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Global – October 27, 2026 -- Alteryx argues that unpredictable output, not token cost, is the main barrier to scaling AI agents in the enterprise: the same request to a large language model can return a different answer each time.

Token burn rises with agent complexity, but variance is the bigger problem

Agents must reason through business logic, infer context, read results and choose the next action, sometimes several times in a single instance. Restarting a process or re-deriving business logic adds to token costs. Alteryx says the larger obstacle is that LLMs generate outputs from a probability distribution. In its words, "you cannot scale a business on randomness."