DOI: 10.7469/jksqm.2026.54.3.555 ISSN: 1229-1889

A Study on the Impact of Problem-Solving Skills among Automotive Manufacturing Workers on Job Engagement and Productivity in an AI-Enabled Environment

Chae Hyun Lee, Seung Kug Kim

Purpose: This study conducts an empirical analysis of the effects of AI literacy, creativity, and social problem- solving skills among automotive manufacturing workers in an AI-Enabled environment on job engagement and productivity, and identifies the moderating effects of age and collaborative problem-solving skills to provide practical and theoretical implications for the development of human capital in the workplace.Methods: Using response data from 158 workers in the automotive manufacturing process, we conducted path analysis using a PLS structural equation model (PLS-SEM) based on R(ver. 4.6.1), between-group comparisons, Pearson correlation analysis, and visualization analysis using Power BI.Results: AI literacy had a direct and strong positive effect on work productivity but did not have a significant effect on job engagement. Meanwhile, creative and social problem-solving skills had a significant positive effect on job engagement but did not have a significant direct effect on work productivity. Furthermore, job engagement had a significant positive effect on work productivity. By age group, the impact of AI literacy on work productivity was stronger among middle-aged and older adults in their 40s and older. Additionally, a moderating effect was observed the higher a group’s collaborative problem-solving ability, the stronger the positive impact of each competency on productivity.Conclusion: In the automotive manufacturing sector during the AI era, it has been confirmed that AI literacy serves as a direct driver of productivity, while creative and social problem-solving skills contribute to performance through distinct pathways that indirectly influence job engagement and productivity.