Fostering self-management competencies through AI-based coaching: mechanisms of inhibition and approach motivation, and intrinsic goal motivation

Artificial intelligence (AI)-based coaching helps individuals attain their goals, yet its effects on self-management and the mechanisms underlying these effects remain poorly understood. Self-management includes self-regulation, self-access, self-control, and volitional facilitation. We hypothesised that the anonymous and nonjudgmental nature of AI-based coaching reduces inhibition and fosters approach motivation, activating intrinsic goal motivation and supporting self-management processes. In a quasi-experimental controlled trial (N = 111), we compared an AI-based coach (chatbot) with a self-coaching intervention (control condition). No significant Condition × Time interactions were observed for the outcome variables. Exploratory pairwise comparisons indicated improvements in self-regulation in both conditions. Within-group patterns suggested increased volitional facilitation following AI-based coaching and increased self-access following self-coaching. No significant effects emerged for self-control. Path analyses revealed that during coaching, chatbot users felt less inhibited and more approach-motivated than self-coaching users, which boosted their motivation to work on their goals and strengthened self-management. The findings suggest that AI-based coaching may foster self-management and that these effects may emerge through motivational processes. Whether the relationship plays a less central role in AI-based coaching than in human coaching remains an open question.