Ai's boom: bubble or sustainable growth?

The lingering question: ai sustainability

For over two years, financial markets have grappled with a crucial question: is the economic trajectory of Artificial Intelligence (ai) sustainable, or are we witnessing a bubble? The echoes of the dot-com crash remain vivid, dividing investors between those who believe “this time is different” and those who remain skeptical. Some even suggest a simultaneous occurrence of both – a near ‘quantum’ event supported by various indicators, creating a complex investment landscape.

The bull case: solid fundamentals

The soaring stock prices of ai-driven tech companies like ChatGPT and Claude suggest potential overvaluation. However, underlying this growth are positive indicators, particularly the evolution of earnings which support current valuations. Chris Buchbinder, Portfolio Manager at Capital Group, argues that a comparison to the dot-com era is valid, but requires nuance. He believes we're closer to 1998 than 2000, and while a bubble is possible, we haven't reached a critical point yet.

Earnings and capital expenditure

A key argument against a bubble is the existence and growth of profits. Unlike the telecom companies of the late 90s, today’s leading ai companies generate sufficient cash flow to absorb massive capital expenditures. Companies like Alphabet, Amazon, Microsoft, Meta, Broadcom, and NVIDIA are investing hundreds of billions of dollars in infrastructure, chips, and data centers, but doing so from a position of financial strength, largely avoiding significant debt.

The “magnificent four” investment plans

These leading ai companies – often referred to as the “Magnificent Four” – are projected to invest over $500 billion in 2026 alone. Buchbinder emphasizes that these companies’ stock valuations are supported by strong earnings growth, suggesting that fear of a bubble might be premature. A key factor is the transversal improvement in activity driven by ai adoption, despite the inherent disruption it causes.

Dot-com vs. ai: a comparative look

Sector rotation and emerging risks

Yves Bonzon, Chief Investment Officer at Julius Baer, introduces a counterpoint, highlighting a convulsive start to 2026 characterized by unprecedented sector and thematic rotation since 2000. This includes a return of capital-intensive sectors and a penalty for models based on intangible assets. He notes a compression of software company multiples since ChatGPT's emergence, raising concerns about the viability of business models facing AI agents like Claude, which can generate code and programs.

The rise of retail investors and algorithmic trading

Bonzon also points to a structural shift in market mechanics: retail investors now comprise over a third of trading volume in the U.S., and algorithmic trading – often driven by AI – dominates investment flows. “Machines don’t have feelings,” he warns, suggesting that traditional fear and greed indicators might be becoming obsolete. This could lead to abrupt movements and rotations becoming the new normal.

Etf flows and diversification

The surge in AI investment is reflected in ETF flows. European-domiciled ETFs captured a record $55.9 billion in January 2026, primarily flowing into equity markets, with a preference for global and developed market ETFs. This suggests a continued appetite for risk, but channeled through increasingly diversified investment vehicles, rather than concentrated bets.

Private credit and future opportunities

Loomis Sayles, an affiliate of Natixis Investment Managers, sees “interesting opportunities” in private credit, fueled by AI and technology-related capital expenditures and a rise in mergers and acquisitions. However, they caution that increased competition among lenders could lead to compressed returns and more aggressive structures, a common pattern in the later stages of enthusiasm cycles.