Experimental Evaluation of Employee Involvement and Performance Assessment Based on AI Enabled Compensation Constraints over Manufacturing Industry

An organization’s most valuable asset is its people, who are also its most important resource. There is a direct correlation between employee engagement and a company’s capacity to expand and succeed. An organization can get a competitive edge over its rivals by improving employee engagement through compensation management that is boosted by artificial intelligence. In China’s manufacturing sector, this study aims to examine the connection between AI-enhanced pay management, employee engagement, and performance on the job. The data was collected using a survey questionnaire, and the Artificial Intelligence enabled Performance Predictor (AIPP) is the suggested approach. To test its efficacy, it is cross-validated with the traditional Random Forest (RF) learning methodology. Statistical methods were used to analyze data obtained from 180 questionnaires that were sent to workers of manufacturing organizations. The results showed that there is a strong correlation between effective Artificial Intelligence (AI) enhanced restitution management techniques and higher levels of employee engagement and performance. The mediating effect of employee engagement was also positively correlated with these outcomes. The path coefficient was close to 1 and the p-value was 0.000, suggesting that this relationship is statistically significant. These results stress the significance of engagement in raising performance and the value of AI-enhanced pays management in encouraging employee engagement. In addition to adding to the current body of knowledge, the study provides practical insights for organizations looking to use AI-enhanced pay to promote performance and productivity by offering actual proof of the facilitating role of involvement.