Leaked financial docs show OpenAI is losing billions of dollars a year

2026-06-16 · Source: AI - Ars Technica · Field: Finance & Economics — Capital Markets & Investment Management, Corporate Finance & Treasury · Depth: Fundamental Awareness, short

Summary

Leaked financial documents reveal OpenAI's rapidly expanding revenues are currently overshadowed by even larger expenses, as the company prepares for an initial public offering. Audited statements show revenue surged from \$3.7 billion in 2024 to \$13.07 billion in 2025, with monthly revenues nearing \$2 billion by late 2025. However, research and development costs alone escalated from \$7.81 billion in 2024 to \$19.18 billion in 2025, including \$10.59 billion paid to Microsoft. Total operating losses increased from \$8.78 billion in 2024 to \$20.92 billion in 2025, though improving as a percentage of revenue from 237% to 160%. The 2025 net loss, nearly \$39 billion, includes a \$30 billion accounting charge, making the operational net loss closer to \$8 billion. OpenAI recently raised \$122 billion at an \$852 billion valuation and reports 900 million weekly ChatGPT users, with 50 million paid subscribers, while aiming for profitability by 2030.

Key takeaway

For investors evaluating AI companies like OpenAI, these leaked financials highlight the immense capital requirements for scaling advanced AI. Your investment thesis should account for substantial, long-term R&D and operational losses, even with rapid revenue growth. Expect profitability to be a distant goal, potentially requiring significant cost controls and strategic focus shifts, as seen with OpenAI's move to cut "side quests" and focus on core enterprise users.

Key insights

OpenAI's rapid revenue growth is outpaced by massive R&D and operational costs, leading to significant losses despite high valuation.

Principles

• High growth in AI requires immense R&D investment.
• Inference costs significantly impact product distribution.
• Early-stage AI profitability is a long-term goal.

In practice

• Focus on core users and business applications.
• Evaluate token-based pricing models carefully.
• Prioritize measurable ROI for AI spending.

Topics

• OpenAI Financials
• AI Investment
• Research & Development Costs
• Operating Losses
• Enterprise AI
• IPO Preparation

Best for: Entrepreneur, CTO, VP of Engineering/Data, Investor, Executive, Tech Journalist

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI - Ars Technica.