The purpose of this paper is to analyse the development of MRI systems with AI concepts within the overall context of healthcare systems in India. By employing secondary data collection complemented with the primary data collected through a structured survey conducted among a sample of radiologists, technicians, and healthcare administrators in India, the study investigates the effects of AI on diagnostic accuracy, authorized work, and productivity in MRI diagnostics. In contrast to the prior global studies, this paper explores the key issues in India such as infrastructure gaps, workforce repletion, and regulations and policies. It is evident from the study that the implementation of AI can improve diagnostic competencies and also minimize procedure time in MRI, which is in sync with the trends across the world. Early stage anomaly: The respondents also indicated that the early stage anomaly was detected in time and the amount of work done by the radiologists was reduced. Thus, the implementation of AI in India is even more problematic due to a deficiency in the technical basis, AI-oriented staff education, and an underdeveloped structure of legislation for AI in medical imaging. This is due to a lack of clear regulatory directions from Indian regulatory bodies like the “Central Drugs Standard Control Organization (CDSCO)” or the inadequate clarity around data protection under the “Digital Personal Data Protection Act (DPDPA)”. The research indicates that, while the participants did not regard AI as a threat to radiologists jobs, it is viewed as a strong support tool if applied properly. It underlines that there is a strong requirement for India-specific AI regulation policies for AI solutions, proper institutional training programs for employees, and better IOT connections. Specific recommendations are directed to the heads and managers of Indian health care centers, AI developers, and policymakers as to cooperation in the AIincorporated MRI diagnostics being safe, efficient, and suitable for patients needs. It adds contextual understanding to India’s preparedness and issues, which forms the basis for more culturally appropriate advancements and use of AI in health imaging.