Artificial intelligence (AI) standardization is a critical component in the development and regulation of this rapidly evolving industry. According to reports, the AI standard architecture consists of six key components: basic standards, platform/support standards, key technical standards, product and service standards, application standards, and security/ethical standards. These layers form a comprehensive framework that supports the growth and integration of AI technologies across various sectors.
With the AI industry experiencing rapid expansion, the need for standardized guidelines has become more urgent than ever. On January 18, the National Standardization Administration Committee officially established the National Artificial Intelligence Standardization Group and an Expert Advisory Group. The group is led by Zhao Bo, the dean of the China Electronics Technology Standardization Research Institute, while the vice-chair includes representatives from leading companies and institutions such as Alibaba Cloud, the Chinese Academy of Sciences, Peking University, and the Beijing University of Aeronautics and Astronautics. Pan Yunhe, an academician of the Chinese Academy of Engineering, serves as the head of the expert advisory group.
The National AI Standardization Group plays a crucial role in coordinating and planning the development of AI standards, including the formulation of China’s national AI standardization strategy, system, and policies. It also focuses on international standardization efforts, ensuring technical harmonization and the establishment of foundational AI standards. The expert advisory group, composed of renowned AI scholars and professionals, provides strategic guidance on the overall planning and policy-making for AI in China.
Zhao Bo emphasized that standardization is fundamental to AI development, acting as both a driver of innovation and a competitive advantage. “China has a solid foundation in AI, but infrastructure, policies, and standards still need improvement,†he stated. He further highlighted that the advancement of AI standards directly impacts the industry’s healthy growth and global competitiveness.
This initiative aligns with the Ministry of Industry and Information Technology's "Three-Year Action Plan for Promoting the Development of a New Generation of Artificial Intelligence Industry (2018–2020)." The plan outlines specific goals, including the establishment of an AI support system, standardization framework, and security assurance mechanisms.
Globally, countries like the U.S., EU, and Japan are also investing heavily in AI standardization. For instance, the U.S. has released its National AI Research and Development Strategy, the EU has launched the Human Brain Project, and Japan has implemented a comprehensive safety project focused on AI, big data, and IoT. These efforts reflect a shared goal of securing technological leadership through strong standardization strategies.
In practice, many AI products—such as facial recognition systems, smart speakers, and service robots—are already on the market. However, inconsistent quality and lack of unified standards remain major challenges. Standardizing these technologies will not only enhance product performance but also promote faster innovation and adoption.
Ethical concerns, such as the “trolley problem†in autonomous vehicles or privacy issues like Apple’s fingerprint data leaks, also require clear safety and ethical guidelines. Moreover, the current trend of tech giants creating proprietary platforms and frameworks leads to data silos and limited interoperability. Unified standards can help bridge these gaps, enabling smoother collaboration between vendors.
Wu Wenjun, deputy head of the National AI Standardization Group, noted that basic, technical, and ethical standards are all central to future AI development. “Research and discussions in these areas will go hand in hand,†he said.
From an enterprise perspective, Junda, vice president of Science and Technology, stressed the urgent need for standardization. “We need a clear system framework, defined capabilities for AI integration, and consistent data and evaluation standards,†he added.
The AI standard architecture, as outlined in the “Artificial Intelligence Standardization White Paper†by the China Electronics Technology Standardization Institute, includes six main categories. Basic standards cover terminology, reference architecture, data, and testing. Platform/support standards integrate hardware, software, networks, and data. Key technical standards focus on natural language processing, computer vision, biometrics, and VR/AR. Application standards address industry-specific needs, while product/service standards define intelligent products and services. Security and ethical standards run throughout the entire structure, ensuring responsible AI development.
Huawei, for example, views AI as an enabler for enterprise efficiency. Song Zixuan, vice president of Huawei Cloud, emphasized the importance of open-source initiatives in standardization. “Open source has become a de facto standard in the industry,†he said. “Including it in the standard-setting process will ensure practical and effective standards.â€
Overall, the push for AI standardization is not just about regulation—it’s about shaping the future of technology, ensuring safety, fairness, and global competitiveness. As the AI landscape continues to evolve, well-defined standards will play a vital role in guiding its sustainable growth.
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