be felt across the tech sector for years to come. Will this lead to a “Panic of 2026” or “2027”? Only time will tell, but the signs are becoming increasingly alarming.
For ongoing updates on this developing story and its impact on the tech industry, stay tuned.
