Mongolia is undergoing a rapid digital transformation through its Vision 2050 strategy, aiming to evolve into a regional tech leader by the middle of the century. The initiative focuses on diversifying the national economy beyond mining by building a human-centered digital government. A core component of this shift involves the National Statistics Office (NSO) transitioning from manual data collection to sophisticated digital systems that treat data as a strategic national asset.

The integration of AI is particularly transformative for Mongolia’s agricultural sector. Collaborating with the UN Global Platform, the NSO now employs remote sensing—scanning the Earth via satellite—to automate crop classification. They utilize the Spectral Angle Mapper (SAM) method to identify specific crops like wheat and potatoes from imagery. This data is processed through the Random Forest algorithm, a machine learning method that uses multiple decision trees to provide accurate yield estimations.

Beyond crops, Mongolia is pioneering the use of computer vision to manage livestock. Recent pilot programs have used AI to count sheep and goats directly from video footage as they graze. While challenges like drone costs and the need for specialized skills remain, the country is investing in domestic talent. This commitment to technical excellence has already propelled Mongolia to 11th globally in the Open Data Inventory rankings.

Mongolia is undergoing a rapid digital transformation through its Vision 2050 strategy, aiming to evolve into a regional tech leader by the middle of the century. The initiative focuses on diversifying the national economy beyond mining by building a human-centered digital government. A core component of this shift involves the National Statistics Office (NSO) transitioning from manual data collection to sophisticated digital systems that treat data as a strategic national asset.

The integration of AI is particularly transformative for Mongolia’s agricultural sector. Collaborating with the UN Global Platform, the NSO now employs remote sensing—scanning the Earth via satellite—to automate crop classification. They utilize the Spectral Angle Mapper (SAM) method to identify specific crops like wheat and potatoes from imagery. This data is processed through the Random Forest algorithm, a machine learning method that uses multiple decision trees to provide accurate yield estimations.

Beyond crops, Mongolia is pioneering the use of computer vision to manage livestock. Recent pilot programs have used AI to count sheep and goats directly from video footage as they graze. While challenges like drone costs and the need for specialized skills remain, the country is investing in domestic talent. This commitment to technical excellence has already propelled Mongolia to 11th globally in the Open Data Inventory rankings.