Artificial Intelligence (AI) promises to transform healthcare delivery worldwide, improving diagnostics, access, and system efficiency. Yet biased datasets, exclusionary design choices, and uneven deployment risk reinforcing inequities and disproportionately harming already marginalised communities, including the elderly, persons with disabilities, and rural populations. This interdisciplinary panel will explore inclusive AI strategies, such as participatory design, representative data practices, and context-sensitive governance frameworks, to ensure that AI systems in healthcare are designed, developed, and deployed in ways that mitigate unintended harm. The focus is on building equitable digital health ecosystems that proactively address structural disparities rather than amplify them.