The Dual Impact of Artificial Intelligence on Banking Industry Employment: A Literature Review

Abstract

The widespread adoption of artificial intelligence has brought contradictory changes to banking labour markets, triggering extensive academic discussions over worker behaviour, job displacement and market equilibrium. This review sorts out mainstream literature built upon Reinforcement Sensitivity Theory, technological unemployment theory and General Equilibrium Theory, summarising existing arguments about employees’ polarised responses to AI, two channels of labour substitution, and wage polarisation across financial sectors. Current literature relies heavily on industrial reports and public bank data to describe surface-level employment shifts, yet obvious research gaps remain. Most studies ignore grassroots employee subjective surveys, lack targeted discussion on low-skill worker reskilling mechanisms, and seldom integrate psychological heterogeneity into macro labour equilibrium models. Few works differentiate temporary employment shocks from lasting structural labour adjustments brought by AI transformation. This paper clarifies insufficient research areas in the current field and puts forward clear directions for follow-up academic exploration, providing a reference for subsequent theoretical and practical research on AI and banking employment.