Rohan Paul

AI adoption is spreading but AI spending remains concentrated. "The top 10% of customers (in AI) account for 99.5% of model-serving spend and 99% of neocloud spend, leaving the bottom 90% of firms with 0.5% and 1%." - Torsten Slok, Chief Economist/Partner of Apollo The average firm in that top group is spending roughly 1,791x more on inference. For neoclouds, the gap is about 891x. The same calculation is only about 101x for non-AI SaaS and 48x for CRM. Apollo Academy That is a very different economic shape from normal enterprise software. Software scales mostly with seats. AI scales with machine work. 2 companies can both count as "AI adopters," while 1 runs a chatbot a few hundred times a month and the other has agents making millions of model calls every day. They look identical in an adoption chart and completely different in infrastructure revenue. So counting AI customers can now be badly misleading. So the next big unlock should turning today's huge low-spend tail into persistent machine workloads. If ordinary companies start running agents continuously across support, coding, sales, operations and back-office work, infrastructure demand can grow far faster than the number of AI customers, because the real unit of growth is no longer the customer in the AI era. It is the amount of work the machines are doing.