This paper proposes the AI Conversation-Based Action Initiation Barrier Reduction Model, a conceptual framework explaining how casual conversations with artificial intelligence can help individuals begin tasks that they otherwise struggle to start. Many productivity problems arise not from a lack of ability but from psychological barriers that prevent action initiation. These barriers may include task complexity, perfectionism, uncertainty about how to begin, or accumulated mental stress. The model presented in this paper suggests that interacting with AI through informal conversation—such as expressing frustration or casually describing the situation—can reduce these psychological barriers. A key idea of the model is the Peripheral Approach, in which users do not initially ask the AI to perform the task or provide solutions. Instead, they begin with casual dialogue. During this process, thoughts are gradually verbalized, emotional stress is externalized, and the structure of the problem becomes clearer. This naturally lowers the mental threshold required to start working. The paper argues that conversational AI should not be viewed solely as a productivity tool for task execution. It may also function as an action initiation interface that helps users overcome the initial psychological resistance to starting work. Interestingly, the writing of this paper itself began through casual conversation with an AI system, illustrating the proposed model in practice.
Akihito Sugawara (Mon,) studied this question.