Mongolia is aggressively pursuing a digital transformation through its Vision 2050 strategy, aiming to evolve from a mining-dependent economy into a high-income regional leader. The National Statistics Office (NSO) is at the forefront of this shift, transitioning from labor-intensive manual data collection to sophisticated register-based methods and satellite-driven analysis. By integrating thirty databases from various state organizations, the government is creating a unified ecosystem designed to improve public services and eliminate corruption through increased transparency.

The most innovative applications are emerging in the agricultural sector, where traditional methods of counting livestock and assessing crops are being replaced by automated systems. Utilizing the Spectral Angle Mapper (SAM) method and Random Forest algorithms, the NSO can now identify wheat and potato crops directly from satellite imagery and drone data. This technical leap allows for more accurate yield estimations without the need for thousands of manual questionnaires, which were historically prone to human error and significant delays.

In a notable pilot project, Mongolian officials successfully deployed an artificial intelligence application to count sheep and goats from video footage as they graze. While high-resolution imagery and drone operations remain costly, the country is investing in internal training to manage these technologies sustainably. These efforts have propelled Mongolia to 11th globally for data openness, signaling a successful fusion of nomadic heritage with cutting-edge data science and evidence-based governance.

Mongolia is aggressively pursuing a digital transformation through its Vision 2050 strategy, aiming to evolve from a mining-dependent economy into a high-income regional leader. The National Statistics Office (NSO) is at the forefront of this shift, transitioning from labor-intensive manual data collection to sophisticated register-based methods and satellite-driven analysis. By integrating thirty databases from various state organizations, the government is creating a unified ecosystem designed to improve public services and eliminate corruption through increased transparency.

The most innovative applications are emerging in the agricultural sector, where traditional methods of counting livestock and assessing crops are being replaced by automated systems. Utilizing the Spectral Angle Mapper (SAM) method and Random Forest algorithms, the NSO can now identify wheat and potato crops directly from satellite imagery and drone data. This technical leap allows for more accurate yield estimations without the need for thousands of manual questionnaires, which were historically prone to human error and significant delays.

In a notable pilot project, Mongolian officials successfully deployed an artificial intelligence application to count sheep and goats from video footage as they graze. While high-resolution imagery and drone operations remain costly, the country is investing in internal training to manage these technologies sustainably. These efforts have propelled Mongolia to 11th globally for data openness, signaling a successful fusion of nomadic heritage with cutting-edge data science and evidence-based governance.