AI is increasingly being adopted across health systems, but evidence on safe and equitable use remains fragmented and not consistently aligned with decision-making needs. Existing frameworks often prioritise model performance over real-world interactions with digital infrastructure and contextual factors. This panel will examine methodological gaps in digital health research and discuss a more holistic agenda for AI integration, governance, effectiveness, and equity, concluding with a set of recommendations.