AI Bubble and the Buffett Indicator: Why Wall Street Veterans Warn of Overheating

📌 Market Overheating Warning: The AI Bubble and the Historical Alarm of the Buffett Indicator

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Introduction — Record-High Markets, but Rising Anxiety

In the fall of 2025, Wall Street once again set fresh all-time highs. The S&P 500 closed at 6,715.79 on October 3rd, marking another historic peak. There is no denying that the market looks strong on the surface. Yet what makes this moment noteworthy is that some of the most seasoned voices in global finance are stepping on the brakes. David Solomon (CEO of Goldman Sachs), Jeff Bezos (founder of Amazon), and billionaire investor Leon Cooperman have all issued warnings that investor euphoria is masking serious risks.

Historically, these moments have often coincided with phases where stocks rise not because fundamentals look attractive, but because narratives and momentum have become “too good” to resist. A high index level alone is not inherently dangerous. The real risk emerges when “the story outpaces the numbers,” a classic precursor to increased volatility.

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Part I. The AI Investment Frenzy and Warning Signs

1) Goldman Sachs CEO’s Warning — “A Correction Within 12–24 Months Would Not Be Surprising”

Speaking at the Italian Tech Week conference in Turin, David Solomon delivered a sobering message: “Within the next 12 to 24 months, it would not surprise me if the stock market experiences a drawdown.”

His reasoning is straightforward:

Every new technology cycle — and today that cycle is AI — attracts an explosive inflow of capital.

A significant portion of that capital inevitably flows into areas that do not convert into profits quickly.

As history shows, such conditions almost always invite a period of reset, review, or correction.

Solomon explicitly compared today’s market with the dot-com era (1999–2000). Back then, the internet was a genuine breakthrough. Giants like Amazon and Google were born. But at the same time, countless dot-com companies collapsed due to weak business models, reckless fundraising, and unrealistic expectations.

His key message is not to sensationalize the word “bubble” but to remind investors that a correction is part of the natural cycle.

> Interpretation

A “reset” is not synonymous with collapse. It means prices are retracing after moving too far ahead of fundamentals.

In such cycles, companies with visible earnings and strong cash flow usually diverge positively from firms that rely solely on narratives.

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2) Jeff Bezos’ Diagnosis — “AI Is in an Industrial Bubble, but the Technology Is Real”

At the same conference, Jeff Bezos described the current environment bluntly: “AI is in the middle of an industrial bubble.” Yet he immediately qualified it with a crucial point: “The technology itself is real and will bring massive benefits to society.”

In other words, bubble does not equal uselessness. Instead, it represents a stage of overheated capital allocation. The hallmark of a bubble is when:

Stock prices decouple from fundamentals, at least temporarily.

Both good ideas and bad ideas get funded together, with little distinction.

Investors find it difficult to separate winners from losers.

Still, Bezos argued that “industrial bubbles leave a lasting footprint.” Just as the dot-com boom left behind the internet infrastructure and e-commerce revolution, and just as the biotech bubble left behind viable platforms and life-saving drugs, the AI bubble will also leave behind real productivity assets.

> Reality check

According to PitchBook, U.S. AI startups raised $104.3 billion in the first half of 2025 alone. This staggering figure shows why the term “flood of capital” is not an exaggeration.

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3) Leon Cooperman and Warren Buffett’s Warning — “When Psychology and Momentum Drive Prices”

Veteran investor Leon Cooperman labeled today’s environment as the “late innings of a bull market.” As valuations stretch and momentum dominates, he warned, “even good news may fail to lift stock prices,” a classic fatigue signal.

To illustrate, Cooperman recalled Warren Buffett’s famous 1999 interview, where Buffett cautioned that when the ratio of total market capitalization to GDP (now known as the Buffett Indicator) rises too far, investors are essentially “playing with fire.”

Today, that ratio is not just elevated — it has surged well above the 200% threshold. For Cooperman, this is a flashing red light: the same psychological conditions that defined the late 1990s are repeating themselves, this time under the banner of AI.

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Part II. Numbers That Confirm the “Overheating”

1) The Buffett Indicator: 216–218% — “Highest on Record”

The Buffett Indicator, calculated as total U.S. market capitalization (Wilshire 5000) divided by GDP/GNP, currently reads between 216% and 218% depending on methodology.

Dot-com peak (1999–2000): ~150%

Pandemic liquidity rally (2021): ~190%

Today (2025): 216–218% — the highest level ever.

This means the stock market’s valuation is more than twice the size of the economy, a level of inflation in asset prices that is difficult to justify through fundamentals alone.

> Caution

The Buffett Indicator is not a timing tool for day traders. But historically, such extremes have signaled lower long-term expected returns and heightened vulnerability to interest rate shocks or earnings disappointments.

