The Future of AI Investment: Contrarian Theses and the Red Queen Effect

The Future of AI Investment: Contrarian Theses and the Red Queen Effect

Introduction:
As the field of artificial intelligence (AI) continues to advance, early-stage investors are faced with the challenge of identifying the most promising investment opportunities. In this article, we will explore five contrarian theses for AI investment and discuss how the Red Queen Effect applies to the evolving landscape of technology and corporate finance.

1. Horizontal LLMs will lose, vertical LLMs will prevail:
   The first contrarian thesis suggests that horizontal language models (LLMs) will lose their dominance as a new and superior technology emerges. Many AI experts believe that LLMs alone will not lead us to artificial general intelligence (AGI). Instead, breakthroughs will come from novel approaches rather than simply accumulating more data. Furthermore, it is argued that vertical LLMs, tailored for specific applications, may be more effective than a single horizontal LLM. This shift in focus highlights the importance of specialization in AI development.

2. AI will impact specific companies, not entire markets:
   Unlike previous waves of technological advancements, AI is expected to have a targeted impact on specific companies rather than revolutionizing entire markets. The essence of AI lies in applying intelligence and learning to different stages of a company's value chain. Therefore, companies with value chains that are more adaptable to AI integration will benefit the most. It is not the industry itself that matters, but rather the alignment of steps in the value chain for optimal AI utilization. This insight challenges the conventional understanding of how AI will shape industries.

3. AI will erode traditional competitive advantages:
   The third contrarian thesis suggests that AI will undermine many forms of competitive advantage. A prime example is Google's acknowledgment that they have no moat in the AI era. As AI becomes more pervasive, it will level the playing field and disrupt traditional sources of competitive differentiation. Companies will need to adapt and innovate continuously to stay ahead. This thesis highlights the importance of agility and responsiveness in the face of AI-driven changes.

4. The bifurcation of the economy into real and AI worlds:
   As AI technologies advance, the economy is projected to split into two distinct realms: the real world and the AI world. This fourth thesis anticipates that customer acquisition channels will collapse into AI-driven agents. This means that consumers will increasingly rely on AI agents to perform various tasks, potentially reducing the need for traditional software interfaces. Companies that excel in leveraging AI agents may gain a competitive edge, rendering traditional growth strategies based on product-led growth (PLG) or community-driven go-to-market (GTM) obsolete.

The Red Queen Effect and the Evolution of AI Investment:
The Red Queen Effect, derived from Lewis Carroll's "Through the Looking-Glass," symbolizes the need to constantly adapt and evolve to survive. This concept is highly relevant in the context of AI investment. Just as species must keep running to stay still, investors and companies must continually innovate and keep pace with the rapidly evolving AI landscape.

The Red Queen Effect reminds us that relying solely on traditional metrics, such as earnings reported in corporate financial statements, may no longer be sufficient to determine the true value of an investment. Instead, investors must embrace a dynamic approach that considers the potential for co-evolution with the AI systems they interact with. Those who are more responsive to change and can exploit the opportunities presented by AI are more likely to thrive in this new paradigm.

Actionable Advice:

1. Embrace specialization: Instead of solely focusing on horizontal AI technologies, explore vertical LLMs tailored to specific applications. Look for companies that understand the nuances of their value chain and can effectively deploy AI in those areas.

2. Foster adaptability: Encourage a culture of agility and responsiveness within companies. Invest in organizations that prioritize continuous innovation and are willing to adapt their business models to leverage AI advancements. This will help them navigate the erosion of traditional competitive advantages.

3. Embrace AI agents: Recognize the increasing importance of AI agents in customer acquisition and engagement. Identify companies that are at the forefront of developing AI-driven agents and understand how to integrate them into their business strategies.

Conclusion:
As AI continues to reshape industries and investment landscapes, early-stage investors must embrace contrarian theses and remain adaptable to stay ahead. Horizontal LLMs may lose their dominance to new technologies, and AI will have a targeted impact on specific companies rather than entire markets. Competitive advantages will erode, and the economy will bifurcate into real and AI worlds. By understanding the Red Queen Effect and taking actionable steps to specialize, foster adaptability, and embrace AI agents, investors can position themselves for success in the evolving AI-driven economy.