Artificial intelligence is moving into MedTech regulation, information access and operations, but speakers at the Veeva MedTech Summit in Amsterdam argued that the harder task is preparing the ground beneath it. Across presentations, panels and interviews, the consistent message was that reliable data, consistent processes, appropriate governance and accountable people must come before scaled AI adoption.
Foundations before tools
Becki Brasher of Medtronic described a four-year effort to become ready for AI. The company did not begin with the technology, according to her account. It harmonised processes, improved data consistency, consolidated systems and established governance structures. Brasher said Medtronic had to earn AI rather than start with it. The point was practical: introducing AI into fragmented or inconsistent environments can create more problems than it solves, because outputs become difficult to trust, validate or scale. Medtronic also focused on preparing employees, since tools alone cannot deliver transformation and staff need knowledge, confidence and oversight.
Governance by risk
Governance was a central theme in the closing keynote by Erik Orzechowski and Benjamin Rochette. They said MedTech organisations must move quickly without compromising quality, safety and regulatory standards. Their argument was that governance should be built into technology development from the start, not treated as a final compliance step. That requires closer collaboration between IT, quality and regulatory teams: IT understands implementation, while quality and regulatory professionals assess risks and define the evidence needed to show compliance. They also called for proportionate governance, so a low-risk administrative application does not carry the same controls as an application influencing patient safety or regulatory decisions. Clear responsibilities, early risk assessments and appropriate controls can support innovation without ignoring obligations.
Human review and measurable value
Human judgement remained another boundary. Brasher said AI should assist human reviewers rather than replace them. In her view, human judgement will remain essential until organisations build trust that what agents deliver is accurate. The summit heard that AI can analyse information, generate documentation and make recommendations, but its output still needs scrutiny. A convincing answer is not necessarily a correct one, especially in a highly regulated environment. Orzechowski and Rochette compared relying on AI without understanding the subject matter to using a calculator without knowing the mathematics behind it. The concern is that a new generation of quality and regulatory professionals could lose the expertise needed to challenge inaccurate recommendations. The consensus was that AI should complement human expertise, with accountable individuals retaining responsibility for important decisions.
Speakers also urged companies to tie AI investment to genuine business value. With many possible applications, organisations should not pursue every opportunity at once. They should identify where technology addresses existing operational challenges and set clear measures of success. The closing keynote listed time savings, reduced process cycle times, less rework, improved quality and employee adoption as ways to assess value. Controlled pilot projects can show where AI is most effective, preserve human oversight and build confidence before expansion. Because the AI landscape and regulatory expectations will keep changing, governance structures must adapt. Success will depend less on the number of initiatives launched than on the ability to turn promising applications into reliable, scalable capabilities.
The summit’s broader conclusion was that digital transformation is a collective challenge. Technology, regulatory compliance, data management and organisational culture cannot be addressed in isolation. Progress will require closer collaboration inside companies and continued engagement among manufacturers, technology providers, regulators and other stakeholders. The tone was optimistic but pragmatic: AI offers significant opportunities, yet realising them requires patience, preparation and a clear view of where human expertise remains indispensable. Orzechowski’s advice was to slow down in order to speed up; getting the foundations right now, the summit heard, should leave the industry better placed to take on future technological opportunities.