The AI Stock Divide: Winners, Losers and 2 Hidden Picks You Need to be Watching.

Key Concepts

• AI Bubble: An investment frenzy leading to a misallocation of capital, where significant funds are poured into AI, with some investments inevitably failing.
• Capital Expenditures (CapEx): Spending by companies on acquiring, upgrading, and maintaining physical assets such as property, buildings, and equipment. In the context of AI, this refers to investments in data centers, hardware, and infrastructure.
• Hyperscalers: Large cloud computing providers that operate massive data centers and offer services to a vast number of users, such as Amazon, Microsoft, and Google.
• Earnings vs. Cash Flow:
  • Earnings: The profit reported by a company, often calculated using accounting principles that spread the cost of long-term assets over their useful life.
  • Cash Flow: The actual movement of money into and out of a company. For large infrastructure projects like data centers, the entire cost is paid upfront, impacting cash flow immediately.
• Capital Light vs. Industrial Firm:
  • Capital Light: Companies that require relatively little investment in physical assets to generate revenue (e.g., software companies).
  • Industrial Firm: Companies that require significant investment in physical assets (e.g., manufacturing, infrastructure).
• AI Winners vs. Losers: Companies that are poised to benefit from the AI boom versus those that are not, often distinguished by their role in the AI ecosystem (recipient of spending vs. spender) and their ability to generate current revenue from AI.
• Canary in the Coal Mine: Stocks that serve as early indicators of broader market sentiment shifts, particularly concerning AI. Declines in these stocks can signal a broader downturn.
• Transformer Models: A type of neural network architecture that has been foundational for the development of Large Language Models (LLMs) and other advanced AI technologies.

AI Winners and Losers: Navigating the AI Boom

This analysis focuses on identifying AI winners and losers in the stock market over the next year, based on recent earnings reports and announcements. The core argument is that while the AI boom is undeniable, the market is becoming more discerning, rewarding companies with tangible AI revenue and current applications over those with speculative future promises.

The AI Bubble: Misallocation of Capital

The widespread enthusiasm for AI has led to predictions of an AI bubble. The transcript defines a bubble not just as soaring prices, but as an "investment frenzy that leads to a misallocation of capital." While hundreds of billions are being invested in AI, some of this capital will inevitably fund "AI losers" and "bad ideas" that will "go up in smoke." The goal for investors is to identify and own the "winners" (like Amazon.com) rather than the "losers" (like Pets.com).

The Current State of AI: Spending Dominates Profits

The recent earnings season has revealed that the AI landscape is currently characterized by significant spending rather than immediate profits. Companies like Meta Platforms and Alphabet have been closely watched for their capital expenditure plans related to AI infrastructure.

• Hyperscaler Spending: The major cloud providers (hyperscalers) are collectively spending approximately $330 billion per year on AI infrastructure, with expectations of further increases.
• Market Impact: These mega-cap tech companies constitute a substantial portion of major market indices. For instance, an S&P 500 index fund holds nearly 30% of its capital in these stocks.

Earnings vs. Cash Flow: A Shifting Financial Landscape

A crucial distinction for understanding the financial health of these tech giants is the difference between earnings and cash flow.

• Earnings Statement: For long-lived assets like data centers (with a 10-year lifespan), only one-tenth of the cost is booked as an expense on the earnings statement each year.
• Cash Flow Statement: The entire cost of the data center is paid upfront, impacting the cash flow statement immediately.

This difference highlights a shift: while these companies report large earnings, their massive AI investments are draining cash. They are transitioning from "capital light cash printers" to resembling "industrial firms" in their capital requirements.

Identifying Winners and Losers: Meta vs. Alphabet

Recent market reactions to earnings announcements provide a clear division between AI winners and losers:

• Meta Platforms: Announced $72 billion in spending through 2025, with 2026 expected to be even larger. The market reacted negatively, with shares dropping over 15%.
  • Reasoning: Meta is primarily spending on AI infrastructure and future development ("AI super intelligence") without generating current revenue from compute. It is seen as an "AI spender" rather than a "recipient of AI spending." Investors recall Meta's costly metaverse venture, making its "super intelligence obsession" sound familiar and risky.
• Alphabet (Google): Announced spending exceeding $90 billion for 2025, an increase from previous projections, with significant plans for 2026. The market responded positively, with shares spiking.
  • Reasoning: Alphabet is both spending on AI and earning from it.
    • Cloud Revenue: Its cloud division grew 34% to $15 billion last quarter, driven by companies hosting AI applications on Google Cloud.
    • Real-World AI Applications: Alphabet is deploying AI to millions of users today. Its Gemini app has 650 million monthly active users, and AI is driving search volumes higher. This demonstrates "real AI today" being more valuable than "promises of a far-off techno future."

Key Takeaway: The market is currently rewarding companies that are recipients of AI spending and those that are generating revenue from AI applications today, rather than those solely focused on future AI development.

Other Notable AI Plays and Warnings

• Amazon: Its cloud division grew 20% last year, its fastest pace since 2022, leading to a surge in its shares after lagging the Magnificent 7 for much of the year. This reinforces the trend of rewarding cloud revenue growth driven by AI.
• Canaries in the Coal Mine (Warning Signs):
  • Coreweave: A cloud play focused on AI computing demand. It is highly leveraged to AI's upside and would be the first to suffer downside. Shares have cooled 15% since the previous week.
  • Palantir: A pure-play AI company deploying machine learning tools. Its shares have reached a lofty valuation (460 times earnings) and are susceptible to a decline in AI sentiment. It is down about 7% after its earnings, though this is considered a "blip" on a long bull run.
  • Significance: These stocks are crucial to watch as they will signal shifts in AI market sentiment.

The Author's Top AI Picks

Based on the analysis, the author presents two favorite mega-cap tech stocks to play the AI boom:

1. Alphabet (GOOGL):
   • Rationale: The author has long advocated for Alphabet as an AI beneficiary, even when others saw it as a threat (e.g., with ChatGPT). Alphabet invented the transformer models that underpin LLMs and its AI tools (Gemini, NotebookLM) are top performers. It has billions of existing users to deploy its AI tools to. Alphabet benefits from both AI spending through its cloud division and its real-world AI applications.
   • Valuation: While trading at around 30 times earnings, it's considered "expensive, but not insane."
2. Cisco (CSCO):
   • Rationale: While Nvidia is the most direct beneficiary of AI hardware, the author suggests Cisco as a better play for investors since July 2024. Cisco's networking equipment is vital for data center buildouts, and its products are gaining market share from Nvidia's networking offerings.
   • Performance: Cisco has provided similar returns to Nvidia and has outperformed it for much of the year.
   • Risk/Reward: Cisco is significantly less risky to own at 18 times earnings compared to Nvidia at 45 times earnings.

Conclusion and Actionable Insights

The market is becoming more rational in its AI investments. The key takeaways for investors are:

• Monitor AI Spend: Keep track of capital expenditures in the AI sector.
• Focus on Winners: Prioritize companies that are recipients of AI spending and those generating current revenue from AI applications.
• Watch Warning Signs: Use stocks like Coreweave and Palantir as indicators of AI market sentiment.
• The Playbook:
  • Alphabet remains a favorite for its dual benefit from AI spend and real-world applications.
  • Cisco offers a less risky, yet rewarding, play on the AI infrastructure buildout.

The transcript also mentions Stansberry Research's development of a quantitative, AI-driven portfolio system that has shown impressive backtested results, outperforming major indices and even Berkshire Hathaway. This system is available at stansberryisystem.com.