AI-driven high-performance work systems and human-centric enablers: evidence from an emerging economy

Abstract

Purpose As Artificial Intelligence (AI) continues to reshape organizational structures and processes, understanding its integration with human capital factors becomes crucial. This study examines the associations between Applied Artificial Intelligence (AAI), Digital Literacy (DL), Job Autonomy (JA), Employee Empowerment (EE), and the perceived effectiveness of High-Performance Work Systems (HPWS) in Pakistan’s manufacturing sector. It further investigates EE as a moderator of the relationships between AAI, DL, JA, and HPWS effectiveness. Design/methodology/approach A cross-sectional quantitative study design was employed to achieve the study objectives. Data were collected from employees in AI-adopting manufacturing firms via purposive sampling. Partial Least Squares Structural Equation Modelling (PLS-SEM) was conducted to test the validity, reliability, and construct validity of the study’s measurement and structural models, as well as the significance and strength of the relationships. Findings The findings indicate that the integration of AI, employees’ digital competencies, and job autonomy significantly enhances employees’ perceptions of HPWS effectiveness. Psychological empowerment plays a pivotal role, exerting a direct positive effect on the effectiveness of HPWS while also strengthening the positive influence of AI use, digital literacy, and job autonomy. These results suggest that technological adoption alone is insufficient; organizations must simultaneously cultivate empowered, digitally capable, and autonomous workforces to fully realize the benefits of AI-enabled work systems. Practical implications The findings offer practical implications for managers, emphasizing the need to complement AI adoption with empowerment-oriented HR practices to maximize the effectiveness of AI-driven work systems. Originality/value This study provides one of the early empirical examinations from a resource-constrained emerging economy, highlighting that the effectiveness of AI-enabled HPWS depends on the alignment between technological capabilities and human-centered enablers. By adopting a socio-technical perspective, it demonstrates that AI-driven transformation yields stronger outcomes when supported by digitally competent, autonomous, and empowered employees. The findings offer practical implications for managers, emphasizing the need to complement AI adoption with empowerment-oriented HR practices to maximize the effectiveness of AI-driven work systems.