Note: considering the latest articles I have read I felt it prudent to ask the current "expert" in the A.I. community the probabilities of a bubble burst. Here is what ChatGPT told me ... 🧐
Here’s a breakdown of the risk that an “AI bubble” might bust — and what the potential effects on the economy could be. I’ll emphasise that exact probabilities are inherently uncertain for bubbles, but we can look at indicators, scenarios, and plausible ranges.
1. Probability of a bubble-burst in AI
There is no precise scientific probability (e.g., “30 % chance”) agreed upon by economists for a burst in the Artificial Intelligence-investment bubble. That said:
• Many analysts believe the risk is increasing. For example, a survey found 54 % of investors thought AI stocks were in a bubble.
• Institutions such as the Bank of England and the International Monetary Fund have issued warnings about the risk of a “sharp market correction” driven by AI-related valuations.
• Analytical essays conclude that the structural conditions for a bubble are present: investment far exceeding current productivity, huge infrastructure build-out, valuations based more on promise than realised returns.
My best estimate: there is a material probability — perhaps in the ballpark of 20-40% over the next 1–3 years — that we could see a significant correction (i.e., a burst of the most speculative portion of the AI boom). This is not a guarantee of collapse, but a non-trivial risk. The wide range reflects uncertainty about how quickly returns on AI investments materialise, and how investor sentiment holds.
2. What could trigger it and how large is the risk?
Triggers
• Valuations become decoupled from actual productivity or profits. For example: massive spending on data centres, chips, etc., but slower‐than-expected business impact.
• Investment financed by debt or leverage rather than equity, increasing systemic risk.
• A faltering of “promise vs reality” — if AI doesn’t deliver at the pace assumed, or hype runs ahead of fundamentals, the mood can shift quickly.
Size of the risk / how big could the fallout be?
• Analysts argue that because the current AI-investment wave is large, concentrated (few big tech companies), and heavily embedded in infrastructure,
.
• On the other hand: If the investment is mostly equity‐financed and the companies hold strong balance sheets, the real‐economy damage might be moderate — more of a wealth/valuation correction rather than full-blown crisis.
3. Potential effects on the economy
If a major AI-bubble correction does happen, here are how the channels of impact might work, and what the magnitude could be.
Channels of impact
• Wealth effect: If valuations in tech/AI stocks fall steeply, household wealth (via retirement funds, 401(k)s, etc.) takes a hit → consumer spending could shrink.
• Investment pull‐back: If companies that built out big AI infrastructure find weak returns, they may cut back further investment, which slows growth.
• Credit/financial stress: If lots of speculative ventures were financed by debt/leverage, a bust could trigger defaults, tighter lending, and broader financial system risk. The bigger the debt layer, the greater the spillover.
• Productivity disruption / misallocation: Huge resources might have been tied up in AI hype rather than more productive uses — so when the bubble bursts, there may be retrenchment and wasted capacity.
• Labour force & structural disruption: One scenario is that AI adoption leads to job changes/displacement; if the economic shock coincides with large structural shifts, there may be higher unemployment, regional impacts, etc.
Magnitude & plausibility
• In a “mild” correction scenario: valuations drop 20-30% among AI-hyped firms, investment growth moderates, but no major systemic crisis. Growth slows, perhaps a mild recession or extended stagnation.
• In a “severe” scenario: widespread credit losses, major tech firms retrench, ripple effects into consumer spending & business investment → could lead to recession, significant job losses in affected sectors, and global spillovers. Some commentators warn this could be worse than the early 2000s dot-com bust because of concentration and infrastructure scale.
Timing
• Some see the risk being most acute in the next 12-24 months, especially if companies fail to show expected returns from their huge AI investment.
• Others argue that the AI transition may stretch over many years and a bust might not appear immediately.
4. My reasoned conclusion
Putting it all together:
• I would assume something like a ~30% chance that we see a significant correction in AI-related valuations/investments in the next couple of years.
• Within that 30%: maybe a ~20% chance of a “moderate” correction (less severe, limited spillover) and ~10% chance of a “severe” correction with broader economy impact.
• Of course, the flip side is a ~70% chance that no major collapse happens — perhaps valuations adjust gradually, or growth continues (albeit perhaps more slowly than hype would suggest).
• The key risk is that if the bubble bursts and investment pulls back sharply, the economy could face a pronounced slowdown — through diminished business investment, weaker consumer spending, and possible financial stress.
• But even in a bust scenario, the fundamental potential of AI (productivity, new business models) means the “base case” doesn’t have to be catastrophic — it depends a lot on how the burst happens, how leveraged the system is, and whether policy/financial systems absorb the shock.
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