The relationship between artificial intelligence and civil servants’ work performance: a chain mediation model of self-efficacy and innovation ability

Abstract Background: As direct providers of public services and key agents of social governance, civil servants have experienced significant changes in their roles and work behaviors under the wave of digital transformation in the public sector, driven by modern information technologies such as artificial intelligence(AI). However, there remain few studies exploring how AI has influenced civil servants’ work performance and through what mechanisms these effects occur. Therefore, this study investigates the relationship between AI application and civil servants’ work performance, focusing on the mediating roles of self-efficacy and innovation ability, as well as the moderating role of willingness to change. Methods: A quantitative research design was adopted in this study. Data were collected through an online questionnaire from 296 civil servants. The empirical analysis employs a structural equation model, chain mediation model, moderation model, and bootstrap method, with all statistical procedures conducted using Stata 16. Results: The findings confirmed that: AI application was positively correlated with civil servants’ work performance; self-efficacy and innovation ability mediated the relationship between AI application and work performance; A chain-mediating effect through self-efficacy and innovation ability was observed in this relationship; Willingness to change exerted a moderating effect on the relationships between AI application and innovation ability, as well as between self-efficacy and innovation ability. Conclusion: This study offers a novel perspective for understanding the behavioral motivations and underlying logic of civil servants amid the digital transformation in the public sector, by emphasizing the impact of AI application, the mediating effects of self-efficacy and innovation ability, and the moderating role of willingness to change. These findings provide beneficial insights for civil servants and policymakers, underscoring the importance of prioritizing and accelerating the learning of AI and the enforcement of AI-related competencies. Further, the study offers practical recommendations from the perspectives of fostering an innovation-oriented institutional environment and stimulating individual motivation for technology adoption.