About this Meeting
If digital transformation in healthcare were primarily a technology problem, it would already be solved. Instead, health systems remain caught between endless pilots and elusive scale. AI solutions often perform well in controlled environments, yet struggle to deliver sustained impact in real-world settings. The limiting factor is no longer innovation — it is alignment.
Drawing on recent WHO insights and real-world transformation experience, this roundtable reframes the challenge beyond product maturity or partnership mechanics. It focuses on the deeper bottleneck that determines success: coherence across incentives, governance, workflows, leadership models, and trust. As innovation accelerates, healthcare systems — and the organizations that serve them — are being asked to absorb change they were never structurally designed to manage.
Across healthcare and life sciences, misalignment shows up in familiar ways: procurement models that reward customization over fitness for purpose, leadership structures that lag technological ambition, and workforce readiness and accountability addressed too late in the adoption cycle. The result is stalled deployment, eroding trust, and growing frustration among clinicians, solution providers, and investors alike.
This executive-level discussion explores why digital and AI initiatives falter as they move from pilot to system-wide deployment, how misalignment undermines adoption and confidence, and what leaders consistently underestimate when attempting to scale. Participants will examine where public, private, and clinical realities collide — and what it takes to build health systems capable of delivering durable digital transformation.
The session positions alignment as execution architecture, with humans-in-the-loop framed not as an ethical afterthought, but as a strategic requirement for trust, accountability, and resilience in healthcare in 2026 and beyond.
Join us to discuss:
Why do digital and AI initiatives continue to stall at the pilot stage despite strong technical performance and early promise?
Where does misalignment most often emerge — across incentives, governance, workflows, procurement, or workforce readiness — and how does it impede scale?
What execution models enable health systems to embed human oversight, accountability, and trust as core components of scalable AI adoption?
