Year: 2024
Type: article
Study design: Observational Study
Abstract: The city of Bangalore is often considered the Silicon Valley of India, standing on an excellent global pedestal regarding technological innovation and economic dynamism.Fast growth in this city over the years has wrought a substantive influx of migrants from all regions of the country, seeking an improved prospect of gainful employment and standards of living.The increasing application of AI across various sectors in Bangalore shows that it plays an important role in productivity gains and economic development.Nevertheless, this migrant population, being an integral part of the manpower in the city, does not benefit equally from these emerging AI tools.This paper tries to investigate exactly how AI tools are impacting the productivity and economic outcomes of migrant workers in Bangalore.The study, based on demographic analysis and empirical data from a stratified random sample of 100 respondents, examines the adoption patterns, perceived benefits, and challenges associated with AI among migrants.Key findings included some of the major uses of ChatGPT, Replika, and Grammarly to improve task management and efficiency for better job performance across industries.While AI holds promise, migrant workers' limitations are quite significant, to name a few: digital literacy gaps and fears of job displacement, which greatly impede their full integration into and benefits from AI technologies.The study underlines the need for targeted intervention and a policy framework that could focus on enhancement in AI literacy, access to training, and awareness of ethical issues with regard to inclusive growth.By addressing these concerns and using AI positively, policymakers, businesses, and educational institutions can equip migrant workers with new opportunities in Bangalore toward sustainable economic growth and a more equitable digital economy.
Author: Kaashvi Nigam
Language: English
Topic: Migration and Labor Dynamics
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4411970354