According to Forbes, Anthropic surpassed OpenAI for the first time in April 2026 in terms of annualized revenue growth rate, reaching a figure of about $30 billion versus about $1 billion fifteen months ago. The company is aggressively growing corporate sales and focusing on higher margin AI solutions for businesses.
The Forbes publication notes that Anthropic is betting primarily on the enterprise segment, including programming tools and enterprise AI agents. Whereas OpenAI continues to invest heavily in scaling its ChatGPT ecosystem, computing infrastructure and new products.
Earlier, the Financial Times and The Wall Street Journal also reported that Anthropic expects to reach its first profitable quarter as early as the second quarter of 2026. The company estimates that quarterly revenue could exceed $10 billion and operating profit could be around $559 million.
At the same time, OpenAI continues to operate with a high cost burden. Reuters writes that the company forecasts multibillion-dollar losses amid investments in data centers, development of its own chips and expansion of AI-infrastructure.
What’s changing in the enterprise AI market
The divergent strategies of the two largest AI companies reflect a broader shift in the generative AI market. Whereas in 2023-2024, massive user adoption was the primary driver of growth, in 2026 investors are increasingly evaluating the ability of AI companies to create a sustainable business model with controllable costs.
Anthropic promotes Claude as a tool for enterprise automation, programming and business processes, with a focus on cost predictability and AI security.
OpenAI, on the other hand, continues to develop a broader platform model with large-scale computational investments and expansion of the ChatGPT user ecosystem.
For the market, this is becoming an important indicator of the maturity of the AI industry. Investors and corporate clients are beginning to pay more attention not only to the quality of models, but also to the economics of their operation – the cost of implementation, the profitability of AI services, and the ability of companies to scale infrastructure without constantly growing losses.
