A scoping review of AI for sustainability and sustainable AI in higher education

Artificial intelligence (AI) is receiving increasing attention for its potential to support sustainability in higher education. As both users and developers of AI technologies, universities are well-positioned to advance environmental and social goals while ensuring that AI is used responsibly. This scoping review examines two related areas: AI for Sustainability, which involves using AI to achieve sustainability outcomes, and sustainable AI, which focuses on reducing the direct environmental and ethical impacts of AI itself. The review examines how these concepts are defined in literature, the field's evolution over time, and the potential or increasing application of AI in sustainability practices by universities. While there are promising examples of the use of AI to advance sustainability projects, including AI used for energy management, climate monitoring, and green campus programs, many of these efforts are still limited in scale and lack clear ethical or environmental guidelines. In addition, much of the current research is either conceptual or based on small-scale pilot projects, with few studies assessing long-term impact or full institutional adoption and commitment. The outcome of the review is intended to provide a structured overview of the extant of work in the area; identify research gaps, and introduce the concept of a future green campus. It argues that future research should focus on testing AI tools in real university settings, measuring their environmental impact, and developing policies that combine ethical and sustainability goals. Greater involvement from students, staff, and faculty will also be essential to ensure that AI supports a fair and sustainable future for higher education.

Authors

Institutions

Publication Details

Journal
Discover Computing
Published
2026-01-27
DOI
https://doi.org/10.1007/s10791-025-09861-2
Primary Topic
Sustainability in Higher Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A scoping review of AI for sustainability and sustainable AI in higher education

Nataliya Podgorodnichenko, Sarah Carr, Ben Kei Daniel
Discover Computing
Sustainability in Higher Education
article

A scoping review of AI for sustainability and sustainable AI in higher education

Nataliya Podgorodnichenko, Sarah Carr, Ben Kei Daniel
article en

Abstract

Artificial intelligence (AI) is receiving increasing attention for its potential to support sustainability in higher education. As both users and developers of AI technologies, universities are well-positioned to advance environmental and social goals while ensuring that AI is used responsibly. This scoping review examines two related areas: AI for Sustainability, which involves using AI to achieve sustainability outcomes, and sustainable AI, which focuses on reducing the direct environmental and ethical impacts of AI itself. The review examines how these concepts are defined in literature, the field's evolution over time, and the potential or increasing application of AI in sustainability practices by universities. While there are promising examples of the use of AI to advance sustainability projects, including AI used for energy management, climate monitoring, and green campus programs, many of these efforts are still limited in scale and lack clear ethical or environmental guidelines. In addition, much of the current research is either conceptual or based on small-scale pilot projects, with few studies assessing long-term impact or full institutional adoption and commitment. The outcome of the review is intended to provide a structured overview of the extant of work in the area; identify research gaps, and introduce the concept of a future green campus. It argues that future research should focus on testing AI tools in real university settings, measuring their environmental impact, and developing policies that combine ethical and sustainability goals. Greater involvement from students, staff, and faculty will also be essential to ensure that AI supports a fair and sustainable future for higher education.

Discover ComputingVol. 29(1)
University of Northern British Columbia (CA), University of Otago (NZ)
Openalex Percentile: Top 79%
Sustainability in Higher Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.