This study examined the complex regulatory landscape governing the adoption of artificial intelligence (AI) in medical imaging, focusing on a comparative analysis of the European Union’s Medical Device Regulation (EU MDR) and India’s Central Drugs Standard Control Organization (CDSCO). The motivation behind this research stemmed from the growing integration of AI technologies in diagnostics, juxtaposed with the lack of standardized global frameworks to support their safe and effective deployment. Despite AI’s potential to enhance diagnostic accuracy and efficiency, inconsistencies in regulation, clinician trust, and ethical oversight continue to act as significant barriers to clinical implementation. A mixed-methods design was adopted to provide a comprehensive evaluation of these issues. Quantitative data were collected through structured surveys and analyzed using Chi-square tests and Exploratory Factor Analysis (EFA) to uncover latent variables influencing AI adoption. Qualitative insights from open-ended survey responses were analyzed thematically to contextualize the statistical findings. The findings demonstrated that significant regulatory disparities between the EU and India affect the pace and confidence with which AI technologies are adopted in clinical settings. It was shown that clinician trust, industry readiness, and ethical considerations are strongly influenced by regulatory clarity and post-market surveillance structures. EFA revealed four key latent factors impacting AI adoption: regulatory confidence, clinician trust, industry compliance, and ethical/data security concerns. Chi-square tests further confirmed that these factors are significantly associated with participants’ roles and geographical regions, highlighting regional variability in perceptions of AI readiness and policy effectiveness. This research concludes that while both regions recognize the transformative potential of AI in diagnostics, fragmented regulatory pathways and ambiguous approval mechanisms hinder global implementation. The study recommends developing regionspecific guidance aligned with international best practices to improve interoperability, regulatory transparency, and clinical trust. By identifying actionable gaps and proposing informed regulatory strategies, this dissertation contributes to ongoing efforts aimed at ensuring the safe, ethical, and efficient deployment of AI in medical imaging. The findings provide valuable evidence for policymakers, regulatory authorities, and medical technology developers seeking to streamline approval processes while safeguarding patient outcomes.