The month Generative AI lost its mojo

2025-06-07 · Source: Marcus on AI · Field: Finance & Economics — Capital Markets & Investment Management, Economic Analysis & Policy, Artificial Intelligence & Machine Learning · Depth: Intermediate, medium

Summary

The generative AI sector is experiencing significant headwinds, suggesting a potential market correction or "mojo" loss. OpenAI is reportedly delaying its IPO until next year, possibly due to an inability to secure a desired \$1 trillion valuation, with advisors cautioning about retail investor enthusiasm. This uncertainty extends to companies associated with AI, including SpaceX, which is down 11.74% for the week and whose \$25 billion bond sale has incurred over \$300 million in paper losses. Major tech stocks like Nvidia (down >8%), Oracle (~22%), Microsoft (10%), and Cerebras (32%) have also seen declines over the last month. Furthermore, US AI policy is criticized for its "draconian" approach to frontier models like GPT-5.6, while medical AI models such as GPT-5, Claude 3.5, and Gemini 2.5 Pro are deemed "not ready" for complex reasoning. Chinese AI models are rapidly gaining market share, contributing to the view that LLMs are becoming a commodity.

Key takeaway

For investors evaluating generative AI companies, the recent market shifts and performance indicators demand a critical re-evaluation of investment theses. You should scrutinize profitability metrics beyond mere revenue growth, considering the immense operational costs and the increasing commoditization of LLMs. Assess the impact of evolving US AI policy and the rapid rise of international competitors. Your due diligence must account for the demonstrated limitations of frontier models in critical applications, mitigating risks associated with overhyped valuations and unsustainable business models.

Key insights

Generative AI's economic viability and technological readiness are facing increasing scrutiny and market skepticism.

Principles

• Revenue growth does not equate to sustained profitability in AI.
• Over-reliance on "tokenmaxxing" is unsustainable for AI business models.
• Frontier AI models still exhibit critical limitations in complex reasoning.

In practice

• Evaluate AI investments based on profitability, not just revenue.
• Diversify AI model usage beyond US-centric providers.
• Stress test frontier AI models for critical applications like medicine.

Topics

• Generative AI
• AI Market Trends
• IPO Delays
• AI Investment
• AI Policy
• Large Language Models

Best for: Entrepreneur, Investor, Consultant, Tech Journalist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Marcus on AI.