Study of Business Practices of MSMEs applying ‘Green AI’ to Achieve ‘Sustainability’ with Special Reference to Sangli District

Abstract

This research investigates the transformative role of "Green AI" as a strategic driver for the United Nations Sustainable Development Goals (SDGs) within the Micro, Small, and Medium Enterprise (MSME) sector. While MSMEs are pivotal to industrial diversity, they often encounter resource barriers in adopting sustainable frameworks. Through an empirical analysis of 50 MSMEs, this study evaluates how the integration of energy-efficient Artificial Intelligence catalyses progress across a broad spectrum of sustainability targets. The findings reveal that Green AI adoption acts as a "sustainability multiplier," primarily through operational dematerialization and resource optimization. In the environmental domain, AI-driven digital workflows significantly reduced paper consumption (SDG 12 & 15), while the synchronization of Green AI algorithms with solar energy systems maximized renewable yields (SDG 7). Socially, the study observes that AI-powered predictive safety analytics and health monitoring enhanced workplace well-being (SDG 3), and personalized AI-driven learning platforms facilitated continuous employee upskilling (SDG 4). Furthermore, the application of smart sensors improved water-use efficiency (SDG 6), and AI-optimized logistics contributed to reduced urban congestion and emissions (SDG 11). The research concludes that transitioning toward Green AI—focusing on both "Green by AI" applications and "Green in AI" computational efficiency—enables MSMEs to bridge the innovation gap and achieve the 2030 Agenda. These results provide a robust framework for policymakers to incentivize AI-driven sustainability that balances economic growth with social and environmental responsibility.