Russian Prime Minister Mikhail Mishustin has called on the Federal Forestry Agency to accelerate the rollout of domestic artificial intelligence across its national operations.
Speaking during a working meeting with agency chief Ivan Sovetnikov, Mishustin urged the forestry service to replace older rigid automated systems with homegrown neural networks to modernize woodland oversight, the government press service reported.
Mishustin said that advanced algorithms can already handle a vast range of tasks instead of traditional machines governed by direct programming, according to remarks carried by the TASS news agency. He stressed that amendments introduced to the Forest Code in 2026 explicitly promote specialized software and geographic information systems to track wildfires, assist timber enterprises, and transition the country to a new forest management model.
Wildfire Tracking and Forest Code Reforms
The Federal Forestry Agency, known as Rosleskhoz, oversees state-owned woodlands across the Russian Federation. Russia holds approximately one fifth of the world's forested land, with expansive tracts of remote taiga stretching across Siberia and the Far East. Monitoring such enormous, isolated areas has long posed severe operational difficulties for rangers attempting to detect seasonal wildfires and illegal logging operations.
Recent legislative reforms aim to solve those logistical hurdles by shifting forestry oversight toward digital tracking. Mishustin emphasized that modern software tools and mapping networks must actively assist commercial timber operators while giving authorities real-time awareness of fire hazards across remote regions.
Drones and Neural Network Timber Audits
In response to the prime minister, Sovetnikov stated that Rosleskhoz is already shifting its daily operations toward domestic Russian artificial intelligence models. The agency plans to broaden the deployment of unmanned aerial vehicles, satellite remote sensing platforms, and machine learning tools across all regional branches.
Sovetnikov highlighted the practical impact of the technology by describing how inspectors measure harvested wood. In the past, a field inspector had to carry a measuring tape, calipers, a ruler, and paper to measure and mark every individual log by hand. Under a new application powered by a neural network, the system performs all necessary calculations automatically from just two photographs.
The agency is also deploying artificial intelligence to evaluate changes in forest characteristics during replanting initiatives. Sovetnikov announced that a comprehensive nationwide audit of all artificial reforestation volumes is scheduled for 2027, with algorithms slated to verify the planted areas and monitor sapling growth.
Domestic Robotics and Industrial Payback
The push for digital forestry tools aligns with a broader state campaign to expand domestic automation and robotics across Russian industries. Chelyabinsk Region Governor Alexey Teksler previously noted that domestically produced industrial robots can achieve financial payback within one to two years when manufacturers integrate them effectively and utilize state support programs.
Teksler pointed out that the Chelyabinsk region manufactures between 60 percent and 80 percent of Russia's industrial robots, depending on machine dimensions. The Urals manufacturing center has become a focal point for domestic automation equipment as national authorities encourage sectors from manufacturing to natural resource management to adopt homegrown high-technology equipment.
