International Journal of Business, Law and Political Science
Vol. 1 No. 12 (2024): International Journal of Business, Law and Political Science

DEVELOPMENT OF AI-DRIVEN WORKFORCE ANALYTICS TOOLS TO IMPROVE TALENT MANAGEMENT, WORKFORCE PLANNING, AND PRODUCTIVITY

Sharma, Rahul (Unknown)



Article Info

Publish Date
28 Dec 2024

Abstract

Objective: Effective talent management and workforce planning are essential for organizational success in the knowledge economy. This research develops AI-driven workforce analytics tools that leverage machine learning to enhance talent acquisition, employee engagement, and productivity optimization. Method: Our integrated platform combines predictive models for employee turnover, performance forecasting algorithms, and skill gap analysis tools to support strategic workforce decisions. The system processes diverse HR data sources including performance reviews, engagement surveys, and productivity metrics to generate comprehensive workforce insights. Results: Deployment in multinational corporations demonstrates 22% reduction in employee attrition, 18% improvement in hiring quality, and 12% increase in overall workforce productivity. Novelty: The study advances HR analytics capabilities and provides evidence-based guidance for talent management practitioners.

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Journal Info

Abbrev

IJBLPS

Publisher

Subject

Economics, Econometrics & Finance Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

Description

International Journal of Business, Law and Political Science - ISSN (Online) 3032-1298 is a peer-reviewed (refereed), open-access journal in the domain of finance and management sciences. IJBLPS seeks to advance multidisciplinary researchers by publishing the highest quality theoretical and ...