Are markets already picking winners & losers in AI?

Key Concepts

• AI Bull Market: The current investment trend focused on Artificial Intelligence technologies and related companies.
• Capex (Capital Expenditure): Funds used by a company to acquire, upgrade, and maintain physical assets such as property, plants, buildings, and equipment.
• Hyperscalers: Companies that provide massive-scale cloud computing services (e.g., Amazon, Google, Microsoft).
• LLMs (Large Language Models): Advanced AI models capable of understanding and generating human-like text (e.g., used in tools like ChatGPT).
• Vibe Coding/Codeex/Cloud Code: Refers to the increasing accessibility of AI-powered code generation tools, potentially disrupting traditional software development.
• Moats: A company’s ability to maintain competitive advantages over its rivals, protecting its long-term profits.
• Personal Intelligence: The concept of AI acting as a personalized assistant, deeply understanding and anticipating user needs.
• AI Safety Trade: Investing in companies positioned to benefit from or address the safety and ethical concerns surrounding AI development.

Market Reaction to AI Investment & Hyperscaler Capex

The discussion begins with the observation that despite recent market downturns, the AI bull market is likely still active. The immediate trigger for the conversation is Amazon’s announcement of a substantial $200 billion capex spend for 2026, significantly higher than previous estimates. This, coupled with Google’s similar increase in capex (over 30% increase this year), is viewed as a positive signal for continued AI buildout. However, the market’s reaction has been negative, with both Amazon and infrastructure players experiencing sell-offs. Doug Clinton attributes this to a general “risk-off” environment and investor uncertainty, rather than a fundamental rejection of the AI trade. He notes investors are reacting to the large capex numbers without fully considering the underlying business fundamentals, exemplified by Google’s strong GCP growth (mid-40% vs. expected mid-30%) and Amazon’s numbers being 2% above street estimates.

Software Selloff & Disruption Potential

The conversation then shifts to the software sector, where a broad selloff is also occurring. Clinton acknowledges the validity of this selloff to some extent, explaining that Intelligent Alpha’s AI-driven stock analysis has identified potential vulnerabilities. He differentiates between software companies likely to be more resilient and those facing greater disruption. Companies like ServiceNow are considered relatively insulated due to the complexity of their offerings. However, companies like Adobe are seen as more vulnerable, as LLMs now allow users to perform tasks previously requiring tools like Photoshop, potentially bypassing Adobe’s services. He emphasizes the need for selective investment within the software space.

Market Timing & Potential Rebound

Clinton cautions against attempting to time the market, noting the difficulty in predicting when the selloff will end. He points to historical examples of “bubble popping” scenarios where rallies can occur even within downtrends, potentially catching short-sellers off guard. He suggests that sentiment may be nearing a washout point, but acknowledges having made similar assessments previously.

Investment Strategies & Emerging Opportunities

Intelligent Alpha is focusing on two key areas for AI-related investments. First, the energy sector, specifically companies involved in powering data centers. The increased capex from hyperscalers necessitates greater energy capacity, benefiting companies like GE Vernova (turbine manufacturers) and Vistra (independent energy suppliers). Second, the “AI safety trade,” focusing on companies with strong competitive advantages (“moats”) and positioning in emerging AI trends. He identifies Google and Apple as prime candidates, particularly in the emerging market of “personal intelligence” – AI acting as a personalized assistant. He believes this market could represent a trillion-dollar opportunity, making Google and Apple relatively safe investments amidst the current uncertainty. He specifically highlights Google and Apple’s potential to dominate the personal intelligence space due to their existing user data and technological capabilities.

Notable Quote

“I think the thing you have to think about with these software names is if you're trying to play, if you're trying to short them, you know, I think you have to be careful in terms of people rushing back into the names when it feels like sentiment has just totally washed out.” – Doug Clinton, emphasizing the risk of shorting software stocks during periods of extreme negative sentiment.

Logical Connections

The discussion flows logically from a broad market overview (AI bull market) to specific examples (Amazon, Google, software selloff) and then to actionable investment strategies. The connection between hyperscaler capex and energy demand is clearly established, as is the rationale for focusing on companies with strong moats in the face of rapid AI development. The conversation consistently returns to the theme of investor uncertainty and the difficulty of predicting market movements.

Data & Statistics

• Amazon Capex: $200 billion for 2026.
• Google GCP Growth: Mid-40% (vs. street expectation of mid-30%).
• Amazon Numbers: 2% above street estimates.
• Hyperscaler Capex Increase: Over 30% increase in capex by both Google and Amazon this year.

Synthesis/Conclusion

Despite current market volatility, Doug Clinton maintains a positive outlook on the long-term prospects of the AI bull market. He believes the recent selloff is driven by investor uncertainty and risk aversion, rather than a fundamental flaw in the AI narrative. His firm is strategically positioning itself to benefit from the increased demand for energy to power AI infrastructure and from the emergence of “personal intelligence” as a key AI application. The key takeaway is the need for selective investment, focusing on companies with strong competitive advantages and exposure to emerging opportunities, while acknowledging the inherent difficulty in timing market fluctuations.