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The digital technologies and AI models are advancing both sustainability’s agenda (by helping researchers to analyse complex interaction among various SDGs parameters, and facilitating sustainability’s decision-making) and education policy strategies (through a personalizing learning and expanding access to education through new AI tools). The University World News explores these issues in a series of special reports.
AI in supporting the Sustainable Development Goals, SDGs
Forced by global challenges, the education policies are being radically transformed. Hence, the digital technologies and AIs are playing an increasing role in addressing complex social-ecologic and sustainability issues. It is possible to formulate a new education-teaching facility called Education for Sustainable Development (ESD) to provide students with the necessary skills, understanding and adequate knowledge to better address SDGs priorities and issues.
Digital technologies – and specifically AIs – are not only “reflecting” advancing SDGs deployment: the AIs are “enabling” these technologies to cope with the work of education providers, as well as prepare future workforce being equipped with smarter, innovative and more productive approaches.
More on such issues as: AI deployment, SDGs and modern education transformations in the posts in our blog at: https://integrin.dk, and/or www.integrin.dk/; specifically: https://www.integrin.dk/2020/07/30/integrated-education-in-europe-eus-attempts-to-make-european-wide-universities/
The so-called “new-old” ESD-approach (based in the SDG-4) is to provide students with the necessary knowledge, skills and values to better address sustainability issues. As Patrick Blessinger (president and chief scientist for the International Higher Education Teaching and Learning Association in the US, IHETLA) notes “education can provide a personalised form of sustainability learning and make higher-order learning available to a broader audience; it gives higher education a unique opportunity to transform the learning process across all knowledge domains”.
Source and citation: https://www.universityworldnews.com/post.php?story=20251215142852409
The term ESD requires, as P. Blessinger correctly notes, “interacting processes of political, economic, social, technological and environmental systems”, i.e. an interacting governance. Thus, using AI models in education and training – as an “adaptive learning platform” can enable education providers both to “learner-the learners” and activate the process acquiring knowledge and skills. Studies from the UNESCO Institute for Information Technologies in Education already in 2020 (!) illustrated how AI-based solutions could apply sustainability-related content to local, linguistic and cultural characteristics in education.
Source: Policy briefs in https://unesdoc.unesco.org/ark:/48223/pf0000374947
Then, the AIs are increasing the students’ accessibility while demonstrating the growing demand for a so-called “universal design for learning, UDL” as an additional tool in expanding the ESD’s workout.
More on the “UDL-design” (2025) in: https://udlguidelines.cast.org/
The AI’s role in education
P. Blessinger points that AI can enhance teachers’ abilities to provide better SDGs education and conducting better scientific research: specifically, un such areas as urban development, energy transition (renewables) and/or biodiversity; e.g. “the AI models can monitor air quality, water purity, carbon emissions and land-use patterns more effectively than ever before”, he notes.
However, he adds, “the ability of AI to… extend sustainability knowledge can be beneficial, but it is human judgement that decides how best to use these technologies”.
He finally, scratches some AIs potentials: e.g. in its ability to “help students become more aware of the interconnectedness of the world”, in making feasible ethical decisions, and in dedicated SDGs’ education and research.
More in: https://www.integrin.dk/2025/06/14/ai-in-education-transformative-approach-to-teaching-and-learning/
A recent review concludes that while AI already supports climate modelling and disaster prediction, its educational potential remains “underexploited”. Some institutions are now moving decisively ahead. The Quality Assurance Agency for Higher Education (QAA) in the United Kingdom, in using AI to promote education for SDGs and increasing access to “digital skills”, has looked at some case studies highlighting students’ engagement with the GenAI models in addressing SDG challenges. The QAA concludes that “when implemented effectively, AI-based ESD can bring about a generation of students who can better address the sustainability issues of the 21st century”.
Source: https://www.universityworldnews.com/post.php?story=20251217141210994
Besides, as the Environmental Sciences Europe’s study-2025 finds, the integration of artificial intelligence into sustainability education can significantly enhance the learning experience by providing personalised instruction, interactive simulations and adaptive feedback, making the long-promised vision of personalised learning increasingly tangible within sustainability curricula.
Reference to: https://link.springer.com/article/10.1186/s12302-025-01159-w
Then, in the world-wide AI’s presence, the educators’ providers are more than just “content deliverers”: they are becoming meaning-makers, ethical filters, and sense-making guides for the AI-mediated world. As James Yoonil Auh notes, “they also become something less visible but equally crucial: emotional shock absorbers”.
AIs perspectives in research
In recent analysis of AI models in advancing SDGs, a team of researchers reviewed about eight hundred (!) articles that explore AI applications in the SDG-related research. The number of articles per year increased substantially over time, exceeding 100 publications in 2020 and surpassing 200 publications annually in 2022 and 2023. Geographically, most research tackling SDGs using AI originates in Europe and Asia, with over 3 hundred articles made by researchers affiliated in China, India, the United States and Spain.
As machine learning represents the dominant subset of AI methods, this digital framework “aligns with most of the empirical applications… while also encompassing the broader AI context for the distribution of the role of AI across the SDGs”.
Source and citation from: Gohr, C., Rodríguez, G., Belomestnykh, S. et al. Artificial intelligence in sustainable development research. Nature Sustainability, vol. 8, 970–978 (2025). In: https://doi.org/10.1038/s41893-025-01598-6.
The seventh session of the United Nations Environment Assembly (in December 2025 at the United Nations Environment Program, UNEP headquarters in Nairobi, Kenya), was devoted to “Advancing sustainable solutions for a resilient planet”, with a major topic on the mounting environmental impact of AI. Although, there is much to be done about the environmental impact of AI, some of the data do rise concern, said G. Radwan, the UNEP’s chief digital officer, and added that “we need to make sure the net effect of AI on the planet is positive before we deploy the technology at scale”.
It is obvious, that the rise of AI brings both risks and opportunities: as AI models grow in capability and scale, there will be demand for sustainable computer infrastructures, energy-efficient AI hardware, green data centres, and intelligent resource-allocation systems that reduce carbon impact.
Source and citation from: https://www.unep.org/environmentassembly/unea7
Additional information in: https://www.universityworldnews.com/post.php?story=20251216121553722