FROM AI SELF-EFFICACY TO INNOVATIVE WORK BEHAVIOR: THE MEDIATING ROLE OF AI JOB CRAFTING AND THE MODERATING ROLE OF PSYCHOLOGICAL SAFETY

Abstract

Artificial intelligence (AI) has been reshaping the landscapes of work, both unlocking new realms of opportunity and presenting new challenges to employees as they navigate the changing dynamics of confidence, motivation, and adapting to work done with the support of AI. This study not only uncovers the role of AI self-efficacy (AISE) and learning goal orientation (LGO) as predictors of innovative work behavior (IWB) via AI job crafting (AIJC) but also explores whether psychological safety (PS) serves as a facilitator between the relationship between AIJC and IWB. Based on Social Cognitive Theory (SCT), AI self-efficacy and learning goal orientation are defined as personal factors, while AI job crafting is defined as a pro-active behavioral mechanism, psychological safety is defined as a contextual condition, and innovative work behavior is defined as behavioral outcome. The time-lagged survey study design was used and was quantitative and explanatory in nature among employees in Pakistani organizations that were using AI based or AI supported technologies. Data was gathered in three waves and 350 usable responses were kept for data analysis. Partial least squares structural equation modeling (PLS-SEM) was used to test the hypothesized relationships. The findings show that there are positive relationships between AI self-efficacy and AI job crafting, between AI learning goal orientation and AI job crafting, and between AI job crafting and innovative work behavior. AI job crafting also mediates the relationships between both AI self-efficacy and learning goal orientation and innovative work behavior. Moreover, psychological safety positively moderates the relationship between AI job crafting and innovative work behavior, meaning that the more psychologically safe they feel, the stronger the effect of AI job crafting is on innovative work behavior. The conditional indirect effects further demonstrate that the indirect effects of AI self-efficacy and learning goal orientation on innovative work behavior through AI job crafting become stronger under higher levels of psychological safety. The results in general suggest that innovation in AI-enabled workplaces does not only rely on employee confidence and motivation to learn but also on how proactively employees are adapting their work and on the psychological safety that supports work behaviors to become innovations.