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2) Record Index Levels: The Hidden Fragility

The S&P 500 closing at 6,715.79 on October 3 does represent undeniable strength. But the important question is not “how high” the index is, but “what is driving it upward?”

The main factors are:

Multiple re-ratings of large AI beneficiaries relative to their capital expenditures and revenue.

Anticipation of interest rate cuts, which lowers discount rates and inflates valuations.

Heavy concentration in mega-cap stocks, leaving the rally vulnerable to narrow leadership.

In other words, today’s market is built on assumptions. As long as those assumptions hold, the rally continues. But if even part of the narrative cracks, volatility could surge.

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3) The Gap Between Story and Numbers

Earnings visibility: AI infrastructure, GPUs, and cloud services have strong top-down stories, but the timing of free cash flow generation varies widely by company.

Valuation strength: When price multiples expand faster than revenue growth, stocks become fragile to interest rate changes, competitive threats, or regulatory scrutiny.

Financing conditions: If the current expectation of easier monetary policy falters, companies dependent on future cash flows will be repriced the fastest.

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Part III. Investor Psychology and Market Cycles

1) The Illusion of “This Time Is Different”

Every bubble shares the same root: human psychology. In 1999, the narrative was “The internet will change the world, so this time is different.” By 2025, the same phrase is back: “AI will change the world, so this time is different.”

Yes, AI’s potential is transformative across industries from healthcare to finance to education. But technology’s promise and the valuation investors are willing to pay for it are two separate realities. History teaches us that whenever “this time is different” becomes the mantra, markets eventually revert to their cyclical nature, and bubbles deflate.

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2) Winners and Losers

History also shows that bubbles don’t treat all companies equally.

Winners: During the dot-com crash, Amazon, Google, and eBay endured the pain but survived to dominate global markets. In the AI era, firms like NVIDIA, Microsoft, and Google — companies with strong cash flow, scale, and defensible moats — are more likely to remain winners.

Losers: Hundreds of smaller dot-coms vanished, just as overhyped AI startups may disappear when capital markets turn restrictive or regulators tighten the screws.

Thus, bubbles serve as a brutal but effective selection mechanism, enlarging winners while eliminating weaker players.

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3) Implications for Investors

In the short term, liquidity and investor enthusiasm may continue to fuel rallies. But in the medium to long term, with valuations already stretched, a correction is inevitable.

That is why investors should rely on a clear risk-management checklist rather than hype.

📝 Risk Checklist

1. Cash flow visibility: Will the company generate meaningful operating cash flow within 1–2 years?

2. Dependency risk: Is revenue overly concentrated in one client, supplier, or regulatory condition?

3. Valuation sanity check: Are multiples reasonable compared to peers or past cycles?

4. Interest rate sensitivity: Can the business withstand higher discount rates?

5. Downside buffer: Does the company hold enough cash or equity strength to weather a bear case?

Companies that pass most of these questions are far more likely to emerge as the long-term survivors of the AI cycle.

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Conclusion — The AI Bubble: Both Risk and Opportunity

Today’s stock market is riding on the back of AI optimism, breaking records in the process. But the Buffett Indicator has soared to historic highs above 217%, and respected voices from Wall Street to Silicon Valley are ringing the alarm bells of overheating.

1) Corrections Are a Natural Phase

Markets never rise in a straight line. Every new technology cycle — railroads, electricity, the internet, and now AI — has gone through a phase of excessive capital inflows, followed by a period of reset, review, and correction. This is not collapse; it is normalization.

2) Scenario Planning for the Next 12–24 Months

Soft landing: Expectations cool but cash-flow-rich AI leaders sustain selective strength.

Valuation reset: Overpriced names tumble and weaker players are forced out, leaving “the real ones” behind.

Re-acceleration: Inflation eases, rates fall, and AI business models prove profitable faster than expected, triggering another wave of gains.

Regardless of which path unfolds, investors must focus on companies resilient enough to survive all three scenarios.

3) A Balanced Investor Mindset

History never repeats exactly, but it often rhymes. The dot-com bubble ended painfully, yet its true innovators became the backbone of the digital economy. Likewise, the AI bubble may deflate, but its core innovations will reshape industries for decades.

For investors, the key takeaway is clear: AI represents both danger and opportunity. Blind optimism is risky, and pure fear is equally costly. What matters is balance — combining cautious risk management with the foresight to identify long-term winners.

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👉 In short, “The AI bubble is a risk to avoid, but also an opportunity to seize.” Smart investors must use discipline and discernment to navigate the cycle — and to make sure they are holding the future winners when the dust settles.