AI Driven Productivity surge: Transforming the Indian service sector workforce, Journal of Indian School of Political Economy, ISSN: 0971-0396, Volume: 36, NO: 02, January-June:2024.
Description
This paper primarily analyses the relationship between labor productivity and Artificial intelligence in Indian service sector. For this purpose, variable such as the value added, amount of capital stock and expenditure on research and development chosen. The value added is treated as a dependent variable, on the contrary other variables are treated as explanatory variables. Here the expenditure on R&D is considered as a proxy for investment in AI. Although AI has been playing major role in output maximization, here the attempt is made to capture AI’s impact on Labor productivity, The data of capital stock and labor productivity were taken from RBI KLEMS data base and the expenditure on research and development taken from: NSTMIS, Department of Science & Technology. The data has been filtered for the research period from 1991 to 2023. The data was transformed into log form for easier statistical interpretation. The measure of central tendency and correlation matrix were executed. For each variable stationary of the data has been worked out using Augmented dickey fuller unit root test. It was observed that there were mixed differences. Hence the ARDL (Autoregressive Distributed log) model was chosen to for accurate model building. The results depicted that Labor productivity and capital stock are correlated around 0.993, that of labour productivity and research & development by 0.996, and whereas capital and research and development 0.992 show that there is a high positive link between labour productivity, capital stock, and research and development. This implies that a rise in one variable tends to boost the others as well. With an R-squared value of 0.7457, the regression model explains a considerable amount of the variance in labour productivity. Specifically, variations in capital stock and research & development account for around 74.57% of the variability in Labor Productivity. Key Words: Artificial Intelligence, Labor Productivity, Research and Development, ARDL model. JEL: C30, C32, C67