Governing AI in Organizational Innovation: Leadership, Trust, and Regulation in Practice

As artificial intelligence moves rapidly from experimentation to implementation in healthcare, organizations face a growing challenge: how to innovate responsibly while navigating an evolving regulatory landscape. This session offers a practical, “on the ground” perspective drawn from major European health data and public–private partnership initiatives. Based on current work led by the European Institute for Innovation through Health Data (i~HD), the presentation explores how AI-enabled health innovations are being assessed during a period of significant regulatory change, including implementation of the EU AI Act and its interaction with the Medical Device and In Vitro Diagnostic Regulations.

Rather than focusing solely on compliance, the talk examines broader leadership questions that emerge when AI enters health innovation environments: How should organizations evaluate trustworthiness? How can early-stage innovators assess quality, utility, and risk? What governance capabilities are needed to manage AI systems over time, rather than only at launch?

The session will also address practical approaches for reviewing AI components, evaluating maintenance needs, and balancing innovation speed with accountability, transparency, and patient trust. Although grounded in healthcare, the lessons extend far beyond the sector. Many research-intensive organizations now face similar tensions between technological opportunity, regulatory uncertainty, and responsible deployment.

For leaders, the challenge is no longer whether AI will be adopted, but how to govern it in ways that preserve trust, quality, and human responsibility. This session will be particularly relevant for executives, researchers, regulators, innovators, and others working with AI implementation in high-stakes environments.