Artificial Intelligence, Demand Switching and Sectoral Wage Gap

Artificial intelligence (AI) induced services are a reality in India and other developing countries. It is an opportune time to assess the impact of such technologies on wage inequality. While doing so, we must distinguish labourers who are complementary to AI and from those who are substitutes. In this paper, we develop a demand-switching model which brings in an additional factor. Proportion of consumers, who easily adapt AI-induced services, will influence the pricing of such services. This would further impact the wages across traditional and non-traditional services. The primary aim of this research is to examine how demand switch towards AI-enabled goods and services influence wage differentials among homogeneous workers in the non-traded sector of an open economy. Especially we discuss the case of the transportation sector. Employing a Finite Change General Equilibrium model, we introduce AI as a technological shock in the non-traded sector. Modelling its effects through price adjustments. Our findings suggest that a shift in preference towards non-traded AI services exacerbates income inequality among previously homogeneous workers. Furthermore, empirical validation of our theoretical framework employs an endogenous structural break analysis, identifying 2007 as the break year for AI introduction in India, coinciding with the emergence of AI-powered services such as Windows Live and AI ride-hailing apps like Ola and Uber. Our investigation into wage disparities within the transportation sector, measured by the Gini coefficient, shows that despite AI’s introduction, inequality has not significantly worsened. This can be attributed to sluggish demand switching from non-AI to AI-based services in India. Data reveals that less than 0.7% of the Indian population uses AI-induced ride services, underscoring the gradual nature of AI’s societal integration and subsequent impact on economic variables

Economic inequality · Goods and services · Homogeneous · Inequality · Shock (circulatory · Technological change · Wage · Wage Inequality · Cyberloafing and Workplace Behavior · Digital Economy and Work Transformation · Labor market dynamics and wage inequality