In June, the U.S. National Oceanic and Atmospheric Administration warned of a 63% chance of a very strong El Niño developing before the end of 2026, potentially rivaling the most severe episodes since records began in 1950. The 1997-98 El Niño triggered severe floods and droughts across Africa, Latin America, North America, and Southeast Asia, resulting in an estimated 22,000 deaths and more than $36 billion in economic losses. Southeast Asia lacks action, not climate information, as it already possesses satellites, weather observations, and monitoring mechanisms like Singapore’s ASEAN Specialised Meteorological Centre. SpaceAI, the convergence of artificial intelligence and space technologies, combines satellite-based Earth observation, large language models, cloud computing, and advanced analytics to transform environmental data into predictive, decision-ready intelligence. With AI, governments can act first by combining satellite imagery with weather forecasts, soil moisture, and vegetation health to identify at-risk areas. Researchers have mapped fire susceptibility in Indonesian peatlands using satellite data and machine learning, and a study in Riau Province revealed that groundwater level was the major driver of fire risk. Governments can use resulting risk maps to prioritize patrols and fire bans.