QUANTIFYING THE ECONOMIC IMPACT OF AI ON SDG 7 ACHIEVEMENT: A COMPREHENSIVE SECONDARY DATA ANALYSIS OF INDIA'S ENERGY TRANSITION

Despite growing policy interest in Artificial Intelligence (AI), comprehensive economic evaluations using systematically consolidated secondary data remain scarce in the Indian energy context. This study addresses this gap by providing a methodological contribution through exclusive secondary data analysis of AI applications in advancing India's progress toward Sustainable Development Goal 7 (SDG 7). Through systematic analysis of 32 government reports, 15 pilot project evaluations, and national energy datasets (2018-2024), we conduct a comprehensive cost-benefit analysis of AI implementations across renewable energy forecasting, smart grid management, and predictive maintenance. Analysis of Central Electricity Authority data reveals AI-driven renewable forecasting reduces grid integration costs by 18-25%, while National Smart Grid Mission data demonstrates smart grid technologies enable utilities to reduce aggregate technical and commercial losses from 21.5% to 16.2%. The analysis reveals a positive net present value of ₹1,45,000 crore (~USD 17.4 billion) for national AI implementation, with an aggregate benefit-cost ratio of 2.8:1. The study recommends integrated policy interventions focusing on public-private partnerships and standardized data governance frameworks to accelerate economically efficient AI adoption, thus informing evidence-based energy governance and positioning India to achieve its National Electricity Plan 2024 targets. Keywords: Artificial Intelligence, SDG 7, Economic Evaluation, Clean Energy, Smart Grid, India, Cost-Benefit Analysis, Secondary Data Analysis, Renewable Integration, Energy Economics, Sustainable Development