The AI Bubble: Structural Risks from Passive Investing and Speculative Accounting

The artificial intelligence (AI) sector has become a defining feature of global equity markets, with valuations soaring to unprecedented levels. However, beneath the surface of this growth lies a web of structural vulnerabilities. Passive investing strategies and speculative accounting practices are amplifying risks, creating a market environment ripe for correction. As investors reassess exposure to AI stocks, the interplay of these factors demands closer scrutiny.

Passive Investing and the Concentration of Risk

Passive investing has long been a cornerstone of modern portfolio management, but its role in the AI sector has exacerbated overvaluation. Automated index-tracking strategies have funneled capital into a narrow group of large-cap tech firms, particularly the so-called "Magnificent Seven." According to Ian Harnett, the AI trend has outperformed global equities six-fold in less than a decade, a classic hallmark of a bubble. This concentration has inflated valuations for companies like Microsoft and Apple, with their dominance in AI infrastructure driving a disproportionate share of market gains.

The rigidity of passive strategies compounds the problem. Unlike active managers, passive funds lack the flexibility to adjust to overvaluations, leaving them exposed to sharp corrections when sentiment shifts. A Bank of America survey found that 45% view the AI-driven market as the biggest tail risk for 2026. This sentiment is echoed by Goldman Sachs, which warns that while U.S. large-cap valuations remain below dotcom-era peaks, a slowdown in AI investment could still trigger market turbulence.

The structural risks extend beyond equity prices. AI infrastructure expansion is increasingly funded through debt rather than equity, echoing the precarious models of the dotcom era. This debt-driven growth raises questions about long-term sustainability, particularly as interest rates remain elevated.

Speculative Accounting and Inflated Valuations

Beyond passive investing, speculative accounting practices are further inflating AI valuations. One of the most contentious issues is the depreciation of AI hardware. Tech giants are depreciating AI chips over 5-7 years, despite their actual economic life being closer to 2-3 years. This discrepancy artificially inflates earnings, masking the true costs of AI investment. For example, Meta and Oracle could see earnings overstated by up to 20% by 2028 under this accounting method.

Revenue recognition strategies also contribute to overvaluation. The revised accounting standards (ASU 2025-06) for internal-use software and AI projects now allow firms to capitalize development costs earlier, provided management commits to funding. While this aligns with the iterative nature of AI development, it creates opportunities for earnings manipulation. Microsoft and Nvidia, for instance, have entered complex multi-element contracts that bundle software licenses, hardware, and support services. These arrangements obscure the true demand for individual components, making it harder to assess the sustainability of revenue streams.

The most extreme example is Palantir Technologies, which traded at a forward P/E ratio of 700x in late 2025 despite posting a 314% loss-to-revenue ratio for its ChatGPT product. Such valuations are disconnected from fundamentals, driven instead by speculative hype and circular financing structures where companies invest in each other's services.

Systemic Risks and Investor Caution

The combination of passive investing and speculative accounting has created a fragile ecosystem. Michael Burry has warned of a potential $176 billion loss across major AI firms between 2026 and 2028. His analysis highlights the risks of circular funding and misrepresentations in depreciation practices.

Market corrections are already emerging. In late 2025, AI-linked stocks like Nvidia and Palantir faced sharp sell-offs, with investors reassessing exposure to the sector. Technical indicators suggest further volatility is likely.

For investors, the lesson is clear: diversification across asset classes and geographies is critical to balancing growth potential with downside protection. As the Bank of America survey underscores, investors must remain vigilant, prioritizing transparency and fundamentals over hype.

Conclusion

The AI market's current trajectory mirrors historical bubbles, with passive investing and speculative accounting amplifying vulnerabilities. While the sector's long-term potential remains intact, the risks of overvaluation and systemic correction are real. As the Bank of America survey underscores, investors must remain vigilant, prioritizing transparency and fundamentals over hype. The next chapter of AI's story will likely be defined by how well markets adapt to these structural challenges.