This paper presents a narrative review of Artificial Intelligence (AI) in healthcare, examining its technological evolution, clinical applications, and associated ethical and regulatory challenges. While AI demonstrates significant potential in improving diagnostic accuracy, operational efficiency, and personalized care, its adoption remains constrained by issues such as data fragmentation, algorithmic bias, lack of transparency, and regulatory inconsistencies. The study identifies a critical gap in integrating technological advancement with ethical governance and policy frameworks. To address this, the paper proposes a conceptual framework for responsible AI implementation in healthcare, supported by interdisciplinary collaboration and policy alignment. A structured methodology involving systematic literature selection, thematic analysis, and critical synthesis is employed. The findings highlight contradictions in current literature, particularly between innovation and ethical accountability. The paper contributes by offering actionable recommendations, including a healthcare AI implementation roadmap and policy guidelines adaptable across diverse economic settings. This study is a narrative review with analytical synthesis, focusing on critically examining existing literature on AI in healthcare while proposing a conceptual implementation framework.