What if we could identify risk among service members and veterans much earlier—using the power of artificial intelligence and data analytics? With technology advancing rapidly, it’s now possible to move beyond traditional methods and bring together many kinds of information and mixed methods approaches, from health records to administrative, social and economic data, to identify those at risk who need help sooner.But, turning this promise into reality isn’t simple. While research supports an “augmented” approach of data with clinical judgment for the use of AI in suicide prevention, effectively navigating the integration of AI for suicide prevention means more than adopting new tools. It requires careful planning, understanding the limitations This session will discuss the benefits of being prepared and poised to leverage technology, combined with real-world lessons that may support the advancement of suicide prevention efforts for service members and veterans. We will discuss the implications for integration of AI and machine learning in clinical and research settings and the current opportunities for integrating AI into mental health programs; in addition, we will explore the importance of combining disparate information and data, including but not limited to clinical and administrative—such as health history, social and economic information, lived experience, and life events—to gain a more complete understanding of suicide risk to help guide earlier interventions. Panelists will share examples and challenges from early uses of AI in suicide prevention, including both the current opportunities and barriers/challenges causing limitation including but not limited to access to systems, IRB reviews, and HIPAA compliance. We will also look closely at how organizations can build trust, protect privacy, and make ethical decisions when using sensitive data and advanced technology to support mental health. Finally, the session will provide actionable, concrete steps organizations can take to safely implement technology and analytics — modernizing suicide prevention while prioritizing the unique needs service members and veterans.