By Michael Yao    Photo：CANVA

     Artificial intelligence is a critical driving force behind the new round of technological revolution and industrial transformation. Accelerating the development of next-generation AI is a strategic issue that bears on whether China can seize the opportunities presented by this new wave of technological and industrial change. In recent years, the Chinese government has placed great emphasis on the transformation and opportunities brought by AI advancements, issuing a series of policy documents including the New-Generation Artificial Intelligence Development Plan, the *Three-Year Action Plan for Promoting the Development of the New-Generation Artificial Intelligence Industry (2018–2020)*, and the Guidelines on Accelerating Scenario Innovation to Promote High-Quality Economic Development through High-Level Application of Artificial Intelligence. These initiatives have laid the strategic direction and policy foundation for China's AI development.

    Since 2023, with the rapid iteration and widespread application of generative AI models like ChatGPT and DeepSeek, a new wave of global enthusiasm for artificial intelligence has emerged. Countries worldwide now view AI as a key force reshaping future competitive landscapes. They are, on one hand, increasing R&D investment and policy support, and on the other, actively building corresponding governance frameworks. In September 2025, seven Chinese government departments – including the Ministry of Transport, the National Development and Reform Commission, the Ministry of Industry and Information Technology, the National Data Bureau, the National Railway Administration, the Civil Aviation Administration, and the State Post Bureau – jointly issued the Implementation Opinions on "AI + Transportation". This document outlines specific tasks across four key areas: enhancing the supply of key technologies, accelerating the empowerment of innovative scenarios, strengthening the guarantee of core elements, and optimizing the industrial development ecosystem. Its goal is to promote the large-scale, innovative application of artificial intelligence in the transportation sector.

Demand-Oriented Scenario Empowerment and Breakthroughs in Practical Application

During the formulation process of the Implementation Opinions, the administration fully incorporated the application needs and practical achievements of various industry entities. Focusing on key areas such as industry safety, operations, travel, logistics, regulation, and planning and construction, it systematically outlined the innovative empowerment scenarios for "AI + Civil Aviation" and proposed a framework for intelligent application scenarios. This framework clearly addresses two critical questions: "Where is AI applied?" and "What problems does it solve?"

Looking at specific areas:

In the realm of "AI + Safety," the focus is on scenarios including flight safety and aircraft maintenance, airport operational and security safety, air traffic control risk warning and emergency response, as well as general aviation and low-altitude safety assurance. Efforts will promote the application of technologies enabling proactive intelligent risk perception, precise warning, and rapid optimized response.

In "AI + Operations," the focus is on scenarios such as flight scheduling and operation dispatch, airport flight support and resource allocation, air traffic control command and capacity management, and multi-stakeholder operational coordination. This will drive intelligent upgrades in multi-source data fusion and analysis, operational situational awareness and prediction, and dynamic optimization of operational strategies.

In "AI + Travel," the focus is on scenarios including seamless passenger travel, personalized services, and intelligent customer service. This involves promoting applications like precise recommendations, itinerary planning, revenue optimization, streamlined check-in and clearance, and smart guidance to enhance the immersive intelligent service capabilities of civil aviation.

In "AI + Logistics," the focus is on scenarios such as the digital integration of logistics information, efficient air cargo operations, and the move towards reduced personnel or fully unmanned logistics support. This includes advancing the implementation of technologies like AI vision monitoring, intelligent dispatching, and embodied intelligence to reduce costs, improve quality, and increase efficiency in air logistics.

In "AI + Regulation," efforts will be made to elevate the application level of AI technology in scenarios such as safety supervision, market oversight, and digital government services, thereby enhancing the industry's governance capacity.

In "AI + Planning and Construction," the goal is to improve the capabilities for intelligent decision-making, precise management and control, and dynamic optimization within civil aviation planning and construction.

