The AI boom propping up markets could trigger the next crash, central banks warn

The AI Boom's Risks: Central Banks Sound the Alarm

The AI boom propping up markets - Central banks are raising concerns about the rapid growth of artificial intelligence, warning that the current surge in investment could lead to a significant financial downturn. In its latest Annual Economic Report, the Bank for International Settlements (BIS) highlighted how the massive expenditure on AI is creating new vulnerabilities that might intensify future economic shocks. This report, released on June 29, 2026, underscores the need for immediate action to prevent the eventual correction from becoming a severe crisis.

Record Investments and Growing Debt

The BIS, often referred to as the central bank for central banks, emphasized that the scale of AI spending is outpacing the ability of companies to sustain it. The report points out that the five leading technology firms—known as hyperscalers—are set to allocate over $1 trillion in AI-related projects by 2026. This investment rate is exceeding their earnings and free cash flow, prompting some to take on substantial debt to maintain momentum.

“There is a clear sense of urgency,” stated Pablo Hernández de Cos, the BIS general manager, during the report’s presentation. He noted that the current AI race is driven by the belief that only a few dominant players will dominate the market, leading firms to commit resources to projects with uncertain returns. This speculative approach could leave the financial system exposed if the anticipated success of AI doesn’t materialize as expected.

Historical Parallels and Market Volatility

The BIS drew comparisons to past speculative bubbles, such as the canal mania of the 1830s and the British railway mania of the 1840s, to illustrate the recurring pattern of overinvestment. These historical episodes began with real technological advancements but eventually collapsed when capital outstripped viable returns. The current AI boom, according to the report, follows a similar trajectory, with risks spreading beyond financial markets to affect the broader economy.

“Each of these cycles ends with a reversal in investment, leading to widespread economic downturns,” the BIS observed. The warning is amplified by the current state of stock markets, which have seen inflated prices due to optimistic projections about AI’s potential. This overvaluation, combined with opaque financing practices, could create a domino effect if demand for AI-related assets slows.

Circular Financing and Hidden Risks

One of the key factors contributing to the AI boom’s fragility is the use of circular financing. This method involves chipmakers and cloud providers investing in AI startups by taking equity stakes, which in turn agree to purchase their products. As a result, funds are recycled back to the initial investors, effectively masking the true financial burden of AI development.

Zhang Tao, the BIS’s chief representative for Asia and the Pacific, highlighted how this reliance on non-bank financial channels—such as hedge funds and private credit vehicles—could exacerbate the impact of a potential AI downturn. These institutions face less scrutiny than traditional banks, allowing them to funnel money into AI projects without immediate accountability. If the AI market falters, the resulting losses might cascade more swiftly than in previous financial crises, according to Tao.

Costs Beyond the Surface

Critics argue that the financial implications of the AI build-out extend far beyond what is immediately visible. A major concern is how technology giants account for their data centers, which are central to AI operations. By extending the useful life of expensive equipment, companies can distribute its cost over longer periods, reducing depreciation charges and presenting healthier earnings figures.

However, this practice may not reflect the actual cash flow demands. The BIS noted that the rapid obsolescence of specialized chips could challenge these assumptions, creating a disconnect between reported profits and real economic performance. If hardware replacement costs rise or demand for AI services declines, the financial strain could become more pronounced.

Apple, for instance, recently announced price hikes for its MacBooks, iPads, and other devices, citing an unprecedented demand for memory and storage. The company claimed to have never experienced such a sharp and rapid increase in component costs. Despite the higher prices, Apple’s shares dropped nearly 6%, marking its worst single-day performance in over a year. Similar price adjustments have been made by Microsoft, Nintendo, and Sony, signaling broader industry pressures.

Energy Demand and Inflationary Pressures

As AI infrastructure expands, its demand for electricity is also growing rapidly. Goldman Sachs predicts that data centers will account for almost half of the US electricity demand growth by 2030. This surge is expected to push consumer power prices up by about 6% annually through 2027, contributing to a new wave of inflation.

Some economists now refer to this as the “third wave” of inflation, following the pandemic and trade-related increases. The AI build-out is driving up the costs of memory and storage components, which are critical for advanced computing systems. This has led to higher prices for consumer electronics and increased operational expenses for companies across sectors.

The BIS itself acknowledges that the AI sector’s energy consumption is already influencing inflation trends. While the report stresses that the outcome remains uncertain, the combination of overextended financing and rising input costs could create a self-reinforcing cycle of price increases. If the current momentum continues, the financial system may face a more severe correction than previously anticipated.

A Call for Prudent Policy

With the AI boom threatening to reshape global markets, central banks are urging policymakers to address the growing risks. The BIS report serves as a reminder that past bubbles have often left lasting scars, and the current situation is no different. The challenge lies in balancing innovation with financial stability, ensuring that the benefits of AI do not come at the cost of a broader economic crash.