Buyers of AI services are struggling to control costs and sellers are not sure how much to charge.

If you have used a free version of an ChatGPT or its AI rivals, then you are obviously getting a good deal. Firms like Microsoft, Google and Anthropic have invested hundreds of billions of dollars in developing Large Language Models (LLMs) the tech behind those services. So getting, ChatGPT, Claude or Gemini to help with your speech or holiday plans is a bargain. But, naturally, those firms want to recoup their investment, so they offer paid-for versions of their AI, which have extra features for tasks like coding or billing. Meanwhile, third party firms are building and selling services based on AI agents, usually based on an LLM, which are trained to do specific tasks. "Trying to tie someone into a cost model for the next 12 months, two years, three years, it doesn't make any sense, honestly, because we don't know," says Simon Gooch at Saviynt, an identity management company which is incorporating agentic AI into its services. That's because of rapidly changing economics around tokens, the building blocks of LLMs and agentic AI. When a user asks an LLM, like ChatGPT or Anthropic's Claude to answer a question, generate software code, or automate a process, that prompt is broken down into mathematical chunks called tokens, which can be processed by the model.