The WMO AI Conference highlighted the importance of shared and open data, coordinated benchmarks, and human-centred service design to ensure AI systems are trusted and transparent. The conference emphasized the need for interoperability while respecting the authoritative role of National Meteorological and Hydrological Services (NMHSs). Key priorities identified include capacity building, regionally based pilot projects, dialogue on public and private datasets, and supporting observation and physics-based systems. The outcomes of the conference, encapsulated in a statement, are set to guide discussions at the upcoming WMO Extraordinary Congress from October 20 to 24.
What were the key outcomes of the WMO AI Conference?
