Explaining Divergent Artificial Intelligence Readiness in South Asia: A Comparative Study of India and Bangladesh
TL;DR
The study proposes that institutional capacity, policy coherence, technological ecosystems and human capital development are emerging as the key enablers of India’s edge early policy implementation, strong public-private partnerships and a strong and established innovation ecosystem.
Abstract
Despite a shared colonial past, geographic proximity, and similar form of democratic government, Bangladesh has consistently scored lower than India in the Government AI Readiness Index (GARI). This research attempts to answer why structurally similar countries differ in their readiness for AI. This study combines Most Similar Systems Design with qualitative policy analysis to help identify the roots of this gap at the level of indicators as defined in the GARI 2025 pillars. Bangladesh significantly lags behind India in terms of computing power, data quality, maturity of AI industry, and safety and security. The study incorporates the historical institutionalism, the state capacity model, the innovation systems theory and proposes that the differences can be attributed to institutional capacity, policy coherence, technological ecosystems and human capital development. These are emerging as the key enablers of India’s edge early policy implementation, strong public-private partnerships and a strong and established innovation ecosystem. The study recommends Bangladesh to emphasize on strategic coordination, human capital investment and governance reform. This study has been conducted within a framework of causal theory, comparison of India and Bangladesh, and adds to the existing literature on AI governance in the Global South.