Labor shortages, changing trends, and increased customer demands plague the garment sector. However, AI in garment automation and computer vision for quality control provide disruptive solutions. AI-driven automation makes production processes more error-free by reacting to demand and design changes. AI improves operational efficiency by monitoring worker performance and enabling human-machine collaboration. Garment faults are recognized more accurately using Faster R-CNN algorithms and improving quality control. Real-time data analysis and predictive maintenance improve textile industry operations. Although ethical issues like AI deployment, workforce treatment, and environmental effect remain important, the sector can grow sustainably by stressing upskilling and ethics. Test findings show a 90% accuracy in flaw detection within samples at 23–27 cm. This study demonstrates AI’s role in improving efficiency, defect detection, and sustainability in garment manufacturing.