AI is transforming healthcare, tackling tropical diseases, and advancing cancer care. In tropical regions, machine learning models like neural networks improve diagnostics by spotting patterns in clinical data, enabling early treatment in areas with limited resources. Yet, challenges like biased datasets and regional disparities limit its reach. In cancer care, AI enhances precision medicine by predicting drug responses and personalizing treatments. Deep learning automates imaging and streamlines diagnostics, while in immunotherapy, it tailors treatment plans based on patient responses, improving outcomes and efficiency. Despite its promise, AI adoption faces hurdles, including ethical concerns, data privacy issues, and unequal access. Collaboration among healthcare providers, tech experts, and policymakers is key to overcoming these barriers. By addressing these challenges, AI can reshape medical care, particularly in underserved areas and complex conditions, fostering a more equitable and effective healthcare system.