Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)

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Smart HR Sustainability System using Green AI for Attrition Prediction and Retention Strategy

Authors
D. Punitha1, S. Saffal Bhat2, Shantanu Singh2, *, K. Sunil Kumar2
1Assistant Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Vadapalani, Chennai, 600026, Tamil Nadu, India
2Student, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Vadapalani, Chennai, 600026, Tamil Nadu, India
*Corresponding author. Email: singhshantanu22334@gmail.com
Corresponding Author
Shantanu Singh
Available Online 31 October 2025.
DOI
10.2991/978-94-6463-866-0_29How to use a DOI?
Keywords
Smart HR Sustainability System; Convolutional Nural Network; Talent - engagement Score; HR sustainability
Abstract

In the current fast-paced business landscape, organizations encounter significant challenges related to employee retention and sustainable development. This paper introduces the Smart HR Sustainability System, an AI-powered analytics framework designed to forecast employee turnover, improve retention strategies, and promote environmentally responsible HR practices. The system utilizes machine - learning, deep - learnings, and big data - methodologies to evaluate both structured and unstructured HR data, focusing on elements such as job satisfaction, career advancement, and engagement in sustainability initiatives. The innovative features of this work include the combination of predictive models (Random - Forest, S.V.M, C.N.N) with energy- efficient AI architectures aimed at minimizing carbon emissions. Furthermore, it presents the HR - Sustainability - Index (H.R.S.I) and Talent - Engagement - Score (TES) as metrics for assessing workforce stability and environmental consciousness. This system effectively integrates AI with sustainability in human resources, providing a distinctive, data-driven approach to fostering a greener and more resilient workforce management strategy.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
31 October 2025
ISBN
978-94-6463-866-0
ISSN
2589-4919
DOI
10.2991/978-94-6463-866-0_29How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - D. Punitha
AU  - S. Saffal Bhat
AU  - Shantanu Singh
AU  - K. Sunil Kumar
PY  - 2025
DA  - 2025/10/31
TI  - Smart HR Sustainability System using Green AI for Attrition Prediction and Retention Strategy
BT  - Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)
PB  - Atlantis Press
SP  - 345
EP  - 356
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-866-0_29
DO  - 10.2991/978-94-6463-866-0_29
ID  - Punitha2025
ER  -