Universities and colleges across the UK are being urged to take a harder look at the environmental consequences of artificial intelligence, moving beyond passive adoption to actively manage the technology's carbon footprint, energy consumption, and electronic waste. New guidance released by Jisc and the Environmental Association for Universities and Colleges (EAUC) at the 2026 EAUC annual conference aims to help post-16 education institutions understand both the risks and opportunities AI presents for sustainability.

Why Are Universities Struggling With AI's Environmental Impact?

AI tools have become deeply embedded across teaching, research, and campus operations at most institutions, often in ways that remain invisible to decision-makers. From AI-assisted marking systems and student support chatbots to energy management platforms, the technology is now part of everyday institutional life. Yet despite this rapid adoption, sustainability considerations are frequently absent from AI implementation discussions.

One of the biggest obstacles is a lack of transparency from technology providers. Universities and colleges increasingly depend on global AI services but often have little visibility into the energy, water, and carbon impacts associated with those tools. This opacity makes it difficult for institutions to accurately account for AI's contribution to their overall emissions, particularly within complex supply chains known as Scope 3 emissions.

Another tangible concern is electronic waste and the environmental costs of hardware production. Significant environmental damage occurs before AI systems even run their first query, through raw material extraction and manufacturing of computing infrastructure. Institutions must therefore consider the full hardware lifecycle, from procurement through end-of-life disposal, when developing AI strategies.

What Practical Steps Can Institutions Take Right Now?

• Audit Existing AI Use: Build a clear picture of which AI tools are already in use across the institution, including those embedded in existing software platforms that may not be immediately obvious.
• Request Environmental Data From Suppliers: Use procurement processes to ask vendors specific questions about energy use, carbon emissions, and water consumption associated with their AI services.
• Integrate Sustainability Into AI Training: Incorporate environmental considerations into AI literacy and training programs for staff and students so everyone understands the implications of their AI use.
• Strengthen Governance Frameworks: Include AI's environmental impact within institutional risk registers and overall operational strategies, not as an afterthought.
• Optimize User Behavior: Encourage staff and students to have a clear rationale before using generative AI and to create well-constructed prompts that minimize unnecessary outputs.

Cal Innes, sustainability subject specialist at Jisc, emphasized the urgency of this work:

"The speed of AI adoption across colleges and universities, in many cases, is surpassing institutions' ability to keep pace with its consequences, with the environmental dimension being one of the least well understood. Our members have expressed a need for support that is both practical and trustworthy, and that's exactly what Jisc and EAUC have aimed to achieve with this guide."

Cal Innes, Sustainability Subject Specialist at Jisc

Can AI Actually Help Universities Meet Sustainability Goals?

Despite the risks, the new guidance emphasizes that AI can support sustainability objectives when deployed thoughtfully and for clearly defined purposes. Potential applications include optimizing campus energy consumption through AI-enabled building management systems, supporting climate research and environmental modeling, extending equipment lifespans through predictive maintenance, automating carbon accounting and reporting, and using digital simulations to replace energy-intensive physical processes.

However, the authors caution that claims about AI's environmental benefits should be critically evaluated and supported by evidence. Institutions are encouraged to focus on proven, targeted uses rather than accepting vendor marketing claims at face value.

Charlotte Bonner, CEO of EAUC, noted that this guidance represents just the beginning of a broader effort:

"This guidance reflects the strength of partnership between Jisc and EAUC, and the insight of practitioners across the sector who are actively grappling with the challenges and opportunities AI presents. We see this as the start of a wider programme of work to support the sector, and we encourage technology suppliers to play their part by improving transparency and working with us to enable more sustainable AI adoption."

Charlotte Bonner, CEO of EAUC

What Comes Next for the Education Sector?

The guidance concludes with a call for greater collaboration across the sector. Universities, colleges, and sector bodies must work together to improve transparency, strengthen reporting standards, and influence suppliers on sustainable AI practices. To support this effort, Jisc and EAUC will host an online AI and environmental sustainability masterclass on July 14, 2026.

The release of this guidance signals a shift in how UK higher education and further education institutions approach AI adoption. Rather than asking simply "Can we use this technology?" institutions are now being pushed to ask "What are the environmental consequences, and how do we minimize them?" As AI continues to permeate every aspect of campus operations, this more intentional approach may become essential for institutions serious about meeting their climate commitments.