The mission will fast-track the adoption of AI in clean energy systems across its 120+ member countries, placing digital infrastructure and citizen-centric platforms at the centre of the energy transition.

Role of AI in energy systems

• Energy Savings: AI applications in the energy sector globally has a potential to save over 13 exajoules (EJ) of energy by 2035.
• Affordability: AI platform from Tata Consultancy Services (TCS) has enabled 15-20% lower operational costs in an offgrid pilot project in Uttar Pradesh.
• Grid optimisation: An AI-native decision support engine developed by Pravah (startup) digitises the grid, forecasts demand and simulates power flows to localise losses.
• Predictive maintenance: Kazam’s AI enabled energy management system (EMS) applies predictive analytics to optimise charging and enable demand flexibility at electric bus depots 
• Mineral mining sector: AI can be used to process geophysical data to improve anomaly detection and orebody prediction. 

Potential Challenges in adopting AI for energy sector

• Emissions: AI-driven data centres could account for nearly 3% of global electricity demand by 2030, raising concerns about meeting this surge alongside global net-zero goals.
• Strain on Grid Infrastructure: The speed of AI adoption poses significant challenges for long-term grid planning and policy frameworks, which are slower to adapt.