HR 4.0 in Manufacturing: Using AI and Big Data to Enhance Workforce Agility and Reduce High Employee Turnover Intentions
Year: 2025
Type: article
Abstract: The human resource management field in manufacturing operations experienced major transformations because of Industrial Revolution 4.0 (IR 4.0) with HR 4.0 as its main advancement combining artificial intelligence systems with big data analytics. The merged system has built organizational employee flexibility and automated HR procedures leading to reduced employee departures. Through the integration of AI in HRM organizations have gained the ability to analyze advanced predictive data alongside improved employee engagement and optimized talent control which has boosted their HR process automation capability. The research evaluates how the implementation of AI algorithms for HR management impacts employee retention outcomes through big data examination. Secondary statistical research of previously collected data examines the part AI technology plays in enhancing employee retention and minimizing staff departures. The paper applies predictive models based on AI algorithms and big data which predict turnover risks. The predictive models assist organizations in detecting risky staff members and facilitate early prevention plans. To evaluate the relationship between AI-powered HR practices and turnover intentions the researchers have applied correlation methods together with regression analysis of Variance (ANOVA) and chi-square testing. The research employs statistical analysis to assess how AI-based solutions impact employee satisfaction levels and efficiency as well as decrease employee turnover rates. The implementation of AI and big data analytics succeeds in both launching employee retention programs effectively and increasing organizational efficiency through improved HR management better decision systems and adaptable workforce models that match Industry 4.0 manufacturing sector requirements. Organizations use these methods to create highly engaged and efficient staff who maintain stability which leads to better productivity and decreased expenses from employee replacement and new hire recruitment.
Authors: Fatima Abrar, Rameez Ahmed, Ikhtiar Ahmed Khoso, Nadeem Farooq, Ikramullah Ibrahimi
Language: English
Topic: AI and HR Technologies
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4407628739