The 'new' tech companies are able to operate much more efficiently than old ones, says Ray Wang

Key Concepts

• AI Bubble vs. AI Boom: Distinction between a speculative bubble and sustained, fundamental growth in the AI sector.
• Data Center Spending: Significant investment in infrastructure supporting AI development and deployment.
• Concentration in Tech Stocks: High market capitalization of a few major tech companies relative to the broader economy.
• AI-Native Companies: New companies built around AI, characterized by high revenue per employee and rapid growth.
• Digital Labor: The role and impact of AI in automating tasks and augmenting human work.
• Business Outcomes: The focus of current AI development on delivering tangible results and efficiencies for businesses.
• Classical AI vs. Generative AI: Evolution from rule-based AI to AI capable of creating new content and solutions.
• AI Agents: Software entities that perform tasks autonomously, often built on platforms like ServiceNow.
• Diversification in AI Investment: The need to look beyond the top AI-focused companies to capture broader market growth.

AI Sector: Bubble or Sustainable Boom?

Ray Wang, Chairman of Constellation Research and co-founder of an AI forum, discusses the current state of the tech sector, particularly concerning Artificial Intelligence. He addresses the apparent contradiction between the massive $380 billion in data center spending and the concentration of the top ten tech stocks representing $25 trillion of the $30 trillion US economy, which might suggest a bubble. However, Wang argues that it's not a bubble but a fundamental boom.

Evidence for a Sustainable Boom

Wang differentiates between the established tech sector and the emerging AI-native companies. While public markets may show signs of concentration, the real innovation and valuation growth are occurring in the private markets. He points to companies like OpenAI, Anthropic, Perplexity, Midjourney, Cursor, and Replit as examples of AI-native businesses with staggering valuations.

A key differentiator for these AI-native companies is their super efficiency. They achieve remarkable revenue per employee, with some companies having as few as 20 people generating $200 million in revenue, or 10 million people generating $200 million. This high revenue and profit per employee, coupled with the significant amount of digital labor they enable, sets them apart from older tech companies.

Wang asserts that traditional metrics for growth, such as 20% or 30% year-over-year increases, are insufficient. AI-native companies are demonstrating growth rates of 10x or even 100x in their delivery capabilities, which justifies their valuations and indicates a new paradigm for growth.

The Ripple Effect of AI Across the Tech Sector

The impact of AI is not confined to a few dominant players. Wang likens it to a rock thrown into a pond, with ripples benefiting a wide array of companies. He cites examples:

• AMD: Despite Nvidia's dominance in GPUs, AMD is showing significant growth. Lisa Su, CEO of AMD, forecasts 35% year-over-year growth for the next 3-5 years, highlighting the immense market opportunity.
• Cisco: The company has achieved four consecutive quarters of revenue beats, driven by its data center business. This includes networking solutions leveraging Ethernet switches based on Nvidia silicon.
• IBM and Oracle: These companies are also experiencing a resurgence in their data center businesses, indicating a broader trend of modernization across the tech landscape.

Wang emphasizes that this is not just a boom for a select few stocks but a widespread modernization program benefiting the entire tech sector.

Diversification and the Evolution of AI

In light of recent market movements, Wang suggests that investors should consider diversifying beyond the "big five" AI stocks. He advocates for looking at the software side of the house, where AI revenues are increasingly being generated.

The evolution of AI is moving from:

• Classical AI: Where 2 + 2 always equals 4 (rule-based, deterministic).
• Generative AI: Where 2 + 2 might equal 4, but with creative variations (content generation).
• Current AI Focus: Where 2 + 2 equals 4, and the question is "What do you want to do with it?" This signifies a shift towards AI focused on business outcomes.

This new phase of AI is about collapsing decision trees and enabling automation for faster decision-making. Companies like Salesforce and ServiceNow are at the forefront of this movement.

AI Agents and Business Outcomes

Wang highlights the development of AI agents as a crucial component of this new AI paradigm. Private companies like Fox (acquired by ServiceNow, which also acquired Boomi) are building these agents. These agents are designed to drive tangible business outcomes by automating tasks and augmenting human capabilities. The ultimate goal is to enable businesses to achieve specific, measurable results through AI.

Conclusion

Ray Wang's perspective is that the current AI surge represents a fundamental and sustainable boom, not a speculative bubble. This boom is characterized by hyper-efficient AI-native companies and is creating a ripple effect across the entire tech sector, driving modernization and growth. The focus is shifting from AI's capabilities to its ability to deliver concrete business outcomes through automation and intelligent agents, necessitating a broader approach to investment and understanding within the tech industry.