Strengthening the Supply of Supporting Elements and Guiding Collaborative Integration and Innovation

Regarding the reinforcement of essential element supply for the high-quality development of "AI + Civil Aviation," the Implementation Opinions states that efforts should focus on three key areas: the development of high-quality datasets, the construction of infrastructure platforms, and the research on industry-specific models and algorithms, in order to enhance the foundational support capabilities of AI in the civil aviation sector. To this end, the Implementation Opinions proposes a series of concrete work measures. In terms of high-quality dataset development, it calls for promoting the integration and fusion of multi-stakeholder data, establishing standards for constructing high-quality datasets across the entire lifecycle, and forming the corpora and knowledge bases necessary to support industry-specific large models. Regarding infrastructure platform construction, it emphasizes advancing the building of civil aviation computing infrastructure and industry data circulation and utilization infrastructure, while strengthening the efficient construction and secure operation of information infrastructure. In the area of industry-specific model and algorithm research, it advocates promoting the research and development of large civil aviation models tailored to the industry's characteristics, achieving breakthroughs in a batch of specialized intelligent algorithms for vertical scenarios, establishing an algorithm evaluation mechanism, and building a shared and efficient algorithm ecosystem.

Meanwhile, the Implementation Opinions points out the need to deepen the profound integration of the industry and related sectors with artificial intelligence, accelerating the formation of a development pattern characterized by collaborative progress and integrated innovation. Regarding industry integration, by integrating the resources of airlines, airports, air traffic control units, service support organizations, and research institutes, a civil aviation AI integration and innovation ecosystem featuring shared resources, coordinated interaction, and co-creation and sharing should be established. This will achieve complementary advantages and collaborative innovation in areas such as policy and standard formulation, model and algorithm R&D, intelligent product development, and application scenario promotion. In terms of cross-sector industrial integration, it is necessary to strengthen coordination and linkage between civil aviation and its upstream and downstream industrial chains, building a collaborative system featuring technology interoperability, data trustworthiness, process interembedding, and ecological mutual promotion. Focusing on areas such as "Civil Aviation + Digital Industry" and "Civil Aviation + Manufacturing Industry," the aim is to promote collaborative R&D among technology companies, manufacturing enterprises, and civil aviation units, and to guide the intelligent upgrading of domestically produced civil aviation equipment.

Advancing Steadily in Phases and Joining Forces to Ensure Coordinated Implementation

To ensure the orderly and steady progress of related work, the Implementation Opinions proposes a two-phase construction goal for the high-quality development of "AI + Civil Aviation": By 2027, the integrated development of artificial intelligence with key civil aviation areas such as safety, operations, travel, logistics, regulation, and planning and construction will be pioneered. Initial success will be achieved in the construction of core AI supporting elements, including high-quality civil aviation datasets, infrastructure platforms, and industry-specific models and algorithms. Breakthroughs will be made in key common technologies for civil aviation AI, forming a batch of exemplary scenarios with industry-leading significance, as well as intelligent products and applications with core competitiveness. By 2030, extensive and deep integration of artificial intelligence with all areas of civil aviation will be realized. The civil aviation AI governance system and safety and security system will be gradually improved, forming a range of high-quality datasets, infrastructure platforms, and industry-specific models and algorithms. AI will effectively enhance the industry's safety levels, operational efficiency, service quality, and resource allocation capabilities, becoming a powerful engine driving the high-quality development of civil aviation.

To ensure the achievement of these construction goals, efforts will subsequently pool the strengths of various stakeholders across the civil aviation sector, coordinating and promoting related work in a unified manner. The focus will be not only on "using AI," but also on "using AI well." In terms of organizational support, the leading role of the Smart Civil Aviation Construction Leadership Group in overall coordination, supervision, and implementation will be fully utilized to promote the execution and realization of key tasks. Regarding safety and security, a full lifecycle safety management system for civil aviation AI systems will be established, strengthening algorithm security assessments, data and information security protection, and reinforcing monitoring, early warning, and emergency response mechanisms for AI applications. For talent support, efforts will be intensified in cultivating interdisciplinary talents who integrate AI with civil aviation operations, and mechanisms for the introduction and incentivization of AI professionals will be established. In terms of policy support, the development of AI application specifications and industry standards tailored to civil aviation scenarios will be accelerated, forming an AI standards system encompassing data governance, algorithm interfaces, application performance, and testing certification. Regarding demonstration and leadership, support will be provided for the construction of a number of AI pilot projects with demonstrative and leading roles, strengthening the overall coordination, business guidance, and experience dissemination of pilot and demonstration projects undertaken by various departments and local authorities, thereby providing sustained momentum for the digital and intelligent transformation of civil aviation.

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