Artificial Intelligence

The Fourth Industrial Revolution(4IR) is reconfiguring labor markets through artificial intelligence (AI). This study examines the effect of AI investment on skilled employment in Kenya in both short- and long-run dynamics and the role of structural breaks. Quarterly data from 2012Q1 to 2024Q4 were analyzed using the Autoregressive Distributed Lag (ARDL) model, incorporating Chow breakpoint tests, structural dummy variables, and Granger causality. Baseline estimates show AI investment significantly raises skilled employment in the short run (8.83%) and long run (4.81%). With structural breaks included, the short-run effect turns negative coefficient (β =–14.21), while the long-run effect remains positive (β =8.13). The error correction term (–0.65) indicates rapid adjustment to equilibrium. Wages positively affect skilled employment in both horizons (β=0.59; β=6.09) which will call for competitive compensation. Inflation has a strong persistent negative short-run effect (β =–51,250.92) and long-run effect (β =-27,852.28). GDP per capita exerts persistent negative effect (β =–0.47; β =–1.46) attributed to capital-intensive growth that limits labor absorption. The results show AI adoption initially displaces skilled labor but later increases demand for advanced skills. Macroeconomic factors amplify these dynamics: wage growth enhances employment, while inflation and GDP growth exert asymmetric effects. Granger causality tests confirm a bidirectional causal relationship between AI and skilled employment. Kenya may provide education and training programs to mitigate transitional unemployment, align training with AI-intensive sectors, expand broadband in underserved counties, integrate AI curricula in TVETs, and sustain competitive wage structures. Regulatory safeguards and social protection are essential to ensure inclusive AI-driven labor market transformation.