 Learning by AI: Market Intelligence and ExportingAlexis Antoniades, Chuan He, Zheming Liang and Mingzhi Jimmy Xu No 12456, CESifo Working Paper Series from CESifo 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. Keywords: artificial intelligence; export behavior; product differentiation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_12456 Access Statistics for this paper More papers in CESifo Working Paper Series from CESifo Contact information at EDIRC. |
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