Executive Summary
Artificial Intelligence (AI) has become one of the defining technologies of this decade, reshaping how organisations innovate, operate and deliver value.
With billions in public and private investment, its rapid expansion is driving profound economic and social change—but also raising urgent questions about environmental impact, ethics and governance.
As part of the AI in ESG series, published by edie over recent months, we engaged with leading voices across business, academia and technology, including Capgemini, Salesforce, Siemens UK, Workiva, Cognizant, Vodafone, M&S, Nature 2030, the Cambridge Institute for Sustainability Leadership (CISL), and the Royal Veterinary College. Insights were also gathered from experts at Google, Microsoft, AWS, Cambridge Zero, and NESO. These conversations explore how AI intersects with sustainability — both as a powerful tool for progress and as a potential disruptor of environmental goals.
The five-part ‘AI in ESG’ series examined these intersections in depth. It began by assessing whether AI can ever be compatible with the 1.5C climate goal and the net-zero transition, before exploring its role in corporate governance, ethics, operational efficiency and disclosure. Later features delved into AI’s potential to enhance sustainability reporting, streamline emissions tracking, and even support biodiversity protection — areas where businesses are under growing pressure to demonstrate measurable progress.
Quantitative insights from edie’s Sustainable Business Tracker provide further context. Surveying hundreds of sustainability professionals, the data shows that only 29% of organisations currently use AI to advance their sustainability agenda, while 51% plan to invest in AI technologies within the next 18 months. Additionally, while 76% of respondents believe AI could make sustainability work easier, only 6% consider the industry ethical, and 92% say it requires stronger regulation.
When asked whether AI could ever align with the 1.5C goal, 20% said no, 37% said yes, and 43% were undecided, reflecting both optimism and uncertainty in equal measure.
From the experts interviewed for the series, several key messages emerged. Energy efficiency remains both a challenge and a potential solution. While AI can optimise resource use and enable more sustainable operations, the lack of transparency around data centre supply chains makes it difficult for companies to accurately measure AI’s carbon footprint. Businesses are therefore encouraged to assess whether their AI providers disclose energy consumption data and to push for greater visibility across the value chain.
Many experts emphasised that AI should augment, not replace, human expertise; a “human in the loop” approach remains essential to ensure accountability and context. Setting standards for low-carbon and ethical AI solutions will be critical. By embedding sustainability requirements into supplier contracts and tenders — such as minimum thresholds for energy efficiency, carbon footprint, and ethical practices — companies can collectively shape a more responsible AI market.
Ultimately, the message is one of balanced engagement. Businesses cannot afford to ignore AI’s transformative potential, but neither can they rush in blindly. The opportunity lies in adopting AI responsibly—driving efficiency, transparency and innovation while ensuring alignment with long-term sustainability goals.