Chinese Air Force Uses AI System for Battle Planning in Large-Scale Operations
نظرة سريعة
- The Chinese air force is employing an AI-enabled "intelligent strike planning system" for battle plans involving over 100 units, as revealed in a state television documentary.
- The system prioritizes targets, coordinates attack waves, and allocates tasks, having been used multiple times in training exercises.
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لماذا يهم
A state television documentary revealed that the Chinese air force is using an AI-enabled system for battle planning in operations involving over 100 units. The system was developed by a team led by Senior Colonel Deng Jianping to support training exercises.
The Chinese air force is using an AI-enabled system to draw up battle plans for operations involving more than 100 units, according to a state television documentary.
The “intelligent strike planning system” was designed to help commanders and pilots by prioritising targets, coordinating attack waves and allocating specific tasks to units, the CCTV programme broadcast on Sunday said, adding that it had been used “multiple” times.
The aerial warfare system was developed by a team led by Senior Colonel Deng Jianping to support training exercises that have featured increasingly large formations and different types of aircraft.
With “hundreds of targets and dozens of formations” moving at high speed, traditional calculation methods could not keep up, Deng told the CCTV documentary series Zhisheng (Achieving Victory), which was broadcast to celebrate the 99th anniversary of the PLA.
“The hardest part isn’t writing code or building models. It’s thoroughly understanding battlefield logic. Targets, firepower, penetration and damage assessment – the entire strike chain,” Deng said.
He added that if there was even a “slight flaw in the logic”, it could make the difference between victory or defeat.
أسئلة مفتوحة
- What specific types of operations has the system been used for?
- What are the system's current limitations or vulnerabilities?
- How effective has the system proven in actual training scenarios?






