AI Enabled Industry 4.0 Practices for Enhancing Sustainability Performance: Evidence from Manufacturing Firms in an Emerging Economy

This study explores how AI-enabled Industry 4.0 technologies would improve SP among manufacturing companies in Bangladesh. Based on six major dimensions ASM, IoT, BDA, CPS, DSCI, and ERE the study examines the impact of AI-led digitalization on the economic, environmental, and social aspects of sustainability. Quantitative research design was used and the data gathered through structured questionnaire based on five-point Likert scale, using managers and executives. One hundred and seventy-seven valid responses were acquired using convenience sampling. Twelve hypothesized relationships were evaluated with PLS-SEM with SmartPLS 4. The empirical results show that the six Industry 4.0 dimensions influence sustainability performance in a significant positive way with the strongest effects observed in Energy Resource Efficiency, Cyber physical systems, and the Internet of Things. The model proved to be able to explain a lot, with a value of R2of 0.87, which means that the variables to be described explain a significant part of sustainability performance. In practice, the findings suggest that manufacturing companies can achieve an opportunity to enhance both the efficiency and environmental results of operation through attention to energy-efficient and AI-oriented projects. Furthermore, the implementation of these technologies leads to the workplace safety and increase in social responsibility. The research contributes to the current body of literature as it considers several AI-based Industry 4.0 technologies simultaneously in the framework of an emerging economy, thus providing information about their interactions and additive and synergistic impacts on sustainability. Nevertheless, the cross-sectional nature and use of self-reported data do not allow causal inferences. Future study can consider longitudinal or a mixed-method study to argue and further understand these relationships.