Artificial Intelligence (AI) is rapidly transforming supply chain systems in developing economies, particularly in India, where high logistics costs and structural inefficiencies have historically constrained economic growth. This study examines the impact of AI-driven technologies on logistics efficiency and Micro, Small and Medium Enterprises (MSME) performance using a descriptive and analytical approach based on data from government and industry sources. The findings indicate that AI adoption has significantly enhanced supply chain performance, with forecasting accuracy increasing from 55–65% to 80–90%, and average delivery time reducing from 5–7 days to 2–3 days, reflecting nearly a 30–40% improvement. Logistics costs have declined from 13–14% of GDP to around 8%, while warehouse efficiency has improved by 25–30% and fuel consumption has decreased by 10–15%. In the MSME sector, AI integration has resulted in a 20–25% reduction in inventory costs and a 10–15% decline in transportation costs, while order fulfilment rates have improved from 70–75% to 90–95% and sales growth has increased from 8–10% to 15–20%. Despite these benefits, challenges such as inadequate digital infrastructure, high implementation costs, data fragmentation, and skill gaps continue to hinder widespread adoption. Overall, the study highlights that AI-driven supply chain transformation enhances efficiency, reduces costs, and strengthens MSME competitiveness, thereby contributing to sustainable and inclusive economic development, while emphasizing the need for supportive policies, digital infrastructure, and skill development initiatives.