Determinants and Outcomes of AI Adoption in Human Resource Information Systems: A Smart PLS-SEM Approach in Achieving Digital Transformation

Abstract

The purpose of the present research is to examine the factors and consequences of artificial intelligence (AI) usage in the Human Resource Information Systems (HRIS) in the manufacturing industry of Saudi Arabia. Quantitative method was employed to collect data from 156 respondents working in manufacturing sectors and the data have been analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that relative advantage and compatibility have an important and significant positive impact on the adoption of AI, whereas complexity, organizational readiness, and security/privacy issues have negative but less significant implications. The use of AI, in its turn, has a positive effect on such critical workforce outcomes as employee retention, job satisfaction, job involvement, workplace engagement, and productivity. The model has moderate to large explanatory power, explaining up to 66.5 percent of the variance on employee retention. The results signify that the perceived relative advantage/ benefits and compatibility/ organizational fit play a pivotal role in the AI adoption process. Also, AI-enabled HRIS is transformative as it increases workforce stability/ employee retention and performance/ productivity. The study provides valuable data to administrators and policy-makers who may wish to leverage AI to realize sustainable digital transformation within the Saudi Arabian manufacturing industry.