Anar Azizov

Type of the article: Research Article

Whether national artificial intelligence (AI) ecosystem development shapes tourism’s contribution to GDP is an open empirical question, particularly given the multidimensional nature of modern AI ecosystems and the heterogeneous reliance of countries on tourism. This study identifies which dimensions of national AI ecosystem development drive within-country changes in tourism’s direct GDP share, using panel data from 33 countries over 2017–2023. Fixed-effects estimation with clustered standard errors is applied to both the composite Stanford HAI AI Vibrancy Score and its seven constituent pillars, complemented by lagged, dynamic, and interaction specifications. The aggregate AI Vibrancy Score shows no significant within-country effect on tourism’s GDP share after controlling for macroeconomic factors (β = 0.061, p = 0.622), indicating that overall AI vibrancy alone does not measurably move tourism’s economic contribution. The pillar decomposition reveals, however, that this null result masks two significant positive drivers of tourism’s GDP share – AI-related R&D (β = 1.811, p = 0.005) and Policy and Governance (β = 0.353, p = 0.037) – both robust to alternative standard errors and two-way fixed effects. The Talent pillar exerts a significant positive effect on tourism’s GDP share with a one-year lag (β = 0.183, p = 0.025), indicating that the human-capital channel requires time to materialize. The COVID-19 pandemic reduced tourism’s GDP share by approximately 37% (β = –0.455, p < 0.001), and AI development did not moderate this decline. The findings imply that targeted AI policies – particularly in R&D and governance – can strengthen tourism’s economic contribution, while aggregate AI metrics obscure heterogeneous pillar-level effects.