Wednesday, 10th June 2026
Anthropic announced two weeks ago that its run-rate revenue crossed $47 billion. With most of the coverage focusing on numbers like these, it’s easy to forget the companies that are sitting on the other side of this bill, actually spending all this money on tokens.
To put the number in perspective, Anthropic’s current run-rate revenue alone is roughly half the size of the entire global CRM market. Together with others like OpenAI and the AI revenue flowing through Amazon Web Services (AWS), Google Cloud, and Microsoft Azure, the total token spend is approaching the size of software categories like CRM and ERP systems that took decades to mature.
Almost every company agrees it needs some form of CRM or ERP system, and no one has to justify the existence of that line item. For AI, however, the case is much less settled, and CFOs are now demanding to see ROI on token spend, which can be genuinely hard to measure or attribute with general-purpose tools like Claude or ChatGPT.
On top of that, current changes to pricing models make budgeting and buying decisions even harder for enterprises. In a Stratechery interview last week, Satya Nadella described the future of software pricing as hybrid, combining a per-user model with a consumption model, because “there is real marginal cost to software” now, and that cost will be priced through. But enterprises are used to per-seat licenses and like them precisely because they are predictable. Ironically, many vendors are now moving toward usage-based pricing to control their own costs, just as buyers are asking for predictability.
Therefore, I doubt that frontier-lab revenue will continue to grow as steeply as it has over the past few months, and we might reach a temporary plateau due to uncertainty. I am convinced that this presents an opportunity for startups offering purpose-built AI systems focused on solving specific business problems, with a much more predictable pricing model and cost structure.