OpenAI's house of cards seems primed to collapse

OpenAI has lost its once-dominant position after a string of 2025 setbacks: challenger models from Google (Gemini 3 Pro), Anthropic and Chinese startup DeepSeek have outperformed GPT-5—which users judged a downgrade—helping DeepSeek briefly displace ChatGPT in app downloads and eroding roughly $1 trillion in market value; ChatGPT still has about 800 million monthly users versus Gemini’s ~650 million. CEO Sam Altman has declared a “code red,” instituted reorganizations and is pursuing aggressive scaling—more than $1.4 trillion in recent infrastructure deals—while disclosing OpenAI is targeting roughly $200 billion in annual revenue to reach profitability by 2030 (he said the firm is tracking to >$20 billion annualized now), a precarious position given Google’s diversified cash flows. The rush to outscale is already stressing supply chains and pushing up memory and SSD prices (RAM kits reportedly doubled–tripled, some SSDs +60%), creating inflationary pressures and fueling concerns of an AI-driven asset bubble with sizable systemic downside if it bursts.

Analysis

OpenAI's competitive position deteriorated markedly through 2025 after a succession of product and market setbacks: China's DeepSeek released its R1 chain-of-thought model on January 20 and briefly displaced ChatGPT in US App Store downloads, users reported GPT-5 felt like a downgrade versus GPT-4o, and Google’s Gemini 3 Pro (released November 18) immediately leap‑frogged competitors on LMArena while GPT-5 ranked sixth. Anthropic parlayed model strength into a Microsoft Copilot 365 deal, signaling enterprise demand is migrating away from OpenAI. Sam Altman declared a companywide "code red," instituted temporary reassignments and delayed some products to accelerate improvement.

Usage and financial metrics amplify the risk: ChatGPT reports ~800 million monthly users versus Gemini’s ~650 million (up from 450 million in July), yet OpenAI lacks Google’s diversified cash flows and reportedly needs roughly $200 billion of annual revenue to reach profitability by 2030 while tracking to just above $20 billion annualized today. The company has signed more than $1.4 trillion of infrastructure deals to outscale competitors, a capital‑intensive strategy the article describes as potentially circular and risky. That scale-up is already stressing supply chains: server demand has driven most RAM kits to double or triple in price and pushed some SSD prices up ~60%.

The piece highlights systemic downside if the AI boom reverses — with commentators citing a potential household-wealth hit on the order of $20 trillion — and concludes OpenAI faces execution and funding risk absent rapid product and revenue recovery, while large incumbents and select semiconductor suppliers emerge as differentiated beneficiaries.

Key Decisions for Investors

• Increase selective exposure to Google (GOOGL/GOOG) and Microsoft (MSFT) because Google’s diversified cash flows and Gemini 3 Pro leadership and Microsoft’s Anthropic partnership reduce their execution and funding risk relative to OpenAI
• Avoid initiating new private-market or direct financial exposure to OpenAI and consider reducing credit or equity exposure to companies whose valuations assume OpenAI dominance, given GPT-5’s reception, the company’s heavy >$1.4 trillion infrastructure commitments and the large gap to its $200 billion revenue target
• Consider tactical, sized exposure to NVIDIA (NVDA) and key memory/semiconductor suppliers to capture near-term server demand, while sizing positions conservatively because component price inflation (RAM doubled/tripled, some SSDs +60%) could reverse if capex slows
• Implement macro downside protection or reduce cyclical beta (raise cash or purchase hedges) and monitor leading indicators — LMArena rankings, monthly active user trends, OpenAI revenue milestones, and server-component price movements — as triggers to re‑rate positions