AI continues to make inroads into the healthcare sector, as public and private-sector actors grapple with challenges that are inhibiting wide preadoption of this disruptive technology, which stands poised to level up patient outcomes, boost care quality and shrink health service delivery costs. It has a huge potential to change the dynamics of how patients get treated, diagnosed and hospital operation in healthcare sector by making them faster accurate and cost-effective. By understanding the barriers and possibilities for AI in healthcare, regulators can support patient health also promoting truly revolutionary changes within an industry. One noticeable problem with using AI is that it requires a high-quality and widely varied dataset to train from. For patient data to be able to move safely and ethically, it will need robust frameworks for managing the different lines of accountability (data governance), agreements about how data should or can be shared between institutions (data-sharing agreements) and sets of standards that describe what is meant by a “record” when medical records are transferred as one unit across any arbitrary pair of systems in semantic interoperability. The other major issue is the public’s distrust of AI algorithms. Accountability, interpretability and bias in the AI algorithms driving decision-making have also been raised by patients and healthcare professionals. In this chapter, we investigate different downsides in integrating AI into the medical domain generalizing their possible usage and issues while covering fundamental success factors for deploying it. It includes successful integration case studies, and a forward-looking conversation on the future of AI along with its challenges. An outcome may be fullest realization of AI technologies will also address disparities related to AI in healthcare, preparing for a future where all people have access to equitable and patient-centered care involving these tools. The chapter concludes with recommendations for ongoing research in AI integration, highlighting the significance of responsible advancement and the use of AI for the benefit of the society.