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<p>In the context of a new round of technological revolution intersecting with transformations in the airspace economy, how Artificial Intelligence (<i>AI</i>) empowers the development of the Low-altitude economy (<i>Lae</i>) has become a forefront issue in theoretical research and policy practice. Using panel data from 2012–2022 for 30 Chinese provincial regions, we construct composite indices for AI and Lae and employ the entropy method, kernel density estimation, a spatial Durbin model, spatial mediation analysis and artificial neural networks to comprehensively evaluate AI’s influence on low‑altitude economic growth. The results show that: AI has a significant inverted U-shaped impact on Lae, with diminishing marginal returns after a certain turning point; AI exhibits a significant U-shaped spatial effect on Lae; an exogenous shock test using the Big Data Pilot Zone policy further confirms the robustness of the conclusions; human capital and technological innovation channels exhibit weaker or even negative effects due to short‑term resource misallocation and skill mismatches; AI is the most important predictive factor for Lae.</p>

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A study of the impact of artificial intelligence on the low-altitude economy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月9日

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  • Jianhui Yin,
  • Wei Chen,
  • Feiyan Wang

摘要

In the context of a new round of technological revolution intersecting with transformations in the airspace economy, how Artificial Intelligence (AI) empowers the development of the Low-altitude economy (Lae) has become a forefront issue in theoretical research and policy practice. Using panel data from 2012–2022 for 30 Chinese provincial regions, we construct composite indices for AI and Lae and employ the entropy method, kernel density estimation, a spatial Durbin model, spatial mediation analysis and artificial neural networks to comprehensively evaluate AI’s influence on low‑altitude economic growth. The results show that: AI has a significant inverted U-shaped impact on Lae, with diminishing marginal returns after a certain turning point; AI exhibits a significant U-shaped spatial effect on Lae; an exogenous shock test using the Big Data Pilot Zone policy further confirms the robustness of the conclusions; human capital and technological innovation channels exhibit weaker or even negative effects due to short‑term resource misallocation and skill mismatches; AI is the most important predictive factor for Lae.