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Learning by AI: Market Intelligence and Exporting

Author

Listed:
  • Alexis Antoniades
  • Chuan He
  • Zheming Liang
  • Mingzhi Jimmy Xu

Abstract

Early adoption of artificial intelligence (AI) reshaped how firms responded to market dynamics by enhancing data collection and analysis. Linking China's universe of customs shipments to millions of online job ads, we tracked AI hiring in sales, marketing, and analytics to build a firm-level proxy for non-production AI and map its exposure across products within firms. To structure our analysis, we introduce a model in which firms confront asymmetric information about heterogeneous consumer preferences and show that AI mitigates these frictions by sharpening firms' ability to learn demand patterns across markets. The model predicts — and the data confirm — that AI-intensive firms fine-tune their product mix and prices with greater precision: they are more likely to export, expand their product lines, and adjust market choices. Crucially, this refinement appears as narrower price dispersion but wider quantity dispersion across destinations — effects strongest for differentiated goods, larger firms, and sales to high-income economies. Together, the evidence shows that AI eases demand-side information frictions, allowing firms to optimize their global reach strategies.

Suggested Citation

  • Alexis Antoniades & Chuan He & Zheming Liang & Mingzhi Jimmy Xu, 2026. "Learning by AI: Market Intelligence and Exporting," CESifo Working Paper Series 12456, CESifo.
    • Handle: RePEc:ces:ceswps:_12456
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    Keywords

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    JEL classification:

    • F14 - International Economics - - Trade - - - Empirical Studies of Trade
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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