The AI Productivity Paradox Is a Feedback Problem

Many organizations report that AI saves time without delivering clearer decisions or better outcomes. This essay argues that the problem is not adoption, skills, or tooling, but a structural failure mode where representations begin to stand in for reality itself. When internal coherence becomes easier than external truth, systems preserve motion while losing their ability to correct. Feedback continues, but consequences no longer bind learning, producing what is described as “continuation without correction.”