Abstract: In the context of digital and AI-driven environments, enhancing leader humility and leveraging its benefits to foster career sustainability have become critical challenges in organizational management. Existing research has primarily examined leader humility in traditional work settings, offering limited practical guidance for cultivating humility in AI-integrated organizations. Recent studies suggest that conventional leadership approaches are no longer sufficient for managing AI-driven workplaces and call for an expanded conceptualization of leadership (AlNuaimi et al., 2022). Responding to this call, this study redefines leader humility in the digital era by incorporating humility toward both employees and AI. In navigating human-AI collaboration, humble leaders should remain people-centered while strategically leveraging digital intelligence to support employee growth rather than replacing human contributions.
Furthermore, prior research on the antecedents of leader humility has predominantly focused on individual leader traits, such as a growth mindset, while overlooking bottom-up influences from employees and the role of AI-generated feedback. This gap limits the practical recommendations for fostering leader humility in AI-driven organizations. In the digital workplace, leader humility extends beyond interpersonal interactions to include humility toward AI, emphasizing the importance of balancing human-machine interactions. Grounded in feedback intervention theory, this study examines how different sources of negative feedback—employee-driven versus AI-generated—affect leader humility. It further uncovers two key mechanisms: perceived face loss and self-reflection, which mediate this relationship. Additionally, it investigates the moderating effect of leader self-attribution, shedding light on its role in shaping how leaders interpret and respond to negative feedback. These findings address the previously overlooked influence of AI in shaping leader humility, offering both theoretical and practical insights into fostering leader humility in AI-integrated workplaces to support career sustainability.
Moreover, existing studies have primarily defined career sustainability in general work environments, adopting a happiness-productivity framework that considers employee well-being and productivity as key indicators (De, Van der Heijden & Akkermans, 2020). Productivity encompasses both job performance and employability, assessing an individual's current work effectiveness and future career potential. Building on this foundation, this study refines the concept of career sustainability in AI-driven workplaces by identifying three key dimensions: employee well-being, job performance, and future career expansion behaviors. The latter is a novel construct introduced in this study, referring to employees' proactive efforts to maintain a competitive edge in AI-integrated workplaces. Employees can achieve this by strengthening interpersonal, teamwork, and communication skills to maximize human advantages while simultaneously improving AI literacy to optimize digital tools for workplace efficiency.
Additionally, existing studies have overlooked how leader humility contributes to career sustainability. Drawing on conservation of resources (COR) theory, this study examines two pathways through which leader humility fosters career sustainability: reducing career replacement anxiety and enhancing relative advantage utilization. Furthermore, this study identifies the moderating role of leaders' digital literacy in shaping these effects. These findings offer new insights into how leader humility influences career sustainability in AI-driven environments, providing a foundation for further research into leadership-driven career development strategies in digital workplaces.
In the era of digital intelligence, career development requires not only external incentives but also internal motivation (Zhang et al., 2021; Chen et al., 2022). Zhang et al. (2021) advocate for integrating self-leadership perspectives into organizational management research to address practical challenges in AI-driven workplaces. However, prior studies have not applied the proactive motivation model to examine how external leadership influences are internalized to drive employees toward career sustainability. This study proposes that leader humility fosters self-leadership by recognizing employees' strengths, learning from employees, and leveraging digital intelligence to identify and support career growth. These mechanisms transform external leadership influence into intrinsic motivation, empowering employees to engage in career expansion behaviors and achieve career sustainability. These findings enrich the understanding of how leader humility promotes self-leadership and provide theoretical insights into career development in AI-integrated workplaces.

Key words: career management, leader humility, career sustainability, digital and AI context, negative feedback