Michael Burry, the legendary investor immortalized in “The Big Short,” has issued a stark warning about the artificial intelligence industry, predicting that the era of Big Tech’s massive profit margins is coming to an end due to AI’s capital-intensive demands. In a recent Substack exchange with tech podcaster Dwarkesh Patel, Burry identified return on invested capital (ROIC) as the critical metric investors should monitor when evaluating AI companies.
Burry argues that AI is fundamentally transforming tech giants like Microsoft, Google, and Meta from historically asset-light software companies into capital-intensive hardware operations. This shift requires massive investments in data centers, chips, and energy infrastructure to support AI applications, which Burry believes will inevitably drive down ROIC and pressure stock prices over the long term.
The investor’s concerns center on profitability: While AI may expand Big Tech’s addressable market, the enormous capital requirements could erode the efficiency that made these companies so profitable. “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 wrote.
Burry has compared the current AI boom to the late-1990s dot-com bubble, calling OpenAI “the Netscape of our time.” This reference is particularly ominous—Netscape’s 1995 IPO marked the beginning of dot-com mania, which spectacularly collapsed five years later. His hedge fund, Scion Asset Management, has taken significant short positions against AI darlings Nvidia and Palantir Technologies, according to September regulatory filings.
The warning comes as leading AI companies including OpenAI, Anthropic, Google, and Meta pour billions into infrastructure to support their energy- and data-intensive AI products. Despite attracting substantial debt and equity investment, these companies have yet to demonstrate significant profit returns on their AI offerings. In a January 2026 tweet, Burry predicted that “almost all AI companies will go bankrupt” and questioned whether a “Panic of 2026” or “2027” might materialize as AI spending gets written off.
Key Quotes
The measure to beat all measures is return on invested capital (ROIC), and ROIC was very high at these software companies. Now that they are becoming capital-intensive hardware companies, ROIC is sure to fall, and this will pressure shares in the long run.
Michael Burry explained why he believes AI is fundamentally changing Big Tech’s business model in a way that will hurt profitability. This quote captures his core thesis that the shift from software to hardware-intensive AI operations will erode the efficiency metrics that made tech stocks so valuable.
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 articulated the fundamental economic challenge facing AI companies in his Substack post. This statement cuts to the heart of concerns about AI profitability—that massive infrastructure spending may never generate adequate returns to justify the investment.
And still, return on investment will continue to fall, almost all AI companies will go bankrupt, and much of the AI spending will be written off. Will it be the Panic of 2026? 2027?
In a January 2026 tweet, Burry made his most dire prediction yet about the AI industry’s future. This quote reveals his belief that an AI bubble burst is not just possible but likely imminent, potentially triggering a market panic similar to previous tech crashes.
Our Take
Burry’s ROIC-focused critique represents a crucial counternarrative to AI hype, but the comparison to dot-com may be imperfect. Unlike 1990s internet companies with no revenue models, today’s AI leaders generate massive cash flows from existing businesses. However, his core insight about capital intensity is valid—AI’s infrastructure demands fundamentally differ from software’s scalability. The real question isn’t whether AI creates value, but whether returns justify the unprecedented capital deployment. History suggests Burry’s skepticism deserves serious consideration, yet AI’s transformative potential could also prove him wrong if productivity gains materialize at scale. The market’s challenge is distinguishing between genuine AI value creation and speculative excess—a distinction that may only become clear in hindsight. Investors should heed Burry’s warning to scrutinize capital efficiency metrics rather than blindly following AI momentum.
Why This Matters
Burry’s warning carries significant weight given his prescient prediction of the 2008 financial crisis, making his AI skepticism impossible for investors to ignore. His focus on ROIC as a key metric challenges the prevailing narrative that AI will automatically translate into profitable returns, forcing a more rigorous examination of AI economics.
The implications are profound for the entire tech ecosystem. If Burry is correct, the hundreds of billions being invested in AI infrastructure could represent one of the largest capital misallocations in tech history. This would affect not just tech giants but the entire supply chain—chip manufacturers, data center operators, energy providers, and thousands of AI startups.
For businesses and workers, a potential AI bubble burst could trigger widespread layoffs, failed startups, and a reassessment of AI adoption strategies. The shift from software to hardware-intensive models also signals a fundamental change in how tech companies operate, potentially ending decades of extraordinary profit margins that fueled innovation and job creation. Burry’s analysis suggests investors and business leaders should scrutinize AI investments through the lens of capital efficiency rather than growth potential alone.
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Source: https://www.businessinsider.com/michael-burry-big-short-key-metric-evaluate-ai-bubble-2026-1