<p>The rapid development of artificial intelligence (AI) has led to increased concerns about technological substitution and the skills of the future in the labour market. While conventional automation has been commonly associated with substitution in routine tasks and skill-biased technological change, the impact of AI may differ significantly in nature and direction. This paper proposes a meta-analysis of 321 estimates from the empirical evidence on the impact of AI and automation exposure on labour market outcomes. The dataset is constructed from 19 empirical studies examining employment, wage, and skill-related effects across different countries, sectors, and empirical designs. To ensure comparability across heterogeneous regression specifications, all coefficients are transformed into partial correlation coefficients and analysed using a three-level random-effects meta-analytic model. The results indicate that the overall pooled effect of technological exposure on labour market outcomes is small and statistically insignificant. However, substantial heterogeneity exists across studies. While some papers report negative employment effects associated with automation and robot adoption, others document positive outcomes related to productivity gains, wage increases, or skill upgrading. Outcome-specific analyses for employment, wages, and skill demand also show no statistically significant average effects. Moderator analysis further reveals no systematic differences between AI-specific measures and broader automation indicators. Overall, the findings suggest that the labour market effects of artificial intelligence and automation are highly context dependent. Rather than producing a uniform pattern of job displacement or skill-biased technological change, technological adoption appears to generate a set of mechanisms that vary across sectors, occupations, and institutional settings.</p>