AI Bubble Warning: Global Market Selloff, Credit Risks, and the Next Phase of Investing

📘 Part I. The “AI Bubble Warning” That Shook Global Markets — The Heat Is Starting to Fade

In early November 2025, global stock markets turned sharply lower.

Technology shares led the sell-off, with the Nasdaq Composite down about –3.8% and the Philadelphia Semiconductor Index off –4.5%.

Analysts said the pullback signaled that the AI-themed rally that had powered markets since 2023 may have reached a tipping point.

This section unpacks why the term “AI bubble” began circulating, what warning signs were flashing, and the structural forces that triggered the current correction.

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1️⃣ Signs of Excess — When Expectations Overtake Reality

The defining feature of this rally was speed — expectations outran fundamentals.

Over the past two years, stocks linked to AI—semiconductors, servers, and data-center infrastructure—soared.

NVIDIA surged roughly ten-fold from 2022 levels, AMD rose five-fold, and Supermicro skyrocketed fifteen-fold.

But profits didn’t keep up.

NVIDIA’s Q3 2025 net income jumped 70% YoY, yet its stock price had already priced in far greater growth.

That gap between earnings and expectations marks the classic early stage of a bubble.

The Bank for International Settlements (BIS) recently warned that “the AI boom resembles the early phase of the late-1990s internet bubble.”

The same three dynamics are visible today:

> (1) Extreme capital concentration in one sector,

(2) Valuations detached from real-economy earnings,

(3) A surge of retail inflows chasing momentum.

One telling metric: U.S.-listed AI ETFs drew $65 billion in the first half of 2025 — a 2.4× increase from the prior year.

Such inflow velocity is a textbook measure of overheating.

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2️⃣ Rates and Liquidity — When Cheap Money Stops Being Cheap

The AI rally was born in an era of easy money.

Low rates and abundant liquidity pushed investors into growth stories.

But by late 2025, the Fed funds rate sits at 5.25–5.50%, inflation remains above 2%, and unemployment is in the mid-3 percent range — leaving the Fed little room to cut.

Meanwhile, the U.S. 10-year Treasury yield has climbed past 4.6%, making bonds competitive again versus equities.

Capital that once chased “growth at any price” is rotating toward value and dividend plays instead.

Put simply, the era of cheap money is over, and expensive money is rewriting market leadership.

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3️⃣ The Contagion — From Wall Street to Tokyo, Taipei, and Seoul

This “AI bubble” anxiety isn’t confined to the U.S.

Because global supply chains are tightly linked, the shock spread quickly across Asia and Europe.

Japan’s Tokyo Electron dropped 5–7% in a single day.

TSMC in Taiwan and SK Hynix in Korea saw similar slides.

The KOSPI Semiconductor Index fell 4.2% in the first week of November, led by steep losses in HBM (High-Bandwidth Memory) stocks.

Yet many Asian chipmakers are still posting solid earnings; what’s fading is investor psychology, not technology.

In other words, the correction is less about fundamentals and more about sentiment — a psychological bubble deflating, not a technological collapse.

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🔍 Key Takeaways

This downturn is more than a blip.

It signals that the AI-themed rally has shifted from euphoria to a cooling phase.

The ingredients of the bubble were clear: runaway expectations, concentrated capital, and valuations that leapt ahead of profits.

Its unwinding reflects higher interest rates, tighter liquidity, and the renewed allure of safer assets.

The lesson: in the next phase, investors must focus less on “Is it AI-related?” and more on “Is it profitable, cash-flow-positive, and reasonably valued?”

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📗 Part II. End of the Bubble — or a New Entry Point?

By November 2025, markets worldwide stand at a crossroads.

For two years, investors poured money into the AI ecosystem — chips, data centers, and power infrastructure.

Now, as the hype fades, they face a pivotal question:

> “Is this merely a pause, or a full-blown regime shift?”

The answer will shape capital flows and industrial strategy for the next decade.

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1️⃣ From Story to Earnings — The Return of Fundamentals

Between 2023 and 2024, narrative ruled.

If a company mentioned “AI,” its stock soared — ChatGPT, generative AI, GPUs, HBMs.

But in 2025, the market stopped rewarding promises and started demanding proof.

The key metric is no longer AI exposure, but AI monetization.

NVIDIA still controls > 80 % of the GPU market, but slowing data-center CAPEX hints that earnings growth may have peaked.

AMD and Intel launched the MI450 and Gaudi 3 AI chips, yet need 6–9 months to turn launches into profits.

Microsoft and Google have achieved stable, recurring AI-cloud revenues via Azure OpenAI Service and Gemini API.

The market’s center of gravity is shifting:

> From “Who builds AI?” to “Who makes money from AI?”

It’s the same filter that followed the 2000 dot-com crash: only businesses with real cash flow survived.

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2️⃣ The Rise of “AI + Infrastructure” — Where the Real Opportunity Lies

Even amid bubble talk, demand for AI-driven infrastructure is exploding.

According to the International Energy Agency (IEA):

> “By 2030, electricity demand from AI data centers will grow sixfold from 2023,

with annual power-infrastructure investment exceeding $1 trillion.”

AI is transforming the physical economy, not just the digital one.

Massive computing loads require more power grids (HVDC), transformers, cooling systems, semiconductors, and energy-storage systems (ESS).

