AI Is Not an Employee: Workplace Mental Models and the Context Discovery Gap in Human-AI Interaction

AI adoption can falter not because systems lack capability, but because organizations apply employee mental models to systems that do not participate in work as socially embedded employees. This article develops a theoretical model of that mismatch, drawing on theory of mind, psychological contracts, shared mental models, transactive memory, and automation reliance research. It introduces the context discovery gap: a mismatch between the organizational context people assume AI already has or will discover and the context it can actually obtain and use in a workplace. Employee-associated expectations may contribute to this mismatch by leading users to leave relevant background unstated. The article argues that the missing psychology of AI adoption lies in the human assumptions through which AI systems are understood, delegated to, and evaluated. As a conceptual contribution, it connects these assumptions to context provision and reliance, develops testable propositions, and identifies responsibilities for designing and maintaining context discovery.