The rapid evolution of Artificial Intelligence (AI) has initiated a paradigm shift in healthcare, transforming traditional models of diagnosis, treatment, and patient management. AI-driven innovations such as deep learning, natural language processing, and predictive analytics are redefining medical decision-making by enabling faster, more accurate, and data-informed outcomes. This study aims to explore the transformative potential of AI in healthcare by examining its key opportunities, existing barriers, and broader societal implications. The research adopts a mixed-method analytical approach, integrating insights from empirical studies, real-world applications, and case-based evaluations to assess both the technological and ethical dimensions of AI adoption. Findings indicate that AI has significantly enhanced early disease detection, personalized care delivery, and healthcare resource optimization. However, challenges related to data privacy, algorithmic bias, and infrastructural disparities continue to hinder large-scale integration. The paper concludes that the responsible deployment of AI, supported by robust regulatory frameworks and transparent governance, can revolutionize global healthcare systems. Future research should focus on developing explainable and ethically aligned AI models to ensure equitable access and trust across diverse healthcare ecosystems.

Keywords: Artificial Intelligence, Healthcare Transformation, Predictive Analytics, Medical Ethics, Digital Health Systems, Algorithmic Transparency, Societal Impact