China Pledges Continued Participation in Global AI Governance

Chinese Premier Li Qiang told attendees at the World Economic Forum's "Summer Davos" Annual Meeting of the New Champions in Dalian on June 24, 2026, that China will continue to participate in global AI governance in a responsible and constructive manner, according to Xinhua and China Daily. Li warned, per an AFP wire carried by France24 and the Straits Times, that "we cannot ignore increasingly prominent risks of losing control of technology and ethical lapses," and cited concerns about labor-market disruption and security risks. Days earlier, around June 17-18, China's foreign minister Wang Yi said at a press conference releasing a whitepaper titled "More Just and Equitable Global Governance" that China is "accelerating the establishment of a global AI cooperation organization," per CNBC. Zhao Haibing, vice chair of a top Chinese economic agency, pushed back at the same event on "closed, exclusive and monopolistic" approaches to technology development.

The governance mechanisms that matter most to practitioners are model export controls, cross-border data rules, and safety-testing standards. Multilateral proposals like the one China is describing typically struggle to translate quickly into aligned technical standards, because national-security and industrial-policy priorities push states toward divergent rules. In practice, that tends to mean continued fragmentation in compliance requirements across jurisdictions rather than a single harmonized regime.

Public remarks by political leaders at high-profile forums raise the political salience of AI governance but do not by themselves create interoperable regulatory regimes. CNBC frames Beijing's messaging as emphasizing multilateral cooperation and outreach to the Global South through channels such as BRICS and the Shanghai Cooperation Organization, part of a broader Chinese effort to shape international AI rulemaking. Similar past international initiatives show that headline announcements are typically followed by long negotiations over technical definitions, enforcement mechanisms, and participation criteria that can take years to resolve.

Expect continued policy uncertainty in the near term. Organizations operating AI systems across jurisdictions typically benefit from investing early in provenance metadata, automated compliance auditing, and staged, modular rollout architectures when headline political attention to AI governance increases, since specific binding rules tend to lag the political announcements by a wide margin.

Concrete follow-through would include draft texts submitted by Chinese delegations to existing multilateral fora, bilateral or plurilateral memoranda of understanding on AI safety testing and information sharing, and specifics in China's whitepaper on export controls, certification regimes, or data-sharing frameworks. Also worth watching: whether China engages with existing institutions or builds parallel ones such as the proposed global AI cooperation organization, and how major technology-exporting states respond, since that will shape cross-border model distribution and compliance burdens for vendors. The next major venue is the World AI Conference and High-Level Meeting on Global AI Governance planned for Shanghai in July 2026.