A Scoping Review of AI for Sustainability and Sustainable AI in Higher Education

Synthesis: Daniel, Podgorodnichenko, and Carr (2026) conduct a scoping review of two interconnected yet distinct pathways at the intersection of AI and sustainability in higher education: AI for Sustainability (using AI to achieve sustainability outcomes) and sustainable AI (reducing the direct environmental and ethical impacts of AI itself). As both users and developers of AI, universities are well-positioned to advance environmental and social goals while ensuring responsible use. The review maps how these concepts are defined, the field's evolution, and universities' actual engagement with AI for sustainability — finding promising examples (energy management, climate monitoring, green campus programs) but limited scale and a lack of clear ethical or environmental guidelines, with much research remaining conceptual or small-scale.

Key Findings

1. Two distinct pathways. AI for sustainability (AI as a tool for sustainability outcomes) and sustainable AI (reducing AI's own environmental/ethical footprint) are related but distinct research areas that are often conflated.
2. Promising but limited applications. Universities use AI for energy management, climate monitoring, and green campus programs, but these efforts are limited in scale and often lack clear ethical or environmental guidelines.
3. Conceptual and small-scale evidence. Much of the current research is conceptual or based on small-scale pilots rather than robust, large-scale implementations.
4. Universities are dual actors. As both users and developers of AI, universities must balance advancing sustainability goals with ensuring AI itself is used responsibly and sustainably.

Relevance

This scoping review is the defining survey for the knowledge base's Sustainability concept page — it establishes the two-part taxonomy (AI for sustainability vs. sustainable AI) that organizes the whole concept. It connects to Ethics, Governance, and Meta Analysis Systematic Review as a systematic map of the evidence base, and to the environmental-impact dimension of sustainable AI.

Connected Concepts

• Sustainability
• Higher Ed
• Meta Analysis Systematic Review
• Ethics
• Governance
• AI Education

Connected Articles

• Alsuhaymi Sustainable Education AI Digitalization 2026 — Value-critical approach to sustainable education and AI
• Liu AI Sustainable Engineering Education 2026 — AI-SEE framework for sustainable engineering education
• LLM Environmental Impact Student Usage 2026 — Environmental impacts of LLM use

Citation

Daniel, B. K., Podgorodnichenko, N., & Carr, S. (2026). A Scoping Review of AI for Sustainability and Sustainable AI in Higher Education. Discover Computing, 29(1), 48.