Working Groups At The AI Impact Summit / Resilience, Innovation, and Efficiency
Resilience, Innovation, and Efficiency Working Group
Driving sustainable, resource-efficient AI systems that strengthen climate resilience and sustainability.
About The Working Group
The scale of resources consumed by modern AI solutions presents myriad challenges for the environment as well as exacerbates existing AI divide between nations. The Resilience, Innovation & Efficiency working group focuses on advancing resource-conscious and adaptable AI systems that operate effectively in low-resource environments without compromising accessibility or impact. It seeks to embed efficiency and resilience as central principles in AI innovation, ensuring that technological progress remains inclusive, sustainable, and responsive to the diverse needs of all nations.
Vision & Objectives
Building an equitable global AI ecosystem
The Working Group on Resilience, Innovation & Efficiency envisions a future where AI systems are designed to be efficient, sustainable, and resilient, capable of operating effectively in varied contexts and with limited resources. It aims to ensure that efficiency is not seen as a limitation but as a foundation for innovation and accessibility
Leadership
Mr Pankaj Agarwal
India Co-Chair
Secretary, Ministry of Power, Government of India
Shri Pankaj Agarwal, Secretary, Ministry of Power, Government of India, has been a key architect of India’s energy transition, driving reforms focused on sustainability, efficiency, and innovation. With extensive experience in public policy, infrastructure, and digital transformation, he brings a unique perspective to the Working Group—linking AI efficiency with energy resilience and national development, and reinforcing India’s commitment to responsible, resource-conscious AI that delivers sustainable impact.
France
Country Co-Chair
Key Issues
Understanding the global AI divide and our approach to bridging it
The Challenge
The increasing scale of AI development has led to growing environmental and accessibility concerns. Training large-scale AI models demands enormous energy and water resources, with global data centres projected to consume nearly 3% of the world’s electricity by 2030.
The Solution
AI’s energy intensity contributes to higher carbon emissions, while its water footprint adds stress in already water-scarce regions. These challenges make resource-heavy AI systems unviable for many parts of the Global South, deepening the global divide in AI innovation and adoption.
The Impact
Addressing this imbalance requires a shift towards efficiency as a design value and building AI systems that do more with less. By prioritizing lightweight architectures, optimized computation, and sustainable infrastructure, the Working Group aims to enable an inclusive AI ecosystem that is resilient, adaptable, and globally beneficial.
Meeting Schedule
16th-20th January 2026
Hybrid Meeting (Bengaluru) [Tentative]
Help shape the future of global AI by sharing your perspectives, suggestions, and expertise. Your input will contribute to equitable access and inclusive AI innovation worldwide.
Share your input
We value your insights and contributions to the working groups
Related Pre-Summit Events
Join related events building momentum for the summit
The International Conference on AI for Sustainable Economic Growth at KPR College focused on how AI can drive inclusive, resilient, and sustainable development. The event featured keynotes, panels, and research presentations on workforce transformation, ethical AI, and green innovation, while fostering global collaboration and knowledge exchange through partnerships and research initiatives.
The workshop at Ashoka University focused on using AI to improve weather forecasting and resilience against extreme climate events. Researchers and practitioners discussed AI-driven approaches for monsoon and flood prediction, shared hands-on training, and explored collaborations to advance India-specific forecasting tools and open-source solutions for the broader climate and AI community.
