Anthropic plans to assert to IPO investors that its AI serviceable annual revenue opportunity exceeds $30 trillion, calculated based on the total amount of human work that the model can theoretically accomplish, rather than traditional software subscription or cloud service spending markets.

Reportedly, the company is considering raising up to $100 billion at a valuation of around $2 trillion; if this financing materializes, it will surpass SpaceX's previous IPO financing record of about $86.2 billion. The aforementioned plans are still in the preparation and banker discussion stage and have not been submitted or priced for public offering terms.

The $30 trillion TAM is not a forecast of Anthropic's near-term revenue but rather a theoretical revenue ceiling if the company captures all work that can be done by AI. This calculation path differs from traditional bottom-up market size calculations: the latter counts enterprise software, cloud computing, or AI budgets, while the former incorporates the labor value of tasks that can be automated into the serviceable market.

Anthropic's annualized revenue run rate exceeded $65 billion by the end of July, growing more than 7 times from about $9 billion at the end of 2025; comparing $65 billion to $30 trillion, the company's current theoretical market penetration rate is about 0.22%. This revenue is a run rate rather than audited full fiscal year revenue, and different media have varying interpretations of its statistical timing and criteria.

The company's internal target points to a revenue range of $190 billion to $200 billion by 2028. Even if it reaches $200 billion, based on the $30 trillion theoretical TAM, the penetration rate would be about 0.67%; however, whether the revenue target is achieved depends on corporate procurement, model performance, inference costs, competitive landscape, regulatory requirements, and the proportion of AI savings that customers convert into vendor spending.

Anthropic's market size argument is said to be partly based on its Economic Index framework: this framework maps model usage to approximately 20,000 occupational tasks in the U.S. Department of Labor's O*NET database and estimates that the proportion of work that AI can theoretically handle in occupational categories such as computer, mathematics, and finance can exceed 80%, with some indicators approaching 94%. Tasks that can be assisted or completed by the model do not equate to the corresponding job wages being fully converted into Anthropic's revenue.

In market mechanisms, the $30 trillion narrative shifts investor attention from current revenue multiples to labor substitution space: if corporate buyers aim to reduce costs in customer service, coding, documentation, analysis, and backend processes, they will shift budgets from wages, outsourcing, and traditional software to model invocation, AI applications, and computing power; the beneficiaries are companies that control models, GPUs, cloud computing, and enterprise distribution channels, while the pressured parties are repetitive white-collar services and low-value outsourcing that can be standardized and split. Whether model suppliers can capture most of this value depends on whether they have customer relationships, workflow control, and ongoing pricing power. fortune+1

Source: Public Information