Artificial intelligence in sustainable development research

Research output: Journal contributionsJournal articlesResearchpeer-review

Standard

Artificial intelligence in sustainable development research. / Gohr, Charlotte; Rodríguez Aboytes, Jorge Gustavo; Belomestnykh, Sergey et al.
In: Nature Sustainability, Vol. 8, No. 8, 08.2025, p. 970-978.

Research output: Journal contributionsJournal articlesResearchpeer-review

Harvard

Gohr, C, Rodríguez Aboytes, JG, Belomestnykh, S, Berg-Moelleken, D, Chauhan, N, Engler, J-O, von Heydebreck, L, Hintz, MJ, Kretschmer, M-F, Krügermeier, C, Meinberg, J, Rau, A-L, Schwenck, C, Aoulkadi, I, Poll, S, Frank, E, Creutzig, F, Lemke, O, Maushart, M, Pfendtner-Heise, J, Rathgens, J & von Wehrden, H 2025, 'Artificial intelligence in sustainable development research', Nature Sustainability, vol. 8, no. 8, pp. 970-978. https://doi.org/10.1038/s41893-025-01598-6

APA

Gohr, C., Rodríguez Aboytes, J. G., Belomestnykh, S., Berg-Moelleken, D., Chauhan, N., Engler, J.-O., von Heydebreck, L., Hintz, M. J., Kretschmer, M.-F., Krügermeier, C., Meinberg, J., Rau, A.-L., Schwenck, C., Aoulkadi, I., Poll, S., Frank, E., Creutzig, F., Lemke, O., Maushart, M., ... von Wehrden, H. (2025). Artificial intelligence in sustainable development research. Nature Sustainability, 8(8), 970-978. https://doi.org/10.1038/s41893-025-01598-6

Vancouver

Gohr C, Rodríguez Aboytes JG, Belomestnykh S, Berg-Moelleken D, Chauhan N, Engler JO et al. Artificial intelligence in sustainable development research. Nature Sustainability. 2025 Aug;8(8):970-978. doi: 10.1038/s41893-025-01598-6

Bibtex

@article{f78b3c85203146d88f22e20e9a3c3d40,
title = "Artificial intelligence in sustainable development research",
abstract = "Artificial intelligence (AI) holds significant potential to advance Sustainable Development Goals by enabling data-driven insights and optimizations. In this analysis, we review 792 articles that explore AI applications in Sustainable Development Goal-related research. The literature is organized along two dimensions: (1) the disciplinary spectrum, from natural sciences to the humanities, and (2) the focus, distinguishing economic from socioecological content. Deep learning and supervised machine learning were the most prominently applied algorithms for forecasting and system optimization. However, we identify a critical gap: only a few studies combine advanced AI applications with deep sustainability expertise. Sustainability needs to strike a balance between contextualization and generalizability to provide tangible knowledge that will lead to responsible change. AI must play a central role in this process. While expectations for AI{\textquoteright}s transformative role in sustainable development are high, its full potential remains to be realized.",
keywords = "Sustainability Governance, Sustainability Science, Sustainability sciences, Communication",
author = "Charlotte Gohr and {Rodr{\'i}guez Aboytes}, {Jorge Gustavo} and Sergey Belomestnykh and Dagmar Berg-Moelleken and Neha Chauhan and John-Oliver Engler and {von Heydebreck}, Linda and Hintz, {Marie J.} and Max-Friedemann Kretschmer and Carlo Kr{\"u}germeier and Jule Meinberg and Anna-Lena Rau and Christoph Schwenck and Iman Aoulkadi and Sabrina Poll and Elisabeth Frank and Felix Creutzig and Oska Lemke and M. Maushart and Jannis Pfendtner-Heise and Julius Rathgens and {von Wehrden}, Henrik",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2025.",
year = "2025",
month = aug,
doi = "10.1038/s41893-025-01598-6",
language = "English",
volume = "8",
pages = "970--978",
journal = "Nature Sustainability",
issn = "2398-9629",
publisher = "Nature Publishing Group",
number = "8",

}

RIS

TY - JOUR

T1 - Artificial intelligence in sustainable development research

AU - Gohr, Charlotte

AU - Rodríguez Aboytes, Jorge Gustavo

AU - Belomestnykh, Sergey

AU - Berg-Moelleken, Dagmar

AU - Chauhan, Neha

AU - Engler, John-Oliver

AU - von Heydebreck, Linda

AU - Hintz, Marie J.

AU - Kretschmer, Max-Friedemann

AU - Krügermeier, Carlo

AU - Meinberg, Jule

AU - Rau, Anna-Lena

AU - Schwenck, Christoph

AU - Aoulkadi, Iman

AU - Poll, Sabrina

AU - Frank, Elisabeth

AU - Creutzig, Felix

AU - Lemke, Oska

AU - Maushart, M.

AU - Pfendtner-Heise, Jannis

AU - Rathgens, Julius

AU - von Wehrden, Henrik

N1 - Publisher Copyright: © The Author(s) 2025.

PY - 2025/8

Y1 - 2025/8

N2 - Artificial intelligence (AI) holds significant potential to advance Sustainable Development Goals by enabling data-driven insights and optimizations. In this analysis, we review 792 articles that explore AI applications in Sustainable Development Goal-related research. The literature is organized along two dimensions: (1) the disciplinary spectrum, from natural sciences to the humanities, and (2) the focus, distinguishing economic from socioecological content. Deep learning and supervised machine learning were the most prominently applied algorithms for forecasting and system optimization. However, we identify a critical gap: only a few studies combine advanced AI applications with deep sustainability expertise. Sustainability needs to strike a balance between contextualization and generalizability to provide tangible knowledge that will lead to responsible change. AI must play a central role in this process. While expectations for AI’s transformative role in sustainable development are high, its full potential remains to be realized.

AB - Artificial intelligence (AI) holds significant potential to advance Sustainable Development Goals by enabling data-driven insights and optimizations. In this analysis, we review 792 articles that explore AI applications in Sustainable Development Goal-related research. The literature is organized along two dimensions: (1) the disciplinary spectrum, from natural sciences to the humanities, and (2) the focus, distinguishing economic from socioecological content. Deep learning and supervised machine learning were the most prominently applied algorithms for forecasting and system optimization. However, we identify a critical gap: only a few studies combine advanced AI applications with deep sustainability expertise. Sustainability needs to strike a balance between contextualization and generalizability to provide tangible knowledge that will lead to responsible change. AI must play a central role in this process. While expectations for AI’s transformative role in sustainable development are high, its full potential remains to be realized.

KW - Sustainability Governance

KW - Sustainability Science

KW - Sustainability sciences, Communication

UR - http://www.scopus.com/inward/record.url?scp=105011342860&partnerID=8YFLogxK

U2 - 10.1038/s41893-025-01598-6

DO - 10.1038/s41893-025-01598-6

M3 - Journal articles

AN - SCOPUS:105011342860

VL - 8

SP - 970

EP - 978

JO - Nature Sustainability

JF - Nature Sustainability

SN - 2398-9629

IS - 8

ER -