On November 19, 2025, the Civil Aviation Administration of China officially issued the "Implementation Opinions on Promoting the High Quality Development of 'Artificial Intelligence+Civil Aviation'". This is the first systematic top-level design document for the development of artificial intelligence in the civil aviation field, following the State Council's "Opinions on Deepening the Implementation of 'Artificial Intelligence+' Action" and the seven departments' "Implementation Opinions on 'Artificial Intelligence+Transportation'". It marks the official entry of the civil aviation industry into a new stage of intelligent development.

Smart Load Allocation: Bring Flight Resources to Life

At the cargo terminal of Shenzhen Airport, a flight that is about to depart is carrying out cargo loading. Unlike traditional manual loading, the staff here only need to use an intelligent system to real-time grasp information such as changes in flight cargo demand, cabin status, and cargo characteristics. The system automatically generates the optimal loading plan. This is a vivid practice of the scenario of "intelligent loading of flight cargo and dynamic allocation of resources". This scenario is based on changes in flight cargo demand, flight schedule adjustments, cargo characteristics, load balancing, cabin status, and other information to construct a flight cargo loading model, achieving flexible and efficient allocation of flight resources for luggage, cargo, mail, and other needs. By constructing a large model of intelligent cargo loading and dynamic resource allocation algorithm, scientifically analyzing and predicting cargo booking demand, and combining luggage, cargo, mail weight, urgency, size, transportation requirements, and aircraft cabin capacity and load parameters, the aircraft cabin resource allocation plan is dynamically adjusted.  

When there is a change in flight schedule, temporary increase or decrease in cargo, etc., the system can quickly recalculate and optimize the allocation of cabin resources within 30 seconds, ensuring the safe operation of flights while maximizing belly loading rates and airline cargo revenue. At the same time, the system can also link with the ground freight support process, optimize the loading and unloading sequence and time of goods, and improve the efficiency of ground operations. This scenario is currently in the exploratory and practical stage, and has been piloted and applied in some airports.

Intelligent warehousing: from "people looking for goods" to "goods looking for people"

Entering the intelligent cargo warehouse at Shanghai Pudong Airport, AGV unmanned transport vehicles are orderly shuttling between shelves, with robotic arms accurately sorting goods, and the entire warehouse is almost devoid of staff. This is the transformation brought about by the "Intelligent Aviation Logistics Warehouse Management" scenario.  

This scenario utilizes artificial intelligence technology to achieve intelligent management of incoming container sorting, pick-up scheduling, and bulk cargo handling, as well as automated operations such as unmanned warehouses and outbound palletizing, and efficient operation of various warehouse scheduling and AGV vehicle collaborative handling. The application scenarios cover multiple aspects such as intelligent sorting of inbound containers, unmanned intelligent warehouses, intelligent booking of inbound pick-up, intelligent distribution of bulk cargo boards, intelligent sorting of bulk cargo boards, intelligent storage of containers, intelligent storage of bulk cargo (palletized goods), container scheduling, special transport warehouse scheduling, and automatic guided vehicle (AGV) scheduling in the warehouse.  

By integrating flight and cargo information, utilizing operations research, intelligent algorithms, and visual recognition technologies, the automation and digital management of the entire process from container sorting, palletizing, to warehouse scheduling can be achieved. The system establishes a mathematical model to generate the optimal allocation plan, uses algorithms to achieve automated control of warehousing operations, optimizes the picking process through a reservation platform and real-time monitoring, and intelligently manages bulk sorting, cargo diversion, and various warehousing scheduling, greatly improving logistics efficiency and regulatory compliance. This scenario is also in the stage of exploration and practice, and has been promoted and applied in multiple large hub airports.  

Unmanned operation: creating a new benchmark for "black light warehouse"

At the cargo terminal of Guangzhou Baiyun Airport, an unmanned tractor is steadily driving along a predetermined route, automatically completing cargo loading and unloading operations; In the cargo security inspection area, the intelligent security inspection system automatically identifies dangerous goods and other special goods through visual recognition technology. This is a typical application of the scenario of "automated handling and unmanned operation of aviation logistics".  

This scenario deploys automated equipment and unmanned cargo aircraft to achieve unmanned handling and transportation of goods throughout the entire process. Deploy automatic shelves, unmanned forklifts, and intelligent loading and unloading arms in the cargo loading and unloading area, complete automatic handling and loading and unloading based on cargo information and instructions, and use robot operating systems (ROS) to achieve equipment control and coordination, realizing unmanned handling of the entire process from apron to warehouse location, greatly reducing cargo processing time. Unmanned cargo aircraft integrate sensor information, achieve autonomous takeoff and landing, flight, and obstacle avoidance through autonomous navigation algorithms, and complete direct delivery to remote areas according to preset routes. The intelligent and unmanned operation of aviation logistics achieves real-time data interaction through digital twins, forming a closed-loop system for the entire operation chain. The promotion and application of this scenario will effectively solve the labor shortage problem in the aviation logistics industry, improve operational efficiency and safety.  

The relevant person in charge of the Development Planning Department of the Civil Aviation Administration of China stated that the release of the "Implementation Opinions" will further clarify the path of the industry's future intelligent development, guide all units to break through the innovation empowerment of artificial intelligence in key scenarios, and build the core supporting elements of civil aviation artificial intelligence. Next, the Civil Aviation Administration of China will continue to strengthen policy coordination and organizational promotion, deepen industry publicity and experience promotion, actively promote the practical implementation of artificial intelligence+civil aviation key scenarios, and accelerate the formation of a coordinated and innovative development pattern.  

With the deep application of artificial intelligence technology, China's civil aviation industry is undergoing a profound intelligent transformation. From intelligent loading to intelligent warehousing, from unmanned operations to full process digital management, artificial intelligence is reshaping every aspect of aviation logistics, injecting strong impetus into the high-quality development of the industry.Editor/Yang Meiling