The interplay between AI and technological relatedness in shaping regional innovation in Europe

This study examines how regional technological relatedness and local AI knowledge influence regional innovative activity, as measured by patenting activity. Using a novel three-way longitudinal dataset (670 four-digit CPC classes × 302 NUTS-2 regions × nine four-year periods, 1986–2021) and leveraging a deep learning-based identification of AI patents, we show that two broad mechanisms operate in parallel. First, in accordance with the extant literature, technologies that are cognitively close to a region’s existing patent portfolio enjoy higher patenting activity, confirming that relatedness remains a strong and persistent predictor of innovative output. Second, local AI endowments are positively associated with patenting across technological fields, even after conditioning on relatedness, indicating that AI plays an enabling and cross-cutting role in a given regional innovation system. Moreover, the interaction between relatedness and AI turns out to be negative and statistically significant, implying that AI attenuates the extent to which local innovative efforts depend on the technology’s proximity to the regional portfolio. In sum, AI appears to enhance overall local innovative activity while reducing its reliance on pre-existing regional knowledge structures.