Hence, the real beneficiaries are not AI software firms but hardware and energy-infrastructure providers such as:

AES Corp (US) — expanding renewable power projects for data centers

NextEra Energy (US) — signing long-term clean-energy contracts for AI servers

LS Electric, Hanwha Aerospace, Hyosung Heavy Industries (Korea) — exporting HVDC and ESS systems globally

Even if the AI hype cools, the need to reinforce and electrify power networks remains.

In the AI era, the core asset isn’t the chip — it’s the power line.

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3️⃣ Global Flows — From Risk-Off to Rebalancing

Some foreign funds are exiting equities, but this is better seen as a portfolio rebalancing, not a panic.

Morgan Stanley recently wrote:

> “The Q4 2025 pullback marks not the end of the AI cycle,

but the start of Phase 2 — the profit-realization stage.”

History rhymes.

After the 1999 bubble burst, Amazon lost 94 % of its market value — then rose 10× within five years.

Why? Because its business model worked once speculation cleared.

Today’s AI correction may set the foundation for the next decade’s winners.

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4️⃣ Lessons for Investors

1️⃣ Follow profits, not hype.

Story-driven rallies always end; earnings keep compounding.

2️⃣ Think value chain, not sector.

Trace how revenue flows — from AI chips to power grids, data centers, network gear, and software.

3️⃣ Use corrections as entry points.

Every bubble pops, but survivors define the next cycle.

(Think Amazon in 2000, Tesla in 2008, NVIDIA in 2020.)

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🔍 Conclusion — “The Future Begins Where the Bubble Ends”

The AI bubble is both a threat and a test.

Every major tech revolution—Internet, smartphone, cloud—was labeled a bubble before becoming indispensable.

AI is no exception.

Unlike past “consumer tech” fads, AI is a “productivity infrastructure” reshaping entire industries.

Short-term corrections may sting, but the long-term trajectory remains intact.

The real task now is to separate real companies, real earnings, and real structural growth from speculative noise.

That discernment will determine the next decade’s returns.

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📘 Part III. Beneath the Surface — When Credit and Liquidity Collide

While headlines fixate on the “AI bubble,” a slower, more dangerous force is building underneath:

the credit cycle and hidden leverage within the financial system.

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1️⃣ Why Major Crises Always Start with Credit

Credit, in essence, is borrowing tomorrow’s income to spend today.

During boom times and low-rate environments, optimism reigns:

Households borrow for homes and consumption.

Corporations borrow for CAPEX and M&A.

Financial firms lever up for higher returns.

Then come the complex products that disguise risk—MBS, CDOs—as we saw in 2008.

A century of BIS and IMF data shows a clear pattern:

> “The magnitude of credit expansion, not stock-market gains,

best predicts the depth of the next downturn.”

When the credit-to-GDP ratio spikes, the odds of a recession within 3–5 years roughly double.

Thus, the key metric isn’t price —it’s debt.

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2️⃣ The Weak Link of This Cycle — Invisible Leverage

Unlike 2008, today’s leverage is outside the banking system.

Non-bank financial institutions (NBFIs) — hedge funds, private-credit funds, and shadow-banking vehicles — now carry much of the risk.

The IMF’s Global Financial Stability Report (Oct 2025) warns that U.S. and European banks have trillions of dollars of exposure to these opaque entities.

They operate with lighter regulation, thinner liquidity buffers, and a tendency to sell everything at once when volatility spikes.

That makes the “shadow” sector the new fault line of systemic risk.

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3️⃣ When AI Euphoria Meets Credit Tightening

If the AI sell-off overlaps with a credit squeeze, the sequence could look like this:

1️⃣ AI & tech stocks slump

2️⃣ Risk-off sentiment spreads

3️⃣ High-yield and BBB credit spreads widen sharply

4️⃣ Private-credit and hedge-fund redemptions trigger forced sales

5️⃣ Contagion hits banks, insurers, and pensions

The BIS and IMF call this a “Deleveraging Market” — a downturn defined not by price declines alone,

but by a collapse in liquidity and credit creation.

History offers precedents:

1998 LTCM crisis — hedge-fund leverage implosion

2008 Lehman collapse — structured-credit meltdown

2020 COVID shock — ETF and corporate-bond freeze

If similar stress emerges today, “AI bubble burst” could move from metaphor to reality.

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4️⃣ Early-Warning Indicators for Individual Investors

You don’t need to panic or go 100 % cash.

But monitor these objective red flags:

① Credit-spread blowout — BBB or high-yield spreads widening > 100 bps rapidly.

② Financial-sector underperformance — Banks/insurers lag while tech stays firm.

③ Liquidity-freeze headlines — Fund-redemption halts, margin-call news, or private-credit distress.

When all three flash simultaneously, it’s not just an AI correction — it’s the start of a credit-cycle reversal.

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🔍 Final Take — The Bubble Is Visible; the Debt Is Not

Market bubbles are emotional.

Crises are mechanical — they’re about liquidity.

In a high-rate, high-debt era, the smartest defense is to track the quality of credit, not the lure of yield.

That vigilance is what separates survivors from casualties when the next downturn hits.

> “A bubble is born of sentiment;

a crisis is born of liquidity.”

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Sources

The Guardian (2025-11-05) – Global Markets Fall Sharply over AI Bubble Fears

Reuters (2025-11-05) – WEF Chief Warns of AI, Crypto and Debt Bubbles

BIS (2025 Q3) – Global Financial Stability Review

IMF (2025 Oct.) – Global Financial Stability Report

IEA (2025) – AI and Data-Center Power Demand Forecast

Morgan Stanley (2025 Q4) – AI Cycle Phase 2: Profit Realization Begins