AI brings significant opportunities for the stable development of foreign trade. Photo: TUCHONG

As a key driver of national economic growth, export trade plays a vital role in advancing high-standard opening up and building a new development pattern of “dual circulation.” In recent years, China has fully leveraged its comparative advantages, actively engaged in economic globalization, and witnessed rapid development in foreign trade, with both the scale and quality of exports steadily increasing. This has not only stabilized and upgraded export performance but also made an important contribution to high-quality economic development. With a relatively complete industrial system, strong supply capacity, and a balanced trade structure, China’s economy remains resilient and full of potential, and its long-term fundamentals for sustained growth are unchanged.

In the short term, however, sluggish external demand, intensifying geopolitical conflicts, and the rapid restructuring of global industrial and supply chains have heightened the risks of “disruptions,” “breakdowns,” and “disconnections.” Against this complex backdrop, the focus of China’s economic development has shifted from promoting growth to smoothing fluctuations and strengthening economic resilience. Enhancing export resilience—reflecting enterprises’ capacity to withstand external shocks and manage risks—has become a crucial means of adapting to changes in global demand and stabilizing foreign trade. Advancing the productive application of AI is an important way to build international competitiveness and gain the initiative in high-standard opening up. As an automated production tool, AI can propel productivity toward greater informatization, networking, and intelligence, support the digital and intelligent upgrading of entire industrial chains, and strengthen the independence and controllability of industrial and supply chains, thereby laying a solid foundation for their stability. Leveraging AI to enhance the security and stability of these chains can improve enterprises’ capacity to withstand and counter major external risks, offering a new perspective on strengthening the export resilience of Chinese enterprises.

Enhancing stability

AI can significantly reduce the risk of “disconnections” in supply chains and help enterprises stabilize their import supply chains in at least two ways. First, AI enables more accurate forecasts of demand for intermediate inputs. As intra-product specialization deepens, export enterprises have become increasingly reliant on such inputs. By processing historical and real-time data, AI allows enterprises to better anticipate market demand and operational risks, and adjust the import of intermediate goods accordingly, mitigating the impact of market fluctuations on production plans and lowering the risk of supply chain breaks. Second, AI enhances information transparency along the supply chain, fostering stable supply–demand relationships. With vast amounts of data generated by frequent interactions between supply chain nodes, AI can help enterprises assess the creditworthiness of upstream partners, select quality suppliers, and promote more reliable relationships between upstream and downstream enterprises, reducing disruption risks caused by defaults and similar issues.

A secure and stable import supply chain is essential to sustaining normal export operations. Today’s complex and volatile global and domestic economic conditions have brought significant uncertainty to exporters, requiring constant adjustment of production factor inputs. Security and stability in imports enable enterprises to make such adjustments more flexibly, cost-effectively, and securely. In this way, a secure and stable import supply chain supports the efficient allocation of production resources, ensures uninterrupted production and export operations, and bolsters an enterprise’s ability to manage external risks, thereby strengthening export resilience. In sum, applying AI helps build a secure and unobstructed import supply system by improving input-demand forecasting and strengthening supply–demand links, thus reducing the risk of supply chain “disconnections” and safeguarding production and exports, ultimately enhancing export resilience.

Increasing effeciency

In the production process, AI not only enables flexible manufacturing to offset the negative effects of demand shifts, but also optimizes the allocation of production factors to maximize output, ensuring high operational efficiency and preventing production disruptions from resource shortages—thereby consolidating the production chain. In the digital economy era, fierce international competition compresses enterprises’ survival space, pressuring them to seek ways to expand their international market shares. A stable production chain helps improve the quality of exported products. High-quality exports, in turn, form a solid foundation for greater export resilience. First, improved quality stimulates overseas demand. In highly competitive international markets, high-quality goods can meet the stringent requirements of foreign buyers, enabling enterprises to expand their export scale and capture greater market share. With a higher market share, these enterprises are better positioned to resist external shocks by relying on a stable demand network. Second, demand for high-quality products tends to be more stable. The theory of similar demand holds that income levels affect demand structure, meaning that high-income countries tend to import high-quality products, while low-income countries tend to import low-quality products. The higher the quality of exports, the stronger and more stable the demand and the greater the ability to withstand external shocks. In short, AI helps maintain stable production chains, allowing enterprises to channel more production resources into improving product quality and stabilizing foreign demand, thereby enhancing export resilience.

Customers are an important source for enterprises to obtain demand information and conduct production activities accordingly. However, high information acquisition and integration costs hinder the development and production activities of enterprises. Unlike traditional marketing methods, where enterprises laboriously collect customer demand information using human resources, AI can intelligently collect, organize, store and process product demand information, enhancing the enterprise’s ability to integrate and analyze overseas market information, lowering information costs and reducing friction. In addition, AI can capture and profile overseas consumer behaviors, intelligently analyze consumer preferences and demand trends, and improve enterprises’ understanding of international markets. Utilizing AI to process end-user demand data gives enterprises more accurate, timely insight into overseas demand conditions and consumer preferences, supporting personalized production for diverse needs and targeted marketing strategies for different markets. This lays the groundwork for expanding international sales channels. Breaking through information barriers in export trade not only diversifies exports but also extends the export sales chain, which in turn disperses risks, mitigates external shocks, and stabilizes export trade. When international demand or prices fluctuate sharply, a diversified product and market mix reduces overall volatility, while broader market reach reduces dependence on a few sources of demand. In summary, AI can reduce information search costs related to exports, support personalized production for diverse consumer demands, and implement targeted marketing strategies for different markets. This allows enterprises to implement diversified export strategies, expand export sales chains, and ultimately disperse export risks and enhance export resilience.

Improving resilience

From the perspective of industrial and supply chains, this article examines AI’s impact on export resilience through three key channels: stabilizing import supply chains, consolidating production chains, and expanding sales chains. Enterprise-level analysis shows that AI can effectively mitigate external demand shocks and boost export resilience. These three channels constitute vital pathways by which AI contributes to the improvement of export resilience. Heterogeneity analysis further indicates that AI’s positive impact on the export resilience of enterprises is particularly pronounced among enterprises oriented toward developed markets, those facing high export risks, capital- and technology-intensive enterprises, and those in the growth and maturity stages. AI also lowers the likelihood of unstable or one-off export relationships, reducing vulnerability in trade. Finally, AI enhances export resilience among upstream and downstream enterprises through spillover effects along the industrial chain.

The application of information technologies such as AI presents significant opportunities for the stable development of foreign trade. This article uncovers and confirms AI’s value in strengthening export resilience among enterprises, offering several policy insights: First, investment in sci-tech innovation and AI talent cultivation should be increased to holistically advance the industry. The construction of digital infrastructure and data resource systems should be optimized, and AI-related legal, regulatory, and technical standards refined to support healthy industry growth. Second, AI application scenarios should be innovated and enriched, and a full-chain, full-process AI application ecosystem established. Enterprises should be encouraged to develop application scenarios along entire industrial chains and to strengthen specialization and upstream–downstream collaboration. Meanwhile, the deep integration of AI technologies with traditional industries should be promoted to build a full-chain, full-process AI industry application ecosystem. Finally, AI industry layout should be optimized according to differences in export market structure, risk levels, labor intensity, and enterprise life cycle, to maximize AI’s “dividend effect” in enhancing enterprise export resilience.

Xin Daleng (professor) and Qiu Yue are from the School of Economics at Shandong Normal University.