Leading with algorithms: how AI-enabled leadership fuels employee innovation through creative self-efficacy and process engagement in the ICT sector

Purpose This study aims to examine how artificial intelligence-enabled leadership (AIL) – a leadership approach that integrates algorithmic intelligence with human judgment – shapes employee innovative work behavior (IWB) in digitally intensive organizations. Drawing on social cognitive theory and the componential theory of creativity, the study investigates creative self-efficacy (CSE) and creative process engagement (CPE) as mediating mechanisms and examines the moderating role of CSE in the AIL–IWB relationship. Design/methodology/approach A multi-source, time-lagged research design was employed using data from 504 matched employee–supervisor dyads in the Turkish information and communication technology sector. Employees reported perceptions of AIL, CSE and CPE, while supervisors independently assessed employee IWB. Hypotheses were tested using partial least squares structural equation modeling with 5,000 bootstrap resamples. Findings The results indicate that AIL has a positive effect on employee IWB. This relationship is partially explained by CSE and CPE, with evidence of a sequential mediation pathway whereby AIL enhances CSE, which in turn promotes CPE and innovative behavior. In addition, CSE moderates the direct effect of AIL on IWB, such that the relationship is stronger for employees with higher creative self-beliefs. Originality/value This study advances leadership and creativity research by conceptualizing AIL as a psychologically consequential leadership form. By demonstrating the dual role of CSE and clarifying the cognitive–behavioral pathway linking AIL to innovation, the study provides a nuanced framework for understanding innovation-oriented leadership in algorithmically mediated work environments.