• Identifying where AI is creating measurable impact across healthcare, diagnostics, operations, and patient engagement
• Addressing barriers to AI adoption, including data silos, integration complexity, regulatory uncertainty, and trust
• Aligning expectations across manufacturers, providers, regulators, clinicians, and patients for responsible AI adoption
• Embedding governance, cybersecurity, and compliance into AI development to support scalable innovation
• Exploring the future of AI-driven healthcare through generative AI, predictive analytics, and autonomous workflows