Economic Theory and Artificial Intelligence: A Cross-model Perspective on Labour Market Dynamics

Abstract This study examines the relationship between labour market changes and artificial intelligence, utilising Romer’s Endogenous growth theory, Schumpeter’s Creative destruction, Solow’s Growth model and Becker’s Human capital theory as theoretical frameworks. The purpose of this research is to clarify the multifaceted impacts of artificial intelligence on economic growth, workforce adjustment and the emergence of novel employment trends, focusing specifically on job losses and gains, wage inequalities, and changing skill requirements. Using a structured literature review methodology, the economic implications of artificial intelligence in the labour market were systematically analysed and synthesised. The results suggest that although artificial intelligence significantly enhances productivity and innovation, it has a complex effect on the labour market, causing employment gains in technologically sophisticated industries and losses in sectors prone to automation. The study emphasises strategic policy interventions and pedagogical reforms that maximise the economic benefits of AI while minimising its disruptive effects on employment. Proponents of such policies argue that by cultivating a workforce that is resilient and capable of adjusting to changes driven by artificial intelligence, they can effectively mitigate inequality and safeguard economic stability.