Artificial intelligence (AI) technologies have the potential to improve healthcare and public health. Although there has been success in AI for research uses, little progress has been made in implementing health-related AI technologies in health systems. Responsible AI for health systems requires engagement and co-design with health system partners, policymakers, and the community. Deploying responsible AI requires engaging stakeholders, particularly those affected by the technology. This commentary presents the importance of participatory approaches for responsible AI implementation. In this commentary, we discuss the planned use of participatory approaches to responsibly deploying validated machine learning models, with a specific case example of diabetes prediction models that can address the challenge of preventing and managing diabetes in a health system.. The participatory methods engage policy-, provider-, and community-level actors to deploy and implement the AI diabetes tools, inform how AI is implemented in health settings, and overcome common deployment barriers. The future of AI in health settings rests on fine-tuning these practices to enable trust, acceptability, and oversight of these technologies to be deeply established in health systems.