Innovation has always moved the energy transition forward quietly at first, then decisively reshaping entire systems.
Over the past decade, we have seen how new ideas can shift entire sectors: solar has become mainstream, electric mobility has accelerated, and grids have become smarter and more flexible. But these transformations didnt happen overnight. Whether it was engines, batteries, HVAC, solar PV or even the early neural network models, each breakthrough took decades to mature before it could scale.
AI may be the first technology with the potential to compress that entire cycleand that creates both opportunity and responsibility. A few themes stand out to me:
1. AI as a Force Multiplier for Climate Action: AI is already improving renewable energy predictability, cutting building emissions, enhancing farm productivity and strengthening carbon accounting. At scale, such solutions could help eliminate gigatonnes of emissionsby augmenting decision-making.
2. Governing AIs Own Footprint Is Essential: AIs rapid growth comes with meaningful energy demand. Its impact on climate will depend on how responsibly we manage data infrastructureensuring transparency, efficiency and a shift toward renewable-powered computing.
3. From Reactive to Proactive Resilience: High-resolution AI models are helping governments and cities move from monitoring climate risks to prognosticating theminforming resilient infrastructure, emergency preparedness and long-term adaptation planning.
4. Democratising Access Matters: Advanced economies currently dominate robotics, automation and industrial software. For AI-enabled climate solutions to scale equitably, they must be accessible to the Global South. India, given its digital public infrastructure and renewable energy momentum, is well positioned to lead.
If 2025 was the year of expectation, 2026 must be the year of integrationwhere AI is embedded across science, policy, agriculture, infrastructure and energy systems. As a practical tool for resilience, efficiency and decarbonisation.
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