This paper examines and emphasizes on how Indian industries have progressively adopted Enterprise Resource Planning (ERP) systems along with automation and machine learning (ML) between the year two thousand fifteen and the year two thousand twenty-four. Adoption of the ERP with Automation and Machine Learning are slow and steady during this period, rather than explosive. In the year two thousand fifteen, roughly six thousand organizations used ERP systems with meaningful automation or AI capabilities; at the same time by year two thousand twenty-four that number is estimated to be close to twenty-seven thousand. Several factors drove this change: cloud ERP lowered entry costs for smaller firms, more SMEs became digitally comfortable, and national initiatives such as Digital India and Make in India encouraged modernization and digitalization. Early uses of ML and automation were often limited to pilots, testing based on isolated experiments — forecasting tests, narrow workflow automations — but after the year two thousand seventeen adoption accelerated. Manufacturing automated routine inspections and process optimization, BFSI leaned on ML for fraud detection and risk analytics, IT services embedded intelligent capabilities into operations, and sectors like healthcare and agriculture found practical uses for scheduling and crop analytics. Where organizations adopted these tools, they typically saw smoother data flows, faster decision making, and help in reducing the manual steps. Progress, however, is uneven: many firms face upfront cost and integration challenges; skilled analytics and AI professionals remain scarce, pushing firms to outsource; organizational resistance to change persists; and uneven digital infrastructure — especially outside major cities — keeps many micro and rural enterprises from reaping the benefits. This study synthesizes secondary data and recent academic and industry reports and concludes with recommendations for policymakers, technology providers, and organizations seeking substantive ERP–AI integration rather than surface-level adoption.