OpenAI gets set to go public: can we entrust the financial markets with ChatGPT and AI?

2026-04-21 · Source: Artificial intelligence (AI) – The Conversation · Field: Finance & Economics — Capital Markets & Investment Management, Economic Analysis & Policy, Corporate Strategy & Leadership · Depth: Fundamental Awareness, medium

Summary

OpenAI, the creator of ChatGPT, is preparing for an Initial Public Offering (IPO) in 2026, marking a significant shift from its original non-profit mission to a market-driven model. Founded in 2015 by Sam Altman and Elon Musk, OpenAI aimed to develop AI for the "common good" and prevent its monopolization. However, the astronomical costs associated with generative AI, including massive computing infrastructure and high R&D expenses, necessitated a hybrid funding model in 2019. Despite a surge in revenue to over $10 billion in 2025, driven by ChatGPT's rapid adoption and diverse revenue streams, OpenAI remains structurally loss-making, with cumulative losses potentially exceeding $140 billion by 2029. The company's reliance on external financing, particularly from Microsoft and Nvidia, highlights its industrial dependency and the "invisible tax" paid to infrastructure providers. Internal governance tensions, exemplified by the November 2023 crisis involving Sam Altman's brief ouster, and intensifying competition from Google's Gemini, Anthropic's Claude, and others, further complicate its position. The IPO is seen as a way to fund investments but may not resolve the underlying economic fragility of generative AI.

Key takeaway

For entrepreneurs considering ventures in generative AI, you must meticulously model the true operational costs, including per-query expenses and infrastructure investments. Your business model needs robust, diversified revenue streams to offset the inherent "cash-burning" nature of large-scale AI. Be prepared for significant capital requirements and potential reliance on major infrastructure partners, which can impact strategic autonomy and long-term profitability.

Key insights

Generative AI's immense operational costs challenge traditional business models, pushing even mission-driven entities towards market-driven financing.

Principles

• Generative AI incurs high marginal costs per query.
• Infrastructure providers profit significantly from AI development.
• Hybrid governance models face inherent tensions.

In practice

• Evaluate generative AI's true operational costs.
• Consider infrastructure provider dependency in AI strategy.
• Diversify revenue streams for AI products.

Topics

• OpenAI IPO
• Generative AI Costs
• AI Market Competition
• Corporate Governance
• GPU Infrastructure

Best for: Entrepreneur, Investor, Executive, Policy Maker

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial intelligence (AI) – The Conversation.