Industry Pain Point: Absence of AI Governance Standards Creates Cascading Issues
From September 22 to 24, 2026, the World New Energy Vehicle Conference (WNEVC) was held in Haikou, Hainan. Li Chuanhai, Vice President of Geely Auto Group and Director of Geely AutomotiveResearch Institute, publicly pointed out at the conference that while AI applications in the automotive industry are accelerating, the lack of unified AI governance standards has become a hidden risk source. This issue causes enterprises to operate independently, with inconsistent standards and incompatible interfaces, directly increasing industry-wide costs and creating safety vulnerabilities. Li Chuanhai called on the entire industry chain to collaboratively advance standardized AI governance, ensuring technological innovation adheres to established rules and benchmarks.
Core Issue: The Double Burden of Standard Fragmentation
The real-world impacts of missing AI governance standards manifest along two dimensions: cost and safety. Cost-wise, enterprises independently pursuing technical pathways results in redundant investments in testing and certification processes, wasting R&D resources. Safety-wise, incompatible interfaces may cause system integration failures, while inconsistent data governance practices heighten information leakage risks. Li Chuanhai emphasized that new energy and intelligent technologies are reshaping the global automotive technology ecosystem, creating an opening for global standard reconstruction. If China does not proactively participate in rule-making, it risks losing future technological的话语权 ( Authority in Setting Standards ).
Significantly, Li did not name specific companies or technical solutions but examined systemic shortcomings from an industry-wide perspective. This focus on foundational rules rather than individual technical metrics reflects a pivotal shift from performance competition to systemic competition across the sector.
Chinese Advantage: Existing Foundations Support Standard Output Capacity
Li outlined China’s track record in global standard participation: from early battery safety regulations and unified charging interfaces, to later functional safety standards (Definition: functional safety ensures systems maintain basic operation during misoperations or component failures) and data governance practices, China has developed comprehensive technical validation and industrial implementation capabilities. These prior achievements constitute the foundational support for participating in—and even leading—international standard development. The key inflection point is that global AI governance frameworks remain unfixed, giving Chinese technical proposals an opportunity window. Li’s team emphasized not China’s overriding advantage but the strategic initiative to “participate broadly, even lead”—translating China’s industrial实践经验 (Practical Experience) into international consensus.
Industry Recommendations: Breaking the Deadlock Mechanistically
Based on these insights, Li proposed actionable industry pathways: first, establishing cross-enterprise, cross-industry-chain AI governance dialogue platforms; second, promoting compatibility testing of core module interface protocols; third, forming quantifiable evaluation metrics for data collection, model training, and result auditing. He clarified that standardization does not stifle innovation but defines safety boundaries for iterative improvement, avoiding redundant trial-and-error.
Practical Recommendations: Who Should Act, Who Should Wait
Immediate action fits best对：Automakers’ R&D departments and Tier 1 suppliers should join regional or national AI governance pilot programs early, collect interface specifications and data format feedback, avoiding rework costs later; teams integrating AI modules such as smart cockpits or driver assistance should assess compatibility between existing systems and potential standards. Recommended to wait for：Smaller algorithm developers or new entrants need not build governance frameworks independently yet, waiting for industry association or leading enterprise-led standard drafts, then assessing compliance costs while concentrating resources on core algorithm optimization.
Final Thoughts
AI governance standardization is an inevitable step in industry maturation. Its value lies not in conforming technical pathways but in ensuring cross-module, cross-system, and cross-vehicle safety coordination. Whether Chinese automakers can leverage their eco-system advantages from new energy development to transform governance authority into global competitive advantage will determine the最终模样 (Final形态/landscape) of automotive industry rules over the next decade.