China's AI firms hit fragmented global rules as overseas expansion gathers pace
摘要：
by WU YangyuAs Chinese artificial intelligence companies push into overseas markets, execu... by WU Yangyu
As Chinese artificial intelligence companies push into overseas markets, executives say their biggest challenges have little to do with model performance or computing power. Instead, a patchwork of global rules on data, AI safety and deployment is shaping how — and whether — large models can be rolled out abroad.
At home, Chinese AI developers operate under a relatively cautious but well-defined data governance regime that provides a clear compliance baseline. Problems tend to arise once models cross borders, where regulatory approaches diverge sharply from market to market and no single international standard governs how foundation models are trained, deployed or monitored.
Europe sits at one end of the spectrum. Companies operating there must comply with the General Data Protection Regulation as well as the European Union's AI Act, which impose strict requirements on data localization, model transparency and algorithm governance, often extending preparation cycles and raising costs.
Many emerging markets sit at the other end. Executives said regulators in parts of Southeast Asia, the Middle East and Africa place greater emphasis on data sovereignty, local ecosystems and supply-chain trust, frequently requiring partnerships with domestic firms or onshore data deployment as a condition for market access.
For companies operating across multiple jurisdictions, these differences are increasingly difficult to manage operationally. Data flows, deployment architectures, computing supply models and security frameworks often have to be redesigned on a country-by-country basis, extending preparation timelines and increasing execution risk.
Traditional trade-policy tools such as trade missions or financing support offer limited help, while companies face growing exposure to cross-border intellectual property disputes, compliance conflicts and legal grey zones shaped by geopolitical tensions.
Few overseas projects have been blocked outright by regulation so far, people involved in international rollouts said, but regulatory divergence is already slowing delivery as each new market requires fresh legal analysis, technical adaptation and due diligence on local partners.
Chinese AI developers also face a structural disadvantage in global competition. Unlike US technology firms that benefit from relatively integrated international ecosystems, Chinese companies often enter overseas markets as isolated players, weakening collective leverage and confusing potential partners.
Executives said companies are not seeking subsidies or direct financial support, but rather stronger institutional backing, including clearer coordination on cross-border legal disputes and more predictable frameworks for overseas operations.
Data governance remains a central pressure point. Foundation-model development depends on access to diverse global datasets, yet approval processes for cross-border data flows remain lengthy even for anonymized or aggregated data. More streamlined approval pathways within existing legal frameworks could help speed testing and iteration while preserving security and privacy safeguards.
Clearer coordination at the national level in international digital cooperation could also ease frictions. Executives said clearer signals on how Chinese AI firms are positioned across different segments would help foreign regulators and industry bodies better understand the ecosystem, reduce overlap among Chinese players and lower compliance costs.
