The AI Boom Is Real. The Hidden Risk Is, Too. - Aronima Biswas

The artificial intelligence (AI) boom in investing has swept through the world’s stock markets this year, pushing a number of tech giants to historic highs (e.g. Nvidia) and stoking the possibility of another revolution in productivity. But the same zeal has triggered warnings from regulators and economists. The International Monetary Fund and Bank of England have both warned that the boom in AI can trigger a rapid stock market correction, claiming that stretched valuations and concentrated gains leave markets vulnerable to unexpected reversals. 

Concentrated optimism, concentrated risk

The IMF’s latest analysis identifies three weaknesses. One, valuations on AI-stocks have increased far in excess of real productivity gain. Two, the majority of the market advance is due to a concentrated position of small numbers of mega-cap firms, and the indices are dependent upon a few names to a great degree. Three, investor attitude has shifted from cautious optimism to enthused momentum. A single earnings or regulation setback can induce a violent sell-off with a concentric effect on world markets.

The Bank of England has also pointed out such warning signs, warning that financial conditions are too heavily based on investor belief in long-term AI potential rather than quantitative profitability. In such a scenario, the risk of a correction is abrupt rather than incremental.

A double bubble in play

Analysts refer to the scenario now as a “double bubble” where one is equity valuation and the other wave of financing into AI startups. The former appears in stock markets, where future profitability is being priced as if overall AI productivity has already fallen. The latter appears in venture capital and private investment channels, where money flows into startups promising AI breakthroughs.

Financial Times analysis shows that the majority of the present AI boom is equity-financed, which is systemic risk by being low on leverage. That distinguishes the AI boom from credit-fueled bubbles that generated crises such as that in 2008. Nonetheless, the lack of debt exposure does not exclude asset price volatility. Equity investors are still capable of triggering brutal corrections if they collectively rerate growth expectations.

Echoes of the dot-com era

The warnings remind one of the late 1990s, when money poured in from venture capitalists into internet companies that would change the world but did not make much money. The dot-com bubble burst in a correction that erased trillions of market value but also financed the digital infrastructure that underlies today’s economy. Economists suggest that the AI boom may act the same way, a wave of overinvestment and hype that eventually gives way to consolidation, leaving actual technological breakthroughs behind.

Measuring the true exposure

It is difficult to estimate the true size of the AI boom. Investing in AI is normally embedded within broader corporate budgets for cloud computing, semiconductors, and automation. The IMF estimates that AI investment is soaring quickly with 92% of firms planning to increase AI investment in the coming years, however it remains a relatively small percentage of global GDP compared with past tech bubbles. This should act to soften the overall economy in the event the valuations come off.

But the problem is expectations. Market prices today are predicated on hypotheses of almost perfect execution by leading AI firms and almost everybody adopting their technologies. If revenues or productivity benefits fall behind these expectations within the next several years, the shakeout will be severe. For now, the market narrative is forcing prices ahead of profits that can sustain.

How pervasive could the collapse be?

According to the IMF chief economist, the fall in AI equities will be painful for investors but is unlikely to lead to a crisis system. Most AI investment continues to be funded with retained earnings or the issuance of equity and not credit. The nature of such a structure is that losses would disproportionately fall on investors rather than threaten bank solvency.

Though, things might take a turn for the worse if leverage begins seeping back into credit markets. Venture debt, structured products, or bank loans collateralized on AI companies growing could magnify losses when the cycle turns. Another threat is liquidity risk. With a handful of stocks propelling world indices, a sudden exit by institutional investors’ can result in out of proportion price swings and further destabilize sentiment.

Geopolitical and policy shocks are yet another unforecastable factor. Export controls on advanced chips, trade tensions over access to information, or oppressive regulation of AI models would each have the ability to act as a catalyst for repricing. The Bank of England has lately warned that the external pressures can combine with domestic market vulnerability to amplify volatility.

Regulatory and Market Responses 

The IMF and Bank of England’s recent actions are aimed at shifting market psychology prior to a correction that otherwise compels it. They emphasize the importance of transparency in AI-facing disclosures, banks’ requirements to monitor concentrated exposures, and the usefulness of incorporating sharp tech-sector declines into stress tests. Regulators are also considering whether to step up surveillance of venture debt and private credit extended to AI firms, where information is limited.

Similarly, portfolio managers should examine concentration risks, particularly in AI related mega-caps whose valuations imply nearly flawless implementation. Venture investors should anticipate more linear paths to the creation of revenues versus speculation on user growth. Next year will likely sort out the companies with genuine technological moats from those artificially inflated by hype.

The outlook: promise with pressure

The outlook for AI remains essentially bullish. Even a correction would not erase the long-term promise of machine learning to redefine productivity across industries. History suggests that innovation cycles tend to overshoot before offering a lasting economic contribution. The issue is not whether the AI space is overhyped, however, it is whether markets can overcome a correction without damaging the broader economy.

The IMF’s base case scenario depicts a contained adjustment, not a meltdown of the system, provided credit markets are insulated and policy signalling is maintained clear. Policymakers are walking quite delicately between allowing innovation to grow and preventing speculative excess from undermining confidence.

For shareholders, the message is clear: diversify, hedge leverage, and distinguish between positive productivity tales and mania tales. The current cycle still has some way to run, but history has shown that technology euphoria without fiscal restraint can result in ugly revaluation.

Bibliography

Arnold, M. and Jones, C. (2025). IMF and BoE Warn AI Boom Risks ‘abrupt’ Stock Market Correction. [online] Financial Times. Available at: https://www.ft.com/content/fe474cff-564c-41d2-aaf7-313636a83e5b. 

Danielsson, J. and Macrae, R. (2025). Of AI Bubbles and Crashes. [online] VOX EU Centre for Economic Policy Research . Available at: https://cepr.org/voxeu/columns/ai-bubbles-and-crashes. 

Financial Times. (2025). Measuring Risk in the AI Financing Boom. [online] Available at: https://www.ft.com/content/50f6a373-f7b9-455e-b8ab-129d312822c1. 

Lawder, D. (2025). AI Investment Boom May Lead to bust, but Not Likely Systemic crisis, IMF Chief Economist Says. Reuters. [online] 14 Oct. Available at: https://www.reuters.com/legal/transactional/ai-investment-boom-may-lead-bust-not-likely-systemic-crisis-imf-chief-economist-2025-10-14/. 

Martindale, J. (2025). S&P 500 Companies Totalling $20 Trillion in Market Cap Have medium-to-high AI Exposure — Concerns of an Impending Bubble Collapse Extend to Almost Half of the Index. [online] Tom’s Hardware. Available at: https://www.tomshardware.com/tech-industry/s-and-p-500-companies-totalling-usd20-trillion-in-market-cap-have-medium-to-high-ai-exposure-concerns-of-an-impending-bubble-collapse-extend-to-almost-half-of-the-index. 

Mayer, H., Yee, L., Chui, M. and Roberts, R. (2025). Superagency in the workplace: Empowering People to Unlock AI’s Full Potential. [online] McKinsey & Company. Available at: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work?. 

Thornhill, J. (2025). AI’s Double Bubble Trouble. [online] Financial Times. Available at: https://www.ft.com/content/da16e2b1-4fc2-4868-8a37-17030b8c5498.