Responsible AI and employee service innovation behavior: A sequential mediation model of AI self-efficacy and AI crafting

While the use of artificial intelligence (AI) has become an effective tool for transforming individuals and organizations, adopting a responsible approach to AI systems is imperative. Drawing on conservation of resources theory and social learning theory, this study examines how responsible AI enhances employees' service innovation behavior via employee AI self-efficacy and employee AI crafting, with a particular focus on the moderating role of leader AI crafting. We tested the proposed relationships using structural equation modeling with data collected from 335 U.S. employees working in various service organizations. The findings demonstrate that the indirect effect of responsible AI on employee service innovation behavior is mediated serially by employee AI self-efficacy and employee AI crafting. Furthermore, leader AI crafting strengthens the positive relationship between responsible AI and employee AI self-efficacy. This study contributes to the AI and management literature by highlighting the importance of responsible AI systems in promoting service innovation behavior among employees. This study addresses both theoretical and practical dimensions, as well as proposing directions for future research.