Federal health agencies are rapidly advancing artificial intelligence (AI) solutions from pilot projects to large-scale deployment, using it to expand their capacity to handle increased workloads with limited resources. This session will examine how AI is aiding the transition from episodic, reactive care to continuous, proactive, and personalized health interventions. Through initiatives such as the Department of Health and Human Services’ (HHS) OneHHS strategy, federal health agencies are incorporating AI into operational, research, and patient-centered tasks. 

Meanwhile, healthcare providers are making significant progress in AI-powered diagnostics, clinical decision support, and risk prediction, integrated into electronic health records (EHRs) and clinical workflows. The growing use of wearable devices, remote monitoring, and data-driven insights for early detection, prevention, and population health management are significantly impacting health outcomes. Panel experts will discuss why interoperable, connected data ecosystems are vital for effective, safe, and clinically relevant AI.

Additionally, health agencies and providers must increasingly safeguard sensitive health data and AI systems amid a shifting cyber threat landscape. Experts will address how to embed privacy, security, transparency, and patient safety into AI design, deployment, and operations. Balancing innovation with responsible AI practices is crucial to maintaining clinician confidence, patient trust, and mission resilience. Attendees will gain insights into practical lessons learned, upcoming opportunities, and priorities for the next phase of federal health AI implementation.

Key Discussion Topics
• How can AI lower administrative tasks, simplify documentation, and assist clinicians without adding more complexity?
• Using AI and digital health tools to expand access to care for rural, underserved, and vulnerable populations.
• Promoting equitable care through telehealth, remote monitoring, and data-driven resource allocation.
• What progress looks like in the AI era: tangible improvements in patient outcomes, clinician performance, operational efficiency, and cost control.
• Aligning AI investments with federal mission priorities, real-time regulatory environments, reimbursement models, and long-term sustainability.