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How long can the AI boom continue at this pace?

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  Published in Stocks and Investing on Thursday, October 9th 2025 at 13:31 GMT by Los Angeles Times
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Is There an AI Bubble? Financial Institutions Sound a Warning

On October 9, 2025, the Los Angeles Times published a sobering assessment of the current state of artificial‑intelligence (AI) startups and the broader market that has poured money into them. The article, titled “Is there an AI bubble? Financial institutions sound a warning,” argues that while AI remains a powerful engine of innovation, the valuations of many companies in the space have become disconnected from their fundamentals, and the risk of a burst bubble is real.

A Quick Snapshot of the Landscape

• Valuation Surge: In the past three years, AI‑focused firms have raised roughly $350 billion, a dramatic jump from the $60 billion raised for software and internet companies in 2019.
• High Multiples: Many of these companies—OpenAI, Anthropic, Cohere, and smaller “generative‑model” startups—are trading at 8‑to‑12× the next‑year projected revenue, a level that mirrors the late‑2000s dot‑com mania.
• Capital‑Intensive Model Development: Building state‑of‑the‑art language or vision models can cost $30–$50 million in compute alone, and the required hardware (GPU clusters, TPUs, and custom ASICs) is priced at $10–$15 million per data‑center.

The article cites a recent report by the Global AI Capital Index that noted a 45 % increase in the number of AI firms valued over $1 billion in 2024, compared to 12 % in 2023. That rapid rise, the Times writers claim, has attracted a wave of speculative investment that may not be sustainable.

Voices from the Financial Sector

The article features interviews with several key players in finance who warn that the current trajectory could be dangerous for both investors and the broader economy.

1. Samantha Lee, Managing Director, Global AI Funds, JPMorgan Chase
   “The hype has been palpable,” Lee says. “But when we look at the cash‑flow projections, we see that most of these firms will need several years of runway before they can reach profitability.” Lee stresses that many AI companies are still heavily reliant on venture debt and that a sharp slowdown in funding could create a cascade of defaults.

2. Dr. Miguel Navarro, Chief Risk Officer, Goldman Sachs
   Navarro points to the lack of “clear, consistent data on AI product adoption.” He warns that “valuation based on expected AI adoption curves is akin to betting on the next big tech trend without seeing solid revenue streams.”

3. Lisa Chen, Senior Analyst, Andreessen Horowitz
   Chen acknowledges the enthusiasm but cautions that “the underlying cost structure is volatile.” She highlights the high capital expenses associated with GPU infrastructure and the fact that many startups are not yet able to leverage economies of scale.

These warnings are echoed by investment banks such as Morgan Stanley and Citigroup, which are tightening their AI-related IPO underwriting criteria. The Times article quotes a former CMO of a leading AI firm who said: “If the market keeps inflating prices without real product traction, we’re likely to see a correction.”

Indicators of a Bubble

The article references several technical and market signals that analysts consider classic bubble markers:

• Rapid Growth in Unicorns: The number of AI unicorns (valuation > $1 billion) surged from 200 in 2019 to 1,200 in 2025, a 600 % jump.
• Excessive Debt: AI companies have taken on an average of 2.5× debt relative to cash reserves.
• Valuation‑to‑Revenue Ratios: Many firms now trade at 10–15× next‑year revenue, while historically, sustainable tech companies trade at 5–7× revenue.
• Price‑to‑Earnings (P/E) Skew: The average P/E for AI firms is 150, far above the S&P 500 average of 20–25.
• Market Sentiment: Social‑media‑driven hype, as highlighted by a Sentiment Analysis report from Bloomberg, shows a 70 % increase in positive mentions of “AI” versus “real‑world ROI.”

These metrics, the article argues, resemble the late‑1990s tech boom, when companies like Pets.com and Webvan were overvalued without a clear path to profitability.

What a Bubble Burst Could Mean

A correction in the AI market would not only affect the startups but could ripple across the broader tech ecosystem:

• Bank Exposure: Banks that have lent heavily to AI firms might see increased non‑performing loans.
• Venture Capital Losses: VC funds that held significant stakes in early‑stage AI companies could wipe out a large portion of their capital.
• Talent Flight: A sudden drop in funding could cause layoffs, creating a talent shortage for other sectors that rely on AI.
• Innovation Slowdown: A tightening of capital could stall progress on breakthrough AI applications that require long‑term investment.

The article notes that the regulatory environment is also under scrutiny. The U.S. Federal Trade Commission has begun to look at potential anti‑competitive practices in AI, while the European Union has proposed the Artificial‑Intelligence Act, which could impose compliance costs on firms that exceed certain thresholds.

A Call for Prudence and Transparency

To mitigate the risk, the article urges several measures:

1. More Rigorous Due Diligence: Investors should require detailed cost breakdowns and realistic milestones.
2. Transparent Reporting: AI companies should publish regular operational metrics (e.g., compute‑cost per model, data‑pipeline efficiency).
3. Diversified Funding: Firms should pursue a mix of venture, corporate, and public financing to avoid overreliance on a single source.
4. Regulatory Clarity: Policymakers should provide clear guidelines for AI development, especially around data governance and carbon‑footprint reporting.

The Bottom Line

The Los Angeles Times article does not dismiss AI as a fad. Rather, it cautions that the sector’s explosive growth, combined with lofty valuations and a lack of solid revenue streams, creates a fragile environment that could snap. Financial institutions across the spectrum are calling for a more measured approach to funding, arguing that sustained progress will come from companies that can demonstrate both technical capability and a viable business model, rather than from speculative bets on the next big breakthrough.

In a world where AI promises to transform everything from finance to health care, the article reminds us that careful stewardship of capital—grounded in fundamentals and tempered by realistic timelines—remains the best safeguard against an eventual bubble burst.