AI and Big Data for a Just Energy Transition

This event will delve into the latest advancements and policy frameworks at the intersection of artificial intelligence and machine learning for climate action. The session will feature outcomes of the Green Digital Action (GDA) Green Computing Pillar, with a key focus on the measurement and transparent reporting of emissions associated with AI workloads, encompassing the methodologies, standards, and tools. Highlights will include solutions emerging from the recent ITU-led hackathon on energy and emission metrics, demonstrating practical pathways for the tech sector to track and reduce environmental impact. It will also provide an overview of the standardization work carried out by ITU-T Study Group 5 on measuring the environmental impact of AI. 
 
Discussion will address the core challenge: how can the digital and tech sectors maximize the societal benefits of AI and data solutions—enabling a faster, fairer energy transition—while balancing these gains against increased digital energy use and carbon footprint? Panellists will explore the evolving standards landscape, share actionable insights for responsible digital innovation, and examine collaborative models for making technology part of a just and sustainable energy future.  
 
  
Themes: 
 
Measurement and reporting of emissions: focusing on tools, methodologies, and policy frameworks—highlighting results from the ITU GDA Green Computing Pillar—for accurately measuring and transparently reporting the environmental impact of AI workloads. 
 
Innovative solutions and practical pathways: showcasing breakthrough approaches, including hackathon outcomes, that enable the tech industry to track, benchmark, and reduce the energy and carbon footprint of AI and digital infrastructure: as well as the UNESCO-UCL “GreenerAI Tool” that shows the environmental impact of genAI models. 
 
Balancing technology benefits and environmental responsibility: examining the societal promise of AI and big data for accelerating a just energy transition while addressing the challenges of rising digital energy consumption and environmental costs.