JPMorgan Exec: AI Is Opportunity, Not a Bubble

JPMorgan Executive Highlights AI as Opportunity, Not Bubble

In a bold statement at the CNBC Delivering Alpha conference, Mary Callahan Erdoes, CEO of JPMorgan Asset & Wealth Management, dismissed the notion that artificial intelligence (AI) is a bubble. Instead, she framed AI as a monumental opportunity, despite ongoing market jitters over skyrocketing tech valuations.

Speaking on November 13, 2025, Erdoes acknowledged a significant disconnect in the market. While investors are aggressively pricing AI multiples, companies have yet to translate this enthusiasm into tangible bottom-line gains. To illustrate AI’s trajectory, she referenced an iconic Ernest Hemingway quote: "How do you go bankrupt? It happens very, very slowly, and then all of a sudden." This analogy suggests a gradual build-up followed by rapid, transformative impact.

Erdoes stressed that labeling AI as a bubble is "a crazy concept," emphasizing that the world stands on the "precipice of a major revolution." Her perspective was echoed by Michael Arougheti, CEO of Ares Management, who described the current investment in machine-learning tools as "meager" compared to their vast potential. Arougheti highlighted a critical imbalance: the supply of AI infrastructure and capabilities lags behind near-term demand, fueling market hyperbole due to the technology’s revolutionary potential.

Market Context and Investor Sentiment

Despite Erdoes’s optimism, the broader market showed signs of unease on the same day. Stocks experienced their worst sell-off in over a month, while hedge funds reportedly reduced equity exposure. Retail investors, however, continued to support the bull market. This bifurcated sentiment reflects institutional caution and retail enthusiasm, with Erdoes’s long-term view offering a strategic counterpoint to immediate market volatility.

Philippe Laffont, Coatue’s CEO, added to the discussion by describing the IPO market as "broken beyond repair." This comment underscores the broader challenges facing the tech sector, even as AI remains a focal point of investment and debate.

The Long-Term View on AI

Erdoes’s perspective challenges the prevailing narrative that AI, with companies like Nvidia and AMD at soaring valuations, is destined for a crash. She argues that the core premise of AI is a foundational technological shift, not a speculative bubble. While some segments of the market may be overheated, the economic impact of AI algorithms is only beginning to unfold.

Her macroeconomic outlook is equally confident. Erdoes dismissed fears of an impending recession, noting that such predictions have circulated for years without materializing. She encouraged investors to "lean in" on credit investments, describing the current environment as a "great buying opportunity" if a recession is not on the horizon.

Implications for Investors

Erdoes’s message to investors is clear: focus on the long-term opportunity of AI rather than short-term bubble fears. This approach requires distinguishing between genuine innovators poised for long-term gains and companies merely riding the hype cycle. Arougheti’s emphasis on supply constraints further highlights the strategic importance of investing in foundational AI infrastructure, including advanced chips, robust data centers, and specialized talent.

The broader market context, with hedge funds exercising caution and retail investors maintaining optimism, underscores the need for a nuanced investment strategy. Erdoes’s calm assessment suggests that investors should look beyond immediate market fluctuations and focus on the transformative potential of AI and other technologies.

Conclusion

In summary, JPMorgan’s Mary Callahan Erdoes frames AI as a monumental opportunity, not a bubble. Her perspective, supported by industry leaders like Michael Arougheti, highlights the long-term potential of AI despite current market volatility. For investors, the key lies in identifying companies that can bridge the gap between AI’s potential and practical application, while navigating the complexities of a rapidly evolving technological landscape.