This session will provide a comprehensive overview of the relationship between artificial intelligence (AI) and sustainability, in two parts. Part 1 will focus on measuring the environmental impact of deploying generative AI and agentic AI, while Part 2 will explore the immense potential of AI as a catalyst for progress in sustainability-driven innovation, operations and governance.
Insights from a Capgemini study revealed a stark lack of corporate awareness, with only 38% of organizations acknowledging AI’s ecological footprint and a mere 12% actually measuring the impact of their Generative AI deployments. The technical reality is sobering, as AI models are exponentially more energy-intensive than traditional tools – a single query can be 10x more
demanding than a standard web search. Since these cloud-based energy costs fall under a company’s Scope 3 emissions, they directly challenge net-zero commitments. To bridge this gap, Capgemini introduced an attributional Life Cycle Assessment (LCA) methodology that tracks the footprint across hardware, compute, and network traffic, allowing firms to use scenario planning to find the necessary balance between business value and environmental responsibility.
On the benefits side of the equation, AI is already accelerating breakthroughs across energy optimization, Scope 3 data modeling, and circular material discovery. A standout example included Microsoft’s use of agentic AI to simulate 300 data center coolant scenarios in just three weeks, ultimately identifying a waterless solution that would have taken years to find manually. Beyond high-level engineering, practical applications like "Greenwashing Check" co-pilots – trained on FTC and EU regulations – and restaurant "control towers" are making sustainability actionable for marketing teams and floor managers alike. However, the transition requires careful human management and leaders must address the "skill gap" risk, ensuring that as AI removes operational friction, junior employees still develop the critical thinking and leadership skills necessary for long-term professional growth.