1As the world grapples with escalating environmental crises, the integration of artificial intelligence (AI) into sustainability efforts is becoming increasingly essential. This first section highlights how AI is being used and explores its transformative potential across various sectors, including wastewater management, decarbonizing the energy sector, and materials discovery while reinforcing the importance of responsible implementation and scaling to ensure that these technologies deliver lasting positive impact.

Zoom Original (jpeg, 1.8M)

2At the heart of this shift is the recognition that AI is no longer merely a tool for incremental improvements: it is driving fundamental transformations in how industries operate and how sustainability goals are achieved. The intersection of AI and sustainability brings new opportunities to rethink traditional processes and adopt more proactive, data-driven solutions. This section brings together several key perspectives on how AI is being leveraged to tackle some of the most pressing environmental challenges of our time.

3The section opens with an article by Philippe Aghion, Mathias Abitbol, Céline Antonin, and Lint Barrage, which explores the role of AI in energy efficiency and climate change mitigation. Philippe Aghion, who has recently been awarded the Nobel Prize in Economics, brings a powerful economic lens to the discussion, highlighting how AI can help reconcile industrial performance with environmental constraints. Taking Veolia’s wastewater management as a case study, the authors compare the direct energy costs of AI operations and the energy savings from AI. Initial results show that AI provides energy and emissions savings of nearly 10%. For the authors, the takeaways are promising: well-governed, purpose-built AI offers a practical pathway to accelerate decarbonization.

4The second article, written by Stuart Stock, outlines Veolia’s AI strategy, focusing on how the company is embedding AI within its operations to manage energy, water, and waste more effectively. Through the GreenUp program, a €4 billion initiative, Veolia aims to decarbonize its operations, reduce pollution, and regenerate resources, all while demonstrating that environmental goals can align with business success. With a growing portfolio of AI solutions, like digital twin systems for wastewater treatment and computer vision for waste management, Veolia is making tangible strides in sustainability with a strategy underpinned by a strong governance framework, emphasizing responsible AI.

5In the energy sector, Nilushi Kumarasinghe, Ursula Eicker, Shahin Masoumi-Verki, Kathryn Kaspar, Suchit Ahuja, and Damon Matthews discuss the role AI can play in decarbonizing the energy sector as well as the risks and challenges that AI-innovation poses. The authors highlight that while AI holds immense promise, it also faces challenges in scaling these solutions globally, addressing regional disparities, and ensuring that AI deployments contribute meaningfully to sustainability goals. The article highlights the need for deliberate, intentional design to ensure that AI technologies help accelerate the energy transition and address the sector’s most significant environmental impacts.

6The application of AI is not limited to industrial processes. Nofri Dahlan and Nurul Aqilah Mahmud explore the impact AI has on building energy management. In a world where buildings account for a large portion of global energy consumption and carbon emissions, AI is revolutionizing how energy is used, managed, and optimized. The authors show that intelligent systems help buildings become more energy-efficient, resilient, and sustainable by controlling heating, ventilation, and air conditioning (HVAC) systems. They also support the integration of renewable energy sources such as solar power and battery storage. The authors highlight that despite challenges such as data fragmentation and integration, AI is proving to be a vital tool for improving energy management in buildings.

7Finally, Bichlien Nguyen emphasizes the critical role of materials in the sustainability transition and how AI is opening a new paradigm to accelerate the discovery and design of sustainable materials. It is also increasingly being applied to optimize the use of raw materials, minimize waste, and ensure more sustainable practices in industries such as construction and manufacturing. Nguyen outlines how AI-driven innovations in materials science and management AI supports the broader are advancing goals across material circularity, clean energy transition, and climate resilience.

8Together, these articles illustrate how AI is driving systemic change across industries, helping businesses not only achieve their sustainability targets but also create new pathways for innovation and growth. From reducing carbon emissions and improving energy efficiency to optimizing resource management, AI is at the forefront of the ecological transformation.