As Artificial Intelligence (AI) continues to revolutionise industries, its environmental impact is becoming a growing concern. Large-scale machine learning models, while transformative, require vast computational power, leading to significant energy consumption and carbon emissions. At AI Leaders, our mission is to not only promote the ethical and applied use of AI in business but also to ensure future business leaders are equipped with the knowledge to develop sustainable AI solutions. A key voice in this conversation is Assistant Professor Raghavendra Selvan from the University of Copenhagen, whose research focuses on the intersection of AI and climate impact.
The Environmental Costs of AI
Assistant Professor Raghavendra Selvan highlights that “training large-scale AI models can be as energy-intensive as driving five petrol-powered cars over their entire lifespan.” This comparison sheds light on the often-overlooked environmental costs of AI innovation. From powering data centres to running complex algorithms, the energy demands of AI are vast, contributing to the carbon footprint.
Selvan, who has a background in machine learning and medical image analysis, is passionate about raising awareness of AI’s environmental impact. In an interview with the Department of Computer Science at the University of Copenhagen, he states, "The environmental footprint of training large AI models is considerable, and if we continue with business as usual, the carbon emissions associated with AI will only grow." His expertise in both AI development and sustainability brings a critical perspective on how the tech community can reduce its environmental impact.
A European Perspective on Ethical AI
The AI Leaders project aligns with Selvan’s call for more responsible AI development. Our focus is on educating future business leaders about AI’s ethical implications, particularly in relation to sustainability. European values—such as social responsibility, environmental protection, and ethics—must be at the core of AI implementation in business. Selvan argues that “to align with climate goals, the AI sector must adopt greener practices, including optimising algorithms and using renewable energy for data centres.”
As part of our commitment to preparing business and management students, we integrate these values into our AI education. Future business leaders must not only be proficient in AI applications but also understand how to balance innovation with environmental responsibility.
Practical Approaches to Reduce AI’s Carbon Footprint
Selvan advocates for specific actions to reduce the carbon footprint of AI. These include improving model efficiency, using energy-efficient hardware, and transitioning to green data centres. He explains that “optimising machine learning models for efficiency can significantly reduce energy consumption, without compromising performance.” This advice is crucial for businesses that rely heavily on AI for decision-making and automation.
At AI Leaders, we aim to ensure that the next generation of business leaders incorporates these practices into their AI strategies. By understanding how to optimise AI models and choosing sustainable data solutions, future managers and entrepreneurs can make AI a force for good—both for business and the planet.
Greener AI for the Business World
Assistant Professor Selvan has been vocal about the need for collective action in the AI community. He points out that “the AI sector must take ownership of its environmental impact. We need more collaboration between industry, academia, and policymakers to develop standards that encourage sustainability.” This is particularly relevant in the European context, where businesses are held to high ethical and environmental standards.
At AI Leaders, we encourage students to explore solutions that merge AI innovation with sustainability goals. As Selvan explains, "The environmental cost of AI can no longer be an afterthought; it needs to be an integral part of the decision-making process."
Building a Sustainable Future with AI
Selvan’s research offers crucial insights into how AI can be both innovative and sustainable. His work, which spans the intersection of machine learning and environmental sustainability, has been instrumental in shaping discussions on the future of AI. He emphasises that “we are at a crossroads where AI can either exacerbate the climate crisis or become part of the solution. The choices we make today will determine which path we take.”
By focusing on practical applications of AI that align with ethical and environmental values, the AI Leaders project is preparing university-level business and management students to face the challenges of tomorrow. Through education, we aim to foster a new generation of business leaders who are not only skilled in AI but also committed to sustainability.