OpenAI’s annualised revenue run rate has surpassed $40 billion, roughly doubling from late 2025, as the artificial intelligence company accelerates its commercial expansion ahead of an expected initial public offering (IPO).
The milestone, reported by Bloomberg, reflects strong demand for OpenAI’s subscription products, emerging advertising initiatives and specialised software, including its Codex coding agent and enterprise-focused ChatGPT Work applications.
OpenAI co-founder and President Greg Brockman told staff in an internal announcement that the company’s monthly revenue run rate increased by more than 20 per cent in July alone, according to Bloomberg.
The latest growth follows comments from Chief Financial Officer Sarah Friar that OpenAI ended 2025 with an annualised revenue run rate of more than $20 billion.
OpenAI is also facing intensifying competition from Anthropic, which has rapidly expanded its presence in the enterprise market and has reportedly filed confidential paperwork for a potential public listing as early as this autumn.
Anthropic reported a $47 billion revenue run rate in May. However, Bloomberg noted that differences in accounting methodologies between the privately held companies make direct comparisons difficult.
The rivalry has prompted OpenAI to adjust its pricing and sales strategy as it seeks to maintain market share against established technology companies and lower-cost international AI competitors.
The company has reduced prices for some AI models to attract developers, while also strengthening its enterprise sales operation. It recently appointed a veteran cybersecurity executive as its second chief revenue officer in less than a year.
The surge in revenue underscores the rapid commercialisation of generative AI, with companies increasingly generating income from both consumer subscriptions and enterprise applications.
As OpenAI and Anthropic move towards possible Wall Street listings, investors are expected to assess whether their rapid revenue growth can be sustained amid the substantial costs associated with developing, training and deploying increasingly sophisticated AI models.
