Impact of Artificial Intelligence on Healthcare: A Review of Current Applications and Future Possibilities

Artificial intelligence (AI) is rapidly transforming healthcare across diagnosis, treatment planning, patient monitoring, drug discovery, administration, and public health. This review synthesizes recent literature on AI applications in healthcare, highlights concrete examples where AI has influenced clinical practice (medical imaging, diabetic retinopathy screening, protein-structure prediction for drug discovery), examines benefits (accuracy, efficiency, scalability), and details persistent challenges (data bias, interpretability, regulatory and ethical concerns). We also survey regulatory progress and guidance, and outline likely near-term and long-term future possibilities, including personalized medicine driven by multi-modal models, AI-assisted clinical trials, and integration of large language models (LLMs) into clinical workflows. Finally, we propose priorities for research, governance, and safe deployment to maximize benefit while minimizing harms. Key policy and scientific developments indicate AI’s promise but underline the need for robust regulation, transparency, and emphasis on equity.