• Assess the efficacy of AI-driven nowcasting in advancing regional forecasting proficiencies and identify 1-2 prospective Regional Specialized Meteorological Centres (RSMCs) and recommend to SC-ESMP (Standing Committee on Data Processing for Applied Earth System Modelling and Prediction).

• AI-based weather nowcasting products: Implement experimental AI-based nowcasting solutions (mainly focus on lightning and rainfall nowcasting) in developing countries, aiming for operational status.

• Guidelines or Good Practices for AI Use in Nowcasting: Develop a tailored framework for AI implementation in nowcasting for developing countries and offer guidance on building AI training datasets. The framework and recommendations will be submitted to the ITU Global Initiative.

• Report on AI's Impact in Weather Forecasting: Analyse and document the changes AI brings to operational workflows in weather forecasting and submit the report to the SC-ESMP.

• A set of recommended practices for public-private engagement in AI-related collaboration and capacity development for developing countries

• Software and data repositories/procedures for running trained nowcasting models over selected regions for benchmarking.

• Verification methodology for AI-nowcasting products to ensure trust in the use of the new products.