Volume-1 ,Issue 3, October-2025

Artificial intelligence (AI) is being used by the pharmaceutical sector more and more to improve quality assurance (QA) and control (QC) in response to the rising complexity of manufacturing processes and regulatory requirements. Real-time monitoring, predictive analytics, automated defect detection, and intelligent quality management are made possible by AI technologies, such as machine learning, deep learning, computer vision, and natural language processing. This improves product consistency, lowers batch failures, and maximizes operational efficiency. AI integration has advantages, but it also has drawbacks in terms of data quality, model explainability, ethical application, validation, and regulatory approval. This review highlights AI's potential to create more effective, predictive, and resilient quality systems that guarantee patient safety and compliance. It also covers industrial implementations, benefits, challenges, regulatory and ethical considerations, and emerging trends like autonomous quality systems, digital twins, and blockchain integration.

Keyword: Artificial Intelligence, Pharmaceutical Quality Control, Quality Assurance, Process Analytical Technology, Predictive Analytics