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In this video, I walk through a small utility I built to explore AI exposure in the Indian job market. Demo link: https://iid.localm.dev/ai-exposure/ The idea was inspired by the U.S. job market visualizer shared by people like Andrej Karpathy, but this version uses Indian market data instead. I combine public data from government sources with additional private analysis where possible to estimate which sectors, job groups, and states may be more exposed to AI and automation. Chapters: 00:00 Project Origins: Adapting Karpathy’s Map for India 01:30 Methodology: MOSPI Data & The Single Axis Rubric 03:25 High-Risk Industries: Finance, Professional Services & AI Co-pilots 07:41 Economic Impact: The Threat to India’s Taxpayer Base 09:45 Geographic Risk: Why Haryana, Gujarat & Urban Pockets are Exposed Some of the key takeaways: Agriculture and construction appear relatively less exposed Information and communication, finance, professional services, real estate, and clerical roles appear much more exposed Urban pockets may face stronger AI impact than state-level averages suggest States with strong manufacturing, instrumentation, and automobile ecosystems may also see significant disruption through robotics and AI This is still an exploratory project, but it shows how AI-assisted programming, data engineering, and visualization can be used together to study labor market change in India. Data sources include public government datasets, especially from the Ministry of Statistics and Programme Implementation. If you find this useful, share your thoughts in the comments and follow for future updates. I plan to expand this analysis with more data and possibly compare other countries as well. #AI #India #Automation #LaborMarket #DataVisualization #ArtificialIntelligence