Why the AI Bubble Hasn’t Popped — ft. Josh Brown | Prof G Markets

Audio Brief

Show transcript
This episode analyzes the current state of the stock market, exploring whether the AI-driven tech rally is a sustainable trend supported by earnings or a speculative bubble waiting to burst. There are four key takeaways from this discussion on market psychology and valuation. First, price action remains the ultimate truth serum, often contradicting bearish media narratives. The podcast highlights a phenomenon called wishcasting, where pundits predict crashes simply because they want them to happen to validate their own underinvested positions. Investors are urged to ignore this noise and instead observe how the market reacts to bad news. If prices stabilize quickly after a negative headline, the bullish trend is likely intact. Second, the current high valuations in the market, specifically a 21 times price-to-earnings ratio, are justifiable if corporate earnings meet growth expectations. The bullish case for 2026 relies heavily on the technology sector delivering nearly 30% earnings growth. While high multiples can signal a bubble, they are mathematically supported as long as the underlying companies continue to expand their profitability at this aggressive pace. Third, artificial intelligence should be viewed as a force multiplier for efficiency rather than just a consumer product. The real return on investment for AI is shifting from novel chatbots to essential utility across boring sectors like biotech and banking. The discussion notes that massive capital expenditures by companies like Amazon and Google are not speculative inventory building but a direct response to enterprise demand. Companies like Palantir act as a tell, proving that businesses are actively paying to solve problems with this new compute power. Finally, young investors in the accumulation phase need a radical mindset shift regarding market performance. If you are under the age of 45 and contributing to a 401(k), rooting for all-time highs is irrational because it makes your future purchases more expensive. These forced buyers should actually hope for corrections or lost decades, which allow them to accumulate assets at a discount and compound wealth significantly when valuations eventually recover. The bottom line is that while media sentiment remains skeptical, the combination of robust earnings growth and the indispensable utility of AI suggests the market's foundation may be stronger than the headlines imply.

Episode Overview

  • This episode analyzes the current state of the stock market, specifically focusing on whether the AI-driven tech rally is a bubble or a sustainable trend supported by earnings.
  • It explores the psychology of financial media, explaining why pundits often "wishcast" for market crashes to validate their own biases, while actual price action tells a different, more bullish story.
  • The discussion breaks down the 2026 market outlook, arguing that high valuations (like a 21x P/E ratio) are justifiable if corporate earnings growth—particularly in the tech sector—meets expectations.
  • It offers a critical mindset shift for young investors (under 45), explaining why they should mathematically root for "lost decades" and lower prices rather than all-time highs.
  • The conversation reframes AI not just as a consumer chatbot product, but as a "force multiplier" for efficiency across "boring" sectors like biotech and banking, which supports continued corporate spending.

Key Concepts

  • Price vs. Punditry: The most reliable market indicator is price action, not media commentary. When negative news hits (like an Oracle dip) and prices stabilize quickly, the market is rejecting the bearish narrative. Much of financial media engages in "wishcasting"—predicting crashes because they want them to happen to justify being underinvested or wrong previously.
  • The "MacGuffin" Theory of AI: Private companies like OpenAI act as a "MacGuffin" (a plot device that drives the story but isn't the main focus). While OpenAI animates the narrative, investors should focus on the "main characters"—public companies like Microsoft, Amazon, and NVIDIA—whose stock prices and transparent financials offer a better "truth serum" for AI adoption.
  • Earnings Growth Justifies Valuations: A high Price-to-Earnings (P/E) multiple is not inherently a bubble if growth supports it. The bullish case for 2026 relies on the expectation that technology sector earnings will grow by nearly 30%, which mathematically supports current high stock prices.
  • The "Forced Buyer" Psychology: Investors in the accumulation phase (under 45) are "forced buyers" via 401(k)s. Therefore, rooting for all-time highs is irrational. Young investors benefit from "lost decades" or corrections, which allow them to accumulate assets at a discount and "slingshot" their wealth when valuations eventually recover.
  • AI as a "Force Multiplier": The true ROI of AI isn't in selling chatbots, but in efficiency layers across all sectors (e.g., accelerating biotech trials, enhancing bank fraud detection). This utility creates a "behavioral lock-in"—if you took AI tools away from knowledge workers today, they would pay a premium to get them back, suggesting a high revenue floor unlike the speculative Dot Com bubble.
  • The "Tell" in Capital Expenditures: Massive spending by "Hyper-scalers" (Amazon, Google) isn't speculative inventory building; it's a response to B2B demand. Companies like Palantir and Accenture act as the "tell"—their growth proves that large enterprises are actively paying to solve business problems with this compute power.

Quotes

  • At 5:08 - "Prices are more important than opinions, and prices represent the sum total of people who actually manage money and are voting with their money." - Explaining why investors should trust charts over "bubble" rhetoric.
  • At 6:55 - "Are they money managers who are overweight small-cap value [and] underweight tech? ... They're wishcasting. They want these stocks to blow up so they can call their clients and say, 'You see, I was right. I'm not a schmuck.'" - Highlight the conflict of interest in bearish market analysis.
  • At 10:21 - "It's the main character in the movie... the thing that animates the actions of everyone else in the movie... [but] OpenAI's share price is not tradable." - Using a film analogy to explain why private catalysts drive the narrative, but public companies provide the investable reality.
  • At 15:55 - "Will the fundamentals continue to justify an above-average price-earnings multiple? That's it. That's the question... If you think the market delivers that [growth], 21 times earnings is justifiable." - Simplifying the complex macro outlook into a single question about earnings growth.
  • At 21:48 - "Palantir is your tell. Amazon is your tell... Amazon, Alphabet, Microsoft are buying GPUs... because their customers want to be able to do more with their data." - Refuting the idea that AI spending is speculative; it connects hardware purchases directly to enterprise demand.
  • At 28:29 - "I take away your LLM usage from your day... What's your experience like relative to what you've just spent the last two years doing? It sucks. You're not going to stop paying for it." - Demonstrating price inelasticity and how AI has transitioned from novelty to essential utility.
  • At 42:30 - "If you know that today [you are a forced saver], are you rooting for all-time highs? Are you mad? Have you lost perspective on time and space? You want lower prices if you're young." - Framing market corrections as necessary opportunities for wealth generation rather than disasters.

Takeaways

  • Ignore the "Bubble" Noise: Stop reacting to media pundits screaming about crashes; instead, watch how price action reacts to bad news. If the market absorbs bad news and stabilizes, the bullish trend is likely intact.
  • Monitor the "Tell" Companies: To gauge the health of the AI trade, don't look at OpenAI leaks; look at the earnings and guidance of "implementation" companies like Palantir and Accenture to see if enterprises are actually spending money on solutions.
  • Change Your Mindset on Corrections: If you are still contributing to a retirement account, actively root for lower prices or a flat market. Stop celebrating all-time highs that make your future purchases more expensive.
  • Focus on the "Boring" AI ROI: Look for investment opportunities in sectors outside of big tech (like biotech or financials) that are using AI to reduce costs and expand margins, as this is where the next phase of value creation ("The S&P 493") may occur.