Artificial Intelligence (AI) is reshaping work, production, and innovation across regions, yet the uneven distribution of AI literacy ‒ a key capability for meaningful participation in AI-mediated labour markets and regional economies ‒ remains poorly understood. This paper provides new comparative evidence on AI literacy across more than 30 EU and neighbouring countries, drawing on novel data from the EU-TRAILS project with detailed regional identifiers that enable analysis at both the NUTS1 and NUTS2 levels. The study examines how individual characteristics such as gender, age, education, and income interact with regional economic structures and labour market contexts to generate substantial spatial disparities in AI readiness, both between and within countries. The findings reveal pronounced regional inequalities, suggesting that AI-driven work transformation may reinforce existing spatial divides unless supported by place-based skills, innovation, and governance strategies. By conceptualising AI literacy as a regionally embedded capability shaped by local labour markets and institutional environments, the paper contributes to debates on inclusive digital transformation, AI governance, and regional development, and offers policy-relevant insights for designing territorially sensitive approaches to AI adoption.

JEL codes: J24; O33; R11; R58.