<p>The integration of artificial intelligence (AI) in healthcare, from diagnostics to predictive analytics, offers transformative potential for improving patient outcomes worldwide, including in India. However, most existing studies remain fragmented, focusing either on technical bias mitigation or high-income country regulations, with limited comparative insights for diverse and resource-constrained regions. This paper addresses this gap by examining critical ethical challenges in AI-driven healthcare—specifically algorithmic bias, transparency, accountability, and equity—through a narrative policy review, stakeholder analysis, and four cross-regional case studies (United States, European Union, Kenya, and India). The study identifies how these challenges differentially manifest across contexts and evaluates mitigation strategies including bias audits, explainable AI (XAI), and evolving regulatory frameworks such as the EU AI Act, WHO guidelines, and India’s National Digital Health Blueprint. Uniquely, it synthesizes global and Indian perspectives, applies fairness metrics to real-world case evidence, and proposes an inclusive ethical framework that integrates cultural and regional values into AI governance. Looking ahead, provide actionable recommendations for policymakers, healthcare providers, and developers, while highlighting pathways for future interdisciplinary research on trust, cultural sensitivity, and equitable deployment of AI in healthcare.</p>