Artificial Intelligence Symbolic Leadership in Small and Medium-Sized Enterprises: Enhancing Employee Flexibility and Technology Adoption - Chunjia Hu; Qaiser Mohi Ud Din; Aqsa Tahir (Systems)
This study examines the influence of leaders’ artificial intelligence symbolization on job-crafting behaviors, highlighting both positive and negative consequences in Chinese small and medium-sized firms. This research utilizes signaling theory to investigate the impact of leaders’ visible adoption of AI on employees’ readiness for change, perceived threats, and job-crafting behaviors. This study examines the moderating influence of organizational support to understand its amplifying and decreasing effects. This work utilizes Python-based statistical tools to provide a novel approach for evaluating behavioral data in social science research. The results reveal that leaders’ AI symbolization significantly improves employees’ readiness for change and promotes proactive job crafting. Conversely, symbolic actions may exacerbate perceived risks, adversely affecting job-crafting behaviors. Organizational support is essential to enhancing the beneficial impacts of AI symbolization on change readiness while alleviating its adverse consequences on perceived threats. These results show how crucial symbolic leadership is for getting people to use new technology and making staff more flexible in SMEs that use AI. By offering organizational training and resources, leaders may optimize favorable results and mitigate adverse effects. This study highlights its significance regarding change readiness, perceived threats, and job crafting. Furthermore, it underscores Python’s (3.9) potential as a groundbreaking tool for enhancing behavioral research in the age of AI.