Sustainable AI: Emerging Trends, Impacts, and Future Challenges

Sustainable AI considers both the environmental impact of AI technologies and their role in advancing global sustainability. This study provides a comprehensive analysis of emerging trends in sustainable AI, highlighting energy-efficient algorithms, green data centers, AI-driven resource management, and ethical governance. It emphasizes AI's dual nature, its potential to drive climate action and socio-economic progress, alongside risks such as carbon emissions, e-waste, and digital inequality. The study underscores the need for interdisciplinary collaboration, inclusive policies, and standardized sustainability metrics to ensure responsible AI deployment. By identifying barriers and proposing strategies, it offers guidance to researchers, policymakers, and industry leaders on aligning AI with long-term environmental, ethical, and social objectives.

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Publication Details

Journal
IEEE Transactions on Sustainable Computing
Published
2025-09-17
DOI
https://doi.org/10.1109/tsusc.2025.3611272
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
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article

Sustainable AI: Emerging Trends, Impacts, and Future Challenges

Jumanne Ally Mohamed, Jianguo Ding, Shepherd Urenje, Feifei Shi et al.
1 citations
IEEE Transactions on Sustainable Computing
Big Data and Business Intelligence
2.28
article

Sustainable AI: Emerging Trends, Impacts, and Future Challenges

Jumanne Ally Mohamed, Jianguo Ding, Shepherd Urenje, Feifei Shi, Doreen Sebastian Sarwatt, Huansheng Ning, Adamu Gaston Philipo, Afidhu Swaibu Yusufu
article en
1 citations

Abstract

Sustainable AI considers both the environmental impact of AI technologies and their role in advancing global sustainability. This study provides a comprehensive analysis of emerging trends in sustainable AI, highlighting energy-efficient algorithms, green data centers, AI-driven resource management, and ethical governance. It emphasizes AI's dual nature, its potential to drive climate action and socio-economic progress, alongside risks such as carbon emissions, e-waste, and digital inequality. The study underscores the need for interdisciplinary collaboration, inclusive policies, and standardized sustainability metrics to ensure responsible AI deployment. By identifying barriers and proposing strategies, it offers guidance to researchers, policymakers, and industry leaders on aligning AI with long-term environmental, ethical, and social objectives.

IEEE Transactions on Sustainable ComputingVol. 10(6)
Uppsala University (SE), Dar es Salaam Institute of Technology (TZ), Blekinge Institute of Technology (SE), University of Science and Technology Beijing (CN)
Openalex Percentile: Top 9%
Big Data and Business Intelligence
2.28
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Sustainable AI: Emerging Trends, Impacts, and Future Challenges — Jumanne Ally Mohamed, Jianguo Ding, et al. · IEEE Transactions on Sustainable Computing (2025) | TGRS Research Map | TGRS