Inside the surge in AI token usage

Key Concepts

• Token-Based Pricing: A software pricing model where costs are determined by usage (tokens) rather than seat-based subscriptions.
• Buyer Strike: A potential market phenomenon where enterprise clients refuse to pay escalating costs for AI services.
• Private Markets: The ecosystem of companies (86% of firms with >$100M revenue) that are not publicly traded, requiring specialized financing.
• Private Credit vs. Private Equity: Distinct asset classes; private credit involves lending to companies, while private equity involves ownership stakes.
• K-Shaped Economy: An economic scenario where different sectors or income groups recover or grow at vastly different rates, leading to divergent outcomes.
• ASI (Artificial Super Intelligence): A theoretical level of AI that surpasses human intelligence.

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1. The AI Valuation Bubble and IPO Outlook

The discussion highlights a wave of upcoming public offerings for multi-billion dollar AI companies like Anthropic and SpaceX.

• Valuation Concerns: Experts argue that current valuations are "out of this world." There is significant concern regarding what happens post-IPO, especially as these companies transition from private funding—where they can raise capital quickly to fuel growth—to the public market, which demands quarterly earnings transparency.
• Growth Sustainability: A key comparison is drawn between Snowflake and Databricks. While Databricks is growing rapidly, the sustainability of these growth rates is questioned as enterprise clients begin to scrutinize AI budgets (e.g., capping AI spending at $1,500).

2. The "Token" Business Model Debate

A central tension in the AI industry is the shift from seat-based pricing to usage-based (token) pricing.

• The Cost Problem: As "Agentic AI" (AI that performs tasks autonomously) scales, token consumption is rising astronomically.
• Buyer Strike: Analysts predict a "buyer strike" because enterprise clients are beginning to receive unexpectedly high bills.
• Market Dynamics: The debate centers on whether token costs will decline due to efficiency or if companies will be forced to plateau their usage. Investors are closely watching how these costs impact profit margins, noting that current AI growth is often subsidized by venture capital.

3. The Importance of Big Data

Beyond the hype of AI, the panel emphasizes that "Big Data" remains the foundational requirement for success.

• Data Quality: "If you don't have good data, you don't have good AI." Cleaning and structuring data is described as a difficult but essential task.
• Investment Value: Data-centric companies are highlighted as highly profitable, citing the Blackstone/Refinitiv deal as a prime example of the long-term value of data infrastructure.

4. Private Markets and Credit Dynamics

The discussion clarifies the health of the private market ecosystem.

• Structural Shift: 86% of companies with over $100 million in revenue are private. This has created a massive, necessary ecosystem for private financing.
• Private Credit vs. Equity: Despite concerns about private credit, the data shows continued inflows (18% in Q1). The panel argues that as interest rates remain high, private equity becomes more attractive, and demand for these asset classes is expected to grow rather than decline.

5. Macroeconomic Outlook: Inflation and Jobs

The panel provides a cautious outlook on the broader U.S. economy:

• Sticky Inflation: Inflation is expected to remain "sticky," making it difficult for the Federal Reserve to cut interest rates.
• K-Shaped Economy: The economy is described as "K-shaped," where certain sectors thrive while others face significant pressure.
• Interest Rates: The current mortgage rate environment is deemed unsustainable, but the panel does not anticipate further rate hikes, suggesting a period of stagnation or slow adjustment.

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Synthesis and Conclusion

The primary takeaway is that while the AI sector is currently experiencing a valuation boom, it faces a "moment of truth" as it transitions to public markets. The business model of AI—specifically token-based pricing—is under threat from a potential "buyer strike" as enterprise clients realize the true cost of scaling AI agents. Investors are advised to look past the AI hype toward the foundational importance of Big Data and the structural necessity of private markets, while remaining cautious about the macroeconomic reality of sticky inflation and a K-shaped economic recovery.