Artificial intelligence (AI) constitutes a transformative and disruptive discipline within computer science, with profound implications for the evolution of medical practice and the delivery of healthcare services. Recent advancements in the application of AI in healthcare have demonstrated its potential to enhance the efficiency, reliability, and security of clinical systems. This review article synthesizes these developments, presents a strategic framework for the design and deployment of effective AI solutions, and outlines prospective directions for the integration of AI in healthcare. Globally, healthcare systems are confronted with complex challenges in achieving the ‘quadruple aim’: improving population health, enhancing patient experience, supporting the well-being of healthcare providers, and reducing the escalating costs of care. These challenges are driven by demographic shifts such as population aging, the rising burden of chronic diseases, and increasing healthcare expenditures. The COVID-19 pandemic has further magnified these pressures by emphasizing the dual necessity for healthcare systems to maintain high-quality, effective service delivery while simultaneously transforming through the integration of data-driven, real-world insights into clinical practice. In addition, the pandemic has illuminated critical systemic issues, including shortages in the healthcare workforce and persistent disparities in access to care, as documented by institutions such as The King’s Fund and the World Health Organization.