Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Rajagopal, Navaneetha Krishnan; Chib, Shiney; Singh, Anjali; Sasidharan, M.; Chacko, Elizabeth; Nargunde, Amarja Satish Title A name given to the resource AI in Predictive HR Analytics for Talent Management Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Proceedings - 2025 International Conference on Recent Innovation in Science Engineering and Technology, ICRISET 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICRISET64803.2025.11254762" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICRISET64803.2025.11254762</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105031412748?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105031412748?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Rajagopal N.K., University of Technology and Applied Sciences, College of Economics and Business Administration, P.O. Box 608, Salalah, 211, Oman; Chib S., Datta Meghe Institute of Management Studies, Rtmnu, Nagpur, India; Singh A., Gl Bajaj College of Technology and Management, Dms, Greater Noida, India; Sasidharan M., Ck College of Engineering and Technology, Department of Mba, Cuddalore, 607001, India; Chacko E., Christ University, Dharmaram College Post, Hosur Road, Karnataka, Bengaluru, 560029, India; Nargunde A.S., Bharati Vidyapeeth (Deemed to be University), Institute of Management and Rural Development Administration, Department of Management Studies, Maharashtra, Sangli, India Description An account of the resource This paper presents the topic on how Machine Learning (ML) can be used to conduct Predictive HR Analytics to streamline Talent Management practices. The aim of the development of the project is mainly the application of Random Forest as a supervised learning model to forecast turnover of the employees, performance, and career-growth potential. With the historical employee data, such as performance reviews, tenure, and levels of engagement, Random Forest models would help determine the aspects that are significant factors to employee retention and performance. The model is incorporated with HR software solutions such as SAP SuccessFactors that help to gather information seamlessly to make predictions in real-time, and base decisions on data. It can be seen in the findings of this research that this approach to identifying the factors that influence the effort to retain employees based on the likelihood of them leaving was not only more accurate than other methods but much more effective in the retention efforts. Through predictive analytics, organizations are better placed to take the initiative of managing talent, minimizing turnover and streamline workforce productivity, which eventually lead to business success. This research demonstrates that such predictive models based on AI have a high potential to change HR practice. 2025 IEEE. Subject The topic of the resource Employee Retention; Employee Turnover; Machine Learning; Predictive HR Analytics; Random Forest; Talent Management; Workforce Optimization Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833155833-8; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online