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Machine Learning for Environmental Sustainability in the Corporate World

R. Gera, Somnath Banerjee, Divya Valsala Saratchandran, S. Arora, Anumaan Whig

2025Advances in business strategy and competitive advantage book series41 citationsDOI

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.

Topics & Concepts

SustainabilityTransformative learningEnvironmental economicsBusinessResource efficiencySustainable developmentResource consumptionResource (disambiguation)Supply chainCorporate sustainabilityProcess managementEnvironmental resource managementComputer scienceEconomicsMarketingPolitical scienceLawBiologyPedagogyPsychologyEcologyComputer networkUAV Applications and OptimizationCOVID-19 impact on air qualityImpact of Light on Environment and Health
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