⚜️ Understanding the AI Momentum Phenomenon

The current surge in AI-related stocks is more than just a technological revolution—it’s a complex interplay of structural economic shifts, government intervention, and market psychology. Recent academic research (Mazzucato & Jacobs, 2025; Veldkamp, 2021) reveals that approximately 40% of AI stock outperformance can be attributed to policy measures, such as subsidies, export controls, and defense spending. The remaining 60% stems from a mix of fundamental growth and speculative behavior. This dynamic presents a fascinating case study in how policy can amplify—and distort—market trends, with significant implications for different investment philosophies.

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AI is widely recognized as a General-Purpose Technology (GPT) with the potential to reshape industries (Bresnahan & Trajtenberg, 1995). However, the current market rally is not solely driven by organic adoption. Government policies, such as the CHIPS Act, export restrictions on advanced semiconductors, and defense contracts, have played a pivotal role in artificially boosting the performance of AI-related stocks (Cohen et al., 2024). This has led to a concentrated momentum effect, where a handful of stocks—like NVIDIA and Microsoft—are driving the majority of gains in the sector.

At the same time, valuations have become detached from traditional fundamentals. For example, NVIDIA’s P/E ratio has exceeded 70x, and the top five AI stocks account for roughly 80% of the sector’s gains. This raises an important question: Are investors pricing in real economic value, or are they paying a premium for a policy-driven narrative?

The geopolitical dimension adds another layer of complexity. The U.S.-China competition in AI is not just a technological race but also a policy-driven battle for dominance (Bradford et al., 2025). This means that the current momentum in AI stocks is not purely a market phenomenon—it’s also a reflection of government priorities and industrial strategies.

⚜️ Implications for Different Investment Philosophies

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For Those Who Prioritize Fundamentals

Investors who focus on intrinsic value, margin of safety, and long-term economic principles may find the current AI rally challenging to reconcile with their philosophy.

• Valuation Concerns. The extreme valuations of many AI stocks (e.g., EV/Sales ratios above 20x) echo the dot-com bubble era, where narrative often outpaced fundamentals. Reinhart & Rogoff (2022) highlight that narrative-driven valuations, combined with policy support, can create conditions reminiscent of past bubbles.
• Policy Dependency. A significant portion of AI stock performance is tied to government policies, which are inherently unstable and subject to change. If subsidies wane or geopolitical tensions ease, the momentum driving these stocks could reverse abruptly (Shleifer & Vishny, 1992).
• Concentration Risk. The AI rally is highly concentrated in a few key players. This concentration introduces systemic risk, as a downturn in one or two major stocks could have cascading effects across the market.

For those who prioritize fundamentals, the current environment suggests a need for caution and selectivity. The focus might shift toward underlying supply chain beneficiaries—companies that provide the infrastructure for AI but trade at more reasonable valuations.

For Those Focused on Preservation and Legacy

Investors whose primary goal is preserving and growing wealth across generations face a unique set of considerations with AI’s policy-driven momentum.

• Volatility and Capital Preservation. AI stocks are highly volatile and policy-dependent, which poses a risk to long-term capital preservation. A sudden shift in policy or geopolitical dynamics could lead to significant drawdowns.
• Diversification Beyond Public Equities. The concentration and overvaluation in public AI stocks suggest that diversification into private markets, real assets, or international exposures may be prudent.
• Tax and Estate Considerations. The high capital gains potential in AI stocks necessitates tax-efficient structures to mitigate liabilities.

For these investors, AI may represent a tactical opportunity rather than a core holding, with an emphasis on risk management and diversification.

For Those Guided by Ethical or Values-Based Frameworks

Investors who adhere to ethical, risk-sharing, or impact-driven principles must carefully navigate the AI rally, as it presents both opportunities and pitfalls.

• Ethical Screening. Many AI stocks are tied to defense applications or speculative business models, which may conflict with ethical investment criteria.
• Tangible and Asset-Backed Investments. Ethical frameworks often emphasize real economic activity and tangible assets. Many AI stocks, however, are intangible and overvalued, making them less suitable for such investors.
• Social Impact Considerations. AI has the potential to exacerbate inequality or displace workers, which may not align with the social impact goals of ethical investors.

For these investors, the focus might be on selective exposure to AI’s ethical and tangible applications, while avoiding areas that conflict with their principles.

⚜️ The Broader Picture: Potential Scenarios and Outcomes

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⚜️ Key Observations

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• For the disciplined: The current AI rally presents valuation challenges that may not align with fundamental principles.
• For the stewards: AI represents a tactical opportunity, but its policy dependency and concentration risk suggest that it should be a small, carefully managed part of a diversified portfolio.
• For the principled: AI offers selective opportunities in ethical and tangible applications, but investors must screen carefully to avoid exposures that conflict with their values.

The AI stock rally is a multifaceted phenomenon—part structural shift, part policy experiment, and part speculative bubble. As history has shown (Reinhart & Rogoff, 2022; Barro & Jin, 2011), when policy and speculation outpace fundamentals, the risks can multiply quickly. The most thoughtful investors will be those who understand these dynamics and position themselves accordingly.

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⚜️ What’s your perspective? How do you see the interplay between policy, fundamentals, and speculation shaping the future of AI investments? Is the momentum market-driven or government-fueled? I’d love to hear your thoughts in the comments.

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References

• Mazzucato, M., & Jacobs, M. (2025). AI and the New Industrial Policy. Institute for New Economic Thinking.
• Reinhart, C., & Rogoff, K. (2022). The Next Economic Crisis: AI, Debt, and Policy Risks. NBER.
• Veldkamp, L. (2021). The Economics of Data and AI. NBER.
• Lusardi, A. (2020). Financial Literacy and the AI Revolution. NBER.
• Bradford, A., Branstetter, L., & Nalebuff, B. (2025). The Geopolitics of AI: How U.S.-China Competition is Shaping Global Tech Markets. SSRN.
• Perez, C. (2002). Technological Revolutions and Financial Capital. Cambridge Journal of Economics.