Civil Aviation AI Innovation Laboratory (CAAC.AI) is an industry-level innovation platform for high-quality "AI + Civil Aviation" development.
The laboratory also drives low-altitude economy innovation — unmanned aircraft, eVTOL, low-altitude airspace management and service support — synergizing AI with this national emerging pillar industry.
Guided by "innovation-driven, safe and controllable; demand-oriented, scenario-empowered; foundations first, key breakthroughs; systematic layout, coordinated progress", we aim to become a strong engine of high-quality civil aviation development.
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Driving civil aviation development through technology innovation, in service of national strategy
Implementing the CPC Central Committee and State Council decisions on AI development: focused on key civil aviation scenarios and real bottlenecks, we promote deep AI integration into aviation business and lead the industry, through top-level design, toward coordinated and innovation-driven development.
By 2030, achieve broad and deep AI integration across all civil aviation domains, with steadily improving governance and safety systems, high-quality datasets, infrastructure platforms and industry models — effectively lifting safety, efficiency, service quality and resource allocation.
Safety first: a full-lifecycle safety management system for aviation AI with algorithm security assessment and data protection, releasing development potential step by step under strict risk control — true intelligence augments human judgment rather than replacing it.
The overall principles for high-quality "AI + Civil Aviation" development set out in the Implementation Opinions
Technology innovation as the primary driver, paired with a full-lifecycle safety management system, algorithm security assessment and data protection — AI that is safe and controllable.
Oriented to real pain points and bottlenecks, focusing on key aviation scenarios: 42 application scenarios mapped systematically, from pilots to scaled application.
Strengthening aviation AI foundations through high-quality datasets, infrastructure platforms and industry model research.
Integrating airlines, airports, ATC, service providers and research institutes into a shared, collaborative innovation ecosystem.
From "using AI" to "using AI well" — a multi-dimensional collaborative innovation system
AI application norms and industry standards for aviation scenarios — data governance, algorithm interfaces, performance and testing & certification
Civil aviation LLM R&D, specialized vertical-scenario algorithms and algorithm evaluation mechanisms
Full-lifecycle high-quality dataset standards; aviation computing and industry data circulation infrastructure
Deploying and promoting 42 application scenarios across six domains
Unmanned aircraft, eVTOL, low-altitude airspace management and service support — synergizing the low-altitude economy with AI
Full-lifecycle AI safety management: algorithm security assessment, data protection, monitoring & alerting
Pooling strengths from across civil aviation to coordinate and advance this work
Advance civil aviation LLM R&D, specialized vertical algorithms, and a shared, efficient algorithm ecosystem.
Guided by the 42-scenario reference, moving typical innovations from pilots to scaled application.
High-quality datasets, computing infrastructure and data circulation facilities — solidifying the AI foundation.
Integrating airlines, airports, ATC, service providers and research institutes into a co-created, shared ecosystem.
Full-lifecycle AI safety management with algorithm assessment, data protection and monitoring & alerting.
Grow composite talent bridging AI and aviation, with recruitment and incentive mechanisms.
Pooling strengths across civil aviation — not just "using AI", but "using AI well"
Leveraging the Smart Civil Aviation Leading Group's coordination and supervision
Full-lifecycle safety management with algorithm assessment and data protection
Growing composite talent with recruitment and incentive mechanisms
Accelerating AI application norms and industry standards into a standards system
Supporting exemplary AI pilots and promoting experience