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Research Paper | Computer Science and Engineering | Volume 15 Issue 3, March 2026 | Pages: 261 - 269 | India
Green AI: Strategies for Mitigating Carbon Footprints in Machine Learning Systems
Abstract: The rapid growth of artificial intelligence (AI) and machine learning (ML) has raised critical concerns about their environmental impact, as training and deploying large-scale models demand vast computational resources and produce significant carbon emissions. Early research (2020-2022) diagnosed these challenges by quantifying AI's carbon footprint, exposing the lack of transparency in energy reporting, and proposing initial efficiency measures. More recent studies (2023-2025) have advanced mitigation strategies, including algorithmic innovations such as pruning and transfer learning, renewable-powered infrastructures, and lifecycle-aware deployment practices, while also embedding Green AI principles into sectors such as energy, healthcare, logistics, and corporate governance. Despite this progress, efforts remain fragmented, with persistent trade-offs between performance and sustainability, limited standardization, and uneven institutional adoption. This paper synthesizes developments across the last five years to provide a comprehensive understanding of Green AI. It identifies the main sources of AI's carbon footprint, evaluates mitigation strategies, and highlights sectoral applications, while critically examining the challenges and trade-offs that persist. Finally, it proposes a roadmap for embedding sustainability across the AI lifecycle-spanning algorithm design, infrastructure optimization, lifecycle management, and policy alignment. By reframing AI success metrics to balance performance with environmental responsibility, this study positions Green AI not only as a technical adjustment but as a foundational principle for sustainable digital transformation.
Keywords: Green AI, Sustainable machine learning, Carbon footprint reduction, Energy- efficient algorithms, AI governance
How to Cite?: Mayur S. Gawali, Amit K. Mogal, "Green AI: Strategies for Mitigating Carbon Footprints in Machine Learning Systems", Volume 15 Issue 3, March 2026, International Journal of Science and Research (IJSR), Pages: 261-269, https://www.ijsr.net/getabstract.php?paperid=SC26211100444, DOI: https://dx.doi.org/10.21275/SC26211100444