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Sustainability and Digital Transformation: Leveraging AI for Environmental Impact

Author

Listed:
  • Phoebe Koundouri
  • Georgios Feretzakis
  • Antonios Papavasiliou
  • Fivos Papadimitriou

Abstract

The intersection of Sustainability and Digital Transformation exemplifies the role of Artificial Intelligence in leveraging global efforts toward the United Nations' 17 Sustainable Development Goals (SDGs). We provide a systematic review of AI's role-specifically Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and Computer Vision (CV)-in monitoring, modelling, and achieving targets across all 17 SDGs. The analysis is contextualized by two different approaches: the first relates to AI applications in scientific research, and the second explores how AI can be utilized to achieve the targets of an SDG. Regarding the former, it is demonstrated how AI-powered tools for sustainability tracking, human security analysis, and green workforce skills mapping contribute to the scientific research of the Ae4ria research network, a dynamic international scientific research network that pursues a multitude of environmental research goals and activities (Ae4ria.org). As for the latter, a detailed case study on SDG 7 (Affordable and Clean Energy) illustrates AI's technical capability in managing the complexity of modern power systems, using dynamic reserve dimensioning, optimization of continuous intraday trading strategies, and multi-agent reinforcement learning for computing economic equilibria in balancing markets. Yet, despite the breadth and high potential of AI in monitoring, assessing, and ultimately achieving the SDGs, we need to address the policy paradox presented by AI's rapidly growing environmental footprint, particularly the substantial energy demands and carbon emissions associated with data centers and large model training. This highlights the need for innovative policy instruments, such as "Green AI" incentives and governance frameworks, that can promote circular economies for digital infrastructures underpinning the development of AI. Realizing AI's transformative potential is ultimately contingent upon addressing critical economic, institutional, and ethical dimensions, ensuring that its deployment fosters an equitable and truly sustainable digital transition for all.

Suggested Citation

  • Phoebe Koundouri & Georgios Feretzakis & Antonios Papavasiliou & Fivos Papadimitriou, 2025. "Sustainability and Digital Transformation: Leveraging AI for Environmental Impact," DEOS Working Papers 2563, Athens University of Economics and Business.
    • Handle: RePEc:aue:wpaper:2563
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    References listed on IDEAS

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    1. Kristof De Vos & Nicolas Stevens & Olivier Devolder & Anthony Papavasiliou & Bob Hebb & James Matthys-Donnadieu, 2019. "Dynamic dimensioning approach for operations reserves: proof of concept in Belgium," LIDAM Reprints CORE 2993, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. De Vos, K. & Stevens, N. & Devolder, O. & Papavasiliou, A. & Hebb, B. & Matthys-Donnadieu, J., 2019. "Dynamic dimensioning approach for operating reserves: Proof of concept in Belgium," Energy Policy, Elsevier, vol. 124(C), pages 272-285.
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