Sources: OpenAI is on track to generate annualized revenue of $40B+ based on its current performance, roughly doubling its run rate from the end of 2025
but it's barely turned a profitYoon Kyung-hwan /Seoul Economic Daily:OpenAI Aims to Double Revenue as It Races Anthropic to IPORyu Hyunseokby Hwang Yoonju /The Asia Business Daily:OpenAI Projects $40 Billion in Annualized Revenue as IPO Nears, Accelerating Growth (Comprehensive)
Context & Ripple Effects
OpenAI’s reported run rate had already risen to $25B annualized revenue by late February, after the company said it had passed $20B in 2025. The latest figure extends a rapid sequence of reported revenue milestones rather than introducing a new revenue model.
The growth also sits beside OpenAI’s much larger 2030 revenue projection, while reports that it has barely turned a profit make monetization quality as important as topline scale. The reported race with Anthropic toward an IPO gives that distinction immediate strategic weight.
First-order effects
- OpenAI enters its reported IPO race with Anthropic able to point to a $40B-plus annualized-revenue run rate, but its limited profitability keeps investor attention on the cost of producing that revenue.
- OpenAI’s reported revenue pace materially exceeds its late-2025 level, strengthening the case that its commercial products and computing-capacity sales are scaling quickly.
Second-order effects
- Anthropic faces a more demanding revenue-scale benchmark in a reported IPO race, increasing pressure to demonstrate both growth and a credible path to profits.
- For OpenAI, the gap between revenue growth and profit directs scrutiny toward AI compute costs and the economics of serving customers, not merely customer demand.
Third-order effects
- If leading AI companies keep reaching larger revenue run rates before sustained profits, public-market readiness will increasingly hinge on unit economics and compute commitments alongside growth.
- The pattern points to AI commercialization becoming a capital-intensive contest in which revenue scale and infrastructure costs are evaluated together.
The trend: Generative-AI leaders are turning fast-growing revenue into IPO narratives while investors test whether compute-heavy growth can produce durable margins.