The qualification of the medical device, which so far has been regulated by standard practices such as Installation Qualification (IQ), Operational Qualification (OQ), and Performance Qualification (PQ), is now experiencing a revolution of such magnitude because of adopting machine learning (ML) and artificial intelligence (AI). While conventional methods have ensured conformity to regulation according to guidelines like FDA regulation and ISO 13485, they are more likely to be infested with inefficiency, cost, and vulnerability to human error—issues which are now no longer affordable in Industry 4.0. This article discusses the transition towards AI/ML-based automation in the production of medical devices based on a synthesis of knowledge from Scopus-indexed, IEEE, and Elsevier journals during 2020-2025. Enabling technologies like Big Data analytics, cloud computing, and the Internet of Things (IoT) are driving sophisticated applications such as predictive maintenance, real-time process optimization, and smart anomaly detection. Hybrid validation approaches integrating traditional techniques with AI-based solutions are gaining popularity for GxP compliance in sophisticated manufacturing environments. Successful use cases among leading medical device manufacturers demonstrate quantifiable benefits such as higher precision, effective use of resources, and higher traceability, along with factoring in challenges such as transparency in algorithms, ethical regulation of AI, and data integrity. The article also assesses emerging regulatory views, such as the FDA's AI/ML Action Plan and the Medical Device Regulation of the European Union (EU MDR), and suggests pragmatic recommendations for regulators and manufacturers, such as the creation of robust data infrastructures and interdisciplinary teams. Ultimately, it outlines areas of research gap in model validation, cybersecurity, and long-term performance testing, concluding that AI has transformative potential in building a robust, intelligent, and future-proofs validation ecosystem

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Please cite this article in press as Jahnavi Vellanki et al. Discuss the transition from traditional validation methods to AI and ML-driven automation in medical device manufacturing. Indo American Journal of Pharmaceutical Research.2025:15(06).