A key concern was the availability and quality of localized heat-risk information. Gaps in heat-hazard mapping, humidity and warm-night data, as well as vulnerability and risk assessments, can make it difficult to identify which populations and locations are likely to experience the greatest impacts and where limited resources should be directed.
The scale of India's urban landscape presents an additional challenge. With thousands of cities and districts requiring heat preparedness, developing detailed plans individually can be time-consuming and resource-intensive. The discussion therefore highlighted the importance of standardising, automating and scaling elements of Heat Action Plan development, allowing more locations to adopt consistent approaches.
The framework was centred around three practical questions: when to act, where to act and what action to take. Heat thresholds can help establish when preparedness measures should begin, while hyperlocal risk assessment can identify where intervention should be prioritised. Heat Action Plans then provide the framework for determining appropriate actions.
The presentation also introduced the Climate Resilience Analytics and Visualization Intelligence System (CRAVIS), bringing together climate information, sectoral data and visualisation with an Agentic AI layer. Such systems can make climate information more accessible and support interaction with complex climate and risk information.
AI and automation were positioned as tools to help address the scale and complexity of heat preparedness rather than as replacements for Heat Action Plans or institutional decision-making. Their value lies in improving the accessibility and specificity of information and supporting more consistent planning.
The overall takeaway was that early warning becomes more effective when it is connected to hyperlocal risk assessment and clearly defined preparedness actions. Scaling this approach requires stronger data systems, standardised methodologies and institutional capacity to convert information into practical heat resilience measures.
