Artificial Intelligence and Export Performance: Insights from OECD Countries

This study investigates the effects of artificial intelligence (AI) investments and research and development (R&D) expenditures on export performance across 15 OECD countries. The analysis is conducted using a panel dataset covering the period from 2013 to 2023 and employs the Method of Moments Quantile Regression (MMQR) approach. This method allows for examining how the impacts of AI and R&D expenditures on export performance vary across different quantiles of the conditional distribution, rather than focusing solely on average effects. The findings reveal that the relationship between AI investments and export performance is neither linear nor homogeneous and differs depending on countries’ export performance levels. In particular, AI investments are found to exert a suppressing effect on exports in the short run, while simultaneously reducing volatility and playing a stabilizing role in export performance. The effects of R&D expenditures are observed to be more pronounced in countries with low and medium levels of export performance, whereas they weaken at higher export levels. Overall, the results highlight the necessity of designing AI and R&D oriented policies within an integrated, differentiated, and country-specific framework that accounts for heterogeneity in export performance across OECD economies.