Xi Jinping at 2026 World AI Conference: Global Innovation Active, China's Core Industry Tops RMB 1.2 Trillion

A new wave of intelligent transformation is sweeping the world. Artificial intelligence is reshaping economic and social development models in all dimensions and exerting profound influence on the progress of human civilization. At the opening ceremony of the 2026 World Artificial Intelligence Conference and High-level Meeting on Global AI Governance, President Xi Jinping said global AI technology innovation has entered an unprecedentedly active period. The combined effect of intelligent technologies featuring intelligent connectivity of all things, human-machine collaboration, cross-sector integration, and co-creation and sharing has generated enormous energy, bringing both huge opportunities and governance challenges. As AI technologies continue to iterate, application scenarios expand, and market adoption accelerates, issues such as technology ethics, data security, and regulatory systems have become more prominent. It is necessary to better coordinate development and security, balance innovation and governance, and improve AI-related institutions and rules.

Internationally, global AI governance has accelerated in recent years. Developed economies in Europe and the United States, leveraging first-mover advantages, have moved early to build and improve laws, industry norms, and regulatory mechanisms. The European Union has enacted the Artificial Intelligence Act, setting tiered regulatory standards and red lines for technology applications. The United States has released a national unified AI regulatory legislative framework, focusing on tiered management of high-risk AI, intellectual property, data security, and algorithm transparency, and strengthening unified federal rules. While countries have broadly reached consensus on AI safety governance, competition over governance discourse and rule-making power is intensifying.

Domestically, China's AI industry is developing rapidly, with high innovation activity and broad application scenarios, and has gradually formed large-scale industrial advantages. In 2025, the core AI industry scale exceeded RMB 1.2 trillion. However, supporting institutional systems lag behind. In areas such as computing resource allocation, cross-border data flows, technology commercialization and industrial application, and social governance, as well as data compliance, ethical constraints, security risk control, and intellectual property protection, regulatory blind spots and rule gaps remain.

In computing resource allocation, relevant authorities are building a price and standard system for computing products, creating a unified computing-network monitoring and dispatching platform, and strengthening comprehensive support for aggregation of diverse computing resources, identifier registration, interconnected scheduling, and data monitoring. In data sharing, the rights and obligations of data resource holders, processing users, and product operators in data circulation are being clarified, and a data revenue distribution mechanism that balances the interests of all parties is being explored. In technology commercialization, a number of concept verification centers are being built, pilot-testing service platforms are being established, and supply lists for pilot-testing platforms are regularly published and updated. In industrial application, registration and approval materials are being simplified, inspection, testing, and certification procedures are being optimized, and product application and promotion are being accelerated.

In response to prominent problems such as unclear intellectual property definitions and difficulty in rights protection in the AI field, relevant parties are further clarifying the ownership, lawful use boundaries, and infringement determination standards for new types of intellectual property, including training data, algorithm models, and AI-generated content. They are improving mechanisms for IP traceability, evidence preservation, rights protection, and punishment, cracking down on illegal misappropriation of training data and tampering with generated content, and regulating authorized use of AI achievements. At the same time, taking into account both corporate R&D interests and society's need for sharing, they encourage the co-building of open-source ecosystems, respect enterprises' independent choices, and establish mechanisms for sharing AI research results and technical experience.

In safety governance, China adheres to the principle of placing equal emphasis on development and security and is building a comprehensive, multi-level, and routine AI safety governance system. Focusing on key areas such as data security, technology security, and industrial security, and targeting high-risk scenarios such as generative AI, intelligent driving, and intelligent risk control, it is establishing and improving a full-chain mechanism covering risk assessment, dynamic monitoring, early warning and prevention, and emergency response. Enterprises' primary safety responsibilities are being consolidated, and full-process safety management of AI product R&D, launch, and operation is being regulated. Cross-departmental coordinated supervision, joint law enforcement, and risk-sharing mechanisms are being improved to prevent and resolve risks such as cross-border risk transmission and technology loss of control.

In science and technology ethics, China adheres to principles of people-centeredness, AI for good, fairness and inclusiveness, and collaborative governance, and is improving a science and technology ethics governance system suited to AI development. In response to problems such as algorithmic discrimination, big-data price discrimination against existing customers, deepfakes, and privacy infringement, AI ethics norms are being refined. A full-process ethics review, assessment, and supervision system covering technology R&D, product deployment, and iterative updates is being established, and routine compliance reviews are being implemented. Industry self-discipline and social supervision are being strengthened, the boundaries of commercial application are being regulated, and the ethical bottom line for the healthy and sustainable development of AI is being upheld.

In global governance, China is actively participating in the building of the global AI governance system and promoting an inclusive, open, balanced, and beneficial global AI governance landscape. Through multilateral mechanisms such as BRICS and the Shanghai Cooperation Organisation, China is sharing AI development and governance experience and enhancing its voice in rule-making. Adhering to extensive consultation, joint contribution, and shared benefits, China is promoting dialogue and cooperation among countries in AI technical standards, safety compliance, risk prevention and control, and ethical norms, breaking down technology monopolies and rule barriers, and opposing unilateralism and technology decoupling in AI governance.