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Machine Learning for Environmental Sustainability in the Corporate World
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Author(s): Rashmi Gera (Pt. J.L.N. Government College, India), Somnath Banerjee (Independent Researcher, USA), Divya Valsala Saratchandran (Independent Researcher, USA), Satpal Arora (Ideal Institute of Management and Technology and School of Law, India)and Anumaan Whig (Delhi Technological University, India)
Copyright: 2025
Pages: 20
Source title:
Driving Business Success Through Eco-Friendly Strategies
Source Author(s)/Editor(s): Shrikaant Kulkarni (Sanjivani University, India & Victorian Institute of Technology, Australia), Marco Valeri (Niccolo Cusano University, Italy)and P. William (Sanjivani College of Engineering, India)
DOI: 10.4018/979-8-3693-9750-3.ch015
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Abstract
This chapter explores the transformative role of machine learning (ML) in promoting environmental sustainability within the corporate world. As businesses increasingly embrace sustainable practices, ML emerges as a critical tool for optimizing resource utilization, minimizing waste, and reducing environmental impact. The chapter examines how ML-driven insights enable corporations to identify inefficiencies, predict environmental risks, and implement proactive strategies to achieve eco-friendly goals. Key applications discussed include energy consumption optimization, sustainable supply chain management, and waste reduction initiatives. By leveraging ML algorithms, businesses can transition towards data-driven sustainability models, ensuring long-term viability and compliance with global environmental standards. The chapter also highlights real-world case studies showcasing successful integration of ML into corporate sustainability strategies and addresses the challenges of balancing environmental goals with operational efficiency.
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