Impact of AI-Driven Human Resource Analytics on Employee Performance and Organizational Effectiveness in Bangladesh
Department of Management, University of Dhaka, Dhaka, Bangladesh.
* Corresponding Author
ORCID Details
Sheikh Jahid Hasan Prince: https://orcid.org/0009-0005-9503-0265
Research Article
International Journal of Scholarly Research in Engineering and Technology, 2026, 08(01), 038–047.
Article DOI: 10.56781/ijsret.2026.8.1.0021
Publication history:
Received on 17 July 2026; revised on 29 August 2026; accepted on 31 August 2026
Abstract:
Artificial intelligence is increasingly transforming human resource management by enabling data-driven workforce planning, performance assessment, and organizational decision-making. This study examines the relationship between AI-driven human resource analytics, employee performance, and organizational effectiveness in the context of Bangladesh. A structured synthetic dataset comprising 2,000 employee-level observations was analyzed using reliability analysis, descriptive statistics, correlation analysis, variance inflation factor assessment, multiple regression, mediation analysis, and machine-learning techniques. The measurement constructs demonstrated strong internal consistency, with Cronbach’s alpha values ranging from 0.845 to 0.932. The results revealed a significant positive association between AI-driven HR analytics and employee performance (β = 0.417, p < 0.001). The organizational effectiveness model further showed that both AI-driven HR analytics (β = 0.208, p < 0.001) and employee performance (β = 0.390, p < 0.001) were significant predictors. Mediation analysis indicated a significant indirect relationship between AI-driven HR analytics and organizational effectiveness through employee performance, with an indirect effect of 0.101 and a 95% bootstrap confidence interval of 0.083–0.122. Predictive modeling provided additional evidence, with Ridge regression achieving test R² values of 0.333 for employee performance and 0.447 for organizational effectiveness. These findings demonstrate the analytical potential of AI-enabled HR practices for understanding workforce and organizational outcomes. However, because the dataset is synthetic, the findings should be interpreted as methodological evidence rather than direct empirical generalizations about Bangladeshi organizations
Keywords:
Workforce Intelligence; Predictive Modeling; Employee Engagement; Organizational Support; Digital Transformation; Decision Support
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Copyright © 2026 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0