launched<\/a> the country\u2019s first agentic AI assistants for weather forecasting and approved a broader roadmap to expand autonomous AI across its operations. The initiative aligns with the UAE government\u2019s vision to embed agentic AI into public services to improve decision-making, operational efficiency, and service delivery.<\/p>\nThe system is designed to augment meteorologists\u2019 work by automating routine analytical tasks while keeping human experts responsible for all operational decisions.\u00a0<\/p>\n
\u201cThe adoption of agentic AI technologies embodies the UAE leadership\u2019s vision of harnessing advanced technologies to build a more efficient and future-ready government ecosystem,\u201d said Abdulla Ahmed Al Mandous, Director General of the National Center of Meteorology and President of the World Meteorological Organization (WMO).<\/p>\n
\u201cWe do not see artificial intelligence as a substitute for human expertise, but rather as a knowledge partner that enhances the capabilities of specialists by providing more advanced tools for data analysis, risk assessment, and timely decision-making,\u201d he added. \u201cHuman expertise will always remain at the core of our operations.\u201d<\/p>\n
The deployment represents one of the first practical implementations of agentic AI within the meteorological sector. Unlike conventional AI tools that perform isolated tasks, the system consists of multiple autonomous yet collaborative agents operating through a unified platform. Together, they support specialists in monitoring weather data, analyzing forecasts, generating operational reports, and assisting early warning activities.<\/p>\n
The first phase introduces two AI assistants\u2014Al-Rasid and Forecaster Assistant\u2014into NCM\u2019s operational forecasting centers.<\/p>\n
Al-Rasid functions as a continuous monitoring agent, processing information from weather observation stations, radar systems, meteorological satellites, seismic monitoring networks, air quality stations, and other operational data sources. It analyzes incoming data in real time, flags anomalies requiring expert attention, and generates national weather briefings alongside short-term outlooks to provide forecasters with a consolidated operational view.<\/p>\n
The Forecaster Assistant focuses on numerical weather prediction. It monitors forecasting models, validates incoming datasets, compares outputs across multiple global forecasting systems, evaluates forecast uncertainty, and prepares preliminary weather and marine bulletins. The system also generates dashboards highlighting potential weather hazards, enabling meteorologists to spend less time on manual processing and more time interpreting complex weather scenarios.<\/p>\n
Meteorological agencies process massive volumes of real-time data from distributed sensing networks, making them well-suited for AI agents that can independently analyze information, surface anomalies, and coordinate workflows while operating under human supervision.<\/p>\n
NCM said all AI-generated outputs will continue to require review and approval by qualified specialists before publication, underscoring a governance model that keeps accountability with human experts.<\/p>\n
Looking ahead, the center plans to extend agentic AI into additional operational domains, including climate services, multi-hazard early warning systems, aviation meteorology, air quality monitoring, seismology, and public communications.<\/p>\n
The expansion will be governed through a framework focused on protecting national data, ensuring the explainability of AI-generated outputs, maintaining full traceability of processes and decisions, and continuously evaluating system performance through defined metrics.<\/p>\n
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