BURST THE BUBBLE?: Expert reveals whether ‘AI bubble’ phenomenon is true

Key Concepts

• AI Bubble vs. AI Boom: The central debate regarding the current state of Artificial Intelligence investment.
• Circular Financing: A concern raised about deals where companies invest in each other, potentially creating artificial value.
• Valuations: The assessment of a company's worth, particularly in relation to its earnings and market sentiment.
• FOMO (Fear Of Missing Out): Investor sentiment driven by the fear of missing potential gains, leading to aggressive investment.
• Eyeballs vs. Earnings: A distinction between early internet companies focused on user acquisition (eyeballs) versus current AI companies generating actual revenue (earnings).
• Asset Allocation: The strategy of distributing investments across different asset classes.
• Mega Caps vs. Small Caps: Investment in large, established companies versus smaller, potentially higher-growth but riskier companies.
• Enhancing Existing Business Models: The strategy of investing in AI that complements and improves current successful business operations.

AI Bubble vs. AI Boom: A Detailed Analysis

The discussion begins by drawing a parallel between current AI market sentiment and the "tariff tantrum" of April, suggesting that media attention amplifies fear and market reactions. The speaker criticizes the media's surprise at negative survey results regarding policy-related fears, likening the situation to a "farce" and "Rick's cafe."

Anthropic Deal and Circular Financing Concerns

A significant recent development highlighted is the deal involving Anthropic.

• Deal Details: Anthropic will purchase $30 billion worth of Azure compute and adopt Nvidia's system.
• Investments: Nvidia will invest $10 billion into Anthropic, and Microsoft will invest $5 billion into Anthropic.
• Concern: This "circular thing" raises concerns, particularly from Winthrop Capital Management's CIO, Adam Coons. Coons points to "shenanigans" observed during the dot-com era and expresses a need for "some concern" and "some doubts" in investing. He likens Nvidia's broad investments to a "modern day version of Berkshire Hathaway," acknowledging their substantial capital and the inherent risk in investing in numerous companies, referencing Google's past divestment of nearly 300 unsuccessful ventures.

The Case for a Bubble

The argument for an AI bubble is presented with several key points:

• Concentration: A significant portion of investment is focused on a few key players.
• Stretched Valuations: Valuations are perceived as high, with the term "valuation" being frequently discussed.
• High Investor Sentiment & FOMO: Investors exhibit a strong "FOMO mentality," leading to aggressive buying of AI stocks.

The Case for a Boom

Conversely, the argument for an AI boom emphasizes the following:

• Eyeballs vs. Earnings: Unlike the dot-com era, which was driven by user acquisition ("eyeballs") with little underlying revenue, current AI companies have "real earnings" stemming from "real demand." This is identified as the "biggest difference."
• Reasonable Valuations: Valuations are not considered "outrageous" when compared to the dot-com boom, where companies traded at "100 times earnings." Google, for instance, is noted to be trading at mid-20s earnings, which is deemed "fairly okay."
• Early Innings: The AI story is described as being in its "very early innings," making direct parallels to the internet boom difficult, though acknowledging that some elements of business (selling to each other) are present. The speaker asserts that "AI as a whole is definitely not in a bubble" and will be a continuously utilized technology.

Asset Allocation Strategy

Adam Coons outlines his firm's asset allocation approach:

• Neutral Stance: The firm is currently at a "neutral" asset allocation. This is attributed to a "larger macro view" where, despite a "fight for narrative," there's no "high conviction in one area."
• High Conviction Against Small Caps: A strong conviction exists in "staying away from small caps." This is due to being in the "late stages of the cycle" with "a lot of unknowns," leading to a preference for "large mega caps."

Top Investment Picks and Rationale

The discussion then shifts to specific investment recommendations:

• Google: Identified as the "number one pick." The rationale is that AI is enhancing an "already existing business model that is working." Six months prior, Google was perceived as threatened by AI, but now it's considered a "premier pre-eminent AI pick." Berkshire Hathaway's significant investment in Google is also noted.
• Microsoft: Mentioned alongside Google as a prime example of a company whose existing business model is being enhanced by AI.
• Cybersecurity (Fortnite and Crowdstrike): These are mentioned as areas of interest, though specific details are not elaborated upon due to time constraints.
• Reddit: The speaker expresses a liking for Reddit, having traded it with subscribers.
  • Caveat: The primary concern is "volatility," necessitating "position sizing accordingly" with smaller holdings compared to a stock like Google.
  • Strengths: The "story," "user base," and efforts to "mold and change their UI" to increase ad revenue are praised.
  • Outlook: There's a possibility of Reddit being "taken out" (acquired), but the belief is that it can "survive well on its own making partnerships." It's also identified as a "beaten down stock" offering value in the current market.

Conclusion

The conversation concludes with a strong emphasis on the distinction between the speculative "eyeballs" focus of the dot-com era and the current AI landscape, which is underpinned by "real earnings" and "real demand." While acknowledging concerns about valuations and investor sentiment, the prevailing view presented is that AI is in its early stages of a significant boom, with established companies like Google and Microsoft well-positioned to benefit from AI's integration into their existing, successful business models. The asset allocation strategy favors large-cap companies due to late-cycle economic conditions, with a cautious approach to smaller, more volatile stocks.