Artificial intelligence is opening new possibilities in MedTech, from streamlining regulatory work to improving access to information and supporting more efficient operations. But discussions at the Veeva MedTech Summit in Amsterdam focused less on the speed of adoption than on whether companies have the foundations to use AI effectively.
A consistent theme across presentations, panels and interviews was that digital transformation depends first on reliable data, consistent processes, appropriate governance and the people responsible for overseeing them. Without those elements, introducing AI into fragmented or inconsistent environments can create more problems than it solves.
Medtronic's four-year groundwork
Becki Brasher of Medtronic described a four-year effort to prepare the company for AI. The work began not with the technology but with organisational foundations: harmonising processes, improving data consistency, consolidating systems and establishing governance structures. Brasher said the company did not start with AI; it had to earn the right to use it.
Her account illustrates why reliable information and standardised processes matter. In their absence, organisations risk producing outputs that are difficult to trust, validate or scale. Preparing employees is also essential, because technology alone cannot deliver transformation; staff need knowledge, confidence and appropriate oversight to incorporate new tools into daily work.
Governance from the outset
The balance between innovation and regulatory compliance was a major theme in the closing keynote by Erik Orzechowski and Benjamin Rochette. As AI adoption accelerates, MedTech organisations must move quickly without compromising the quality, safety and regulatory standards expected of the industry. Orzechowski and Rochette argued that governance should be embedded in technology development from the beginning rather than treated as a final compliance exercise.
That requires closer collaboration between IT, Quality and Regulatory teams. IT teams understand the technology and its implementation, while Quality and Regulatory professionals assess risks and determine the evidence needed to demonstrate compliance. The speakers also called for proportionate governance: an AI application supporting low-risk administrative activities does not necessarily need the same controls as one influencing patient safety or regulatory decisions. Clear responsibilities, early risk assessments and appropriate controls can create a more flexible approach that supports innovation without ignoring obligations.
Human judgement remains central
Despite AI's growing capabilities, speakers stressed the continued importance of human judgement and professional expertise. Brasher said AI should assist human reviewers rather than replace them. In her view, human judgement will remain in place until organisations build trust that what agents deliver is accurate.
AI can analyse large volumes of information, generate documentation and provide recommendations, but its outputs still require scrutiny. A convincing answer is not necessarily a correct one, particularly in a highly regulated environment. The closing keynote compared relying on AI without understanding its underlying subject matter to using a calculator without knowing the mathematics behind it. A related concern is the next generation of regulatory and quality professionals: if employees rely on AI before developing the necessary knowledge, organisations could have fewer people able to challenge inaccurate or inappropriate recommendations.
Pilots and value measures
Another consideration is whether AI investments deliver genuine business value. With many potential applications available, organisations need to resist pursuing every opportunity at once. Instead, they should identify areas where technology can address existing operational challenges and set clear measures of success. The closing keynote highlighted time savings, reduced process cycle times, less rework, improved quality and employee adoption as ways to assess value. Controlled pilot projects can help organisations understand where AI is most effective, retain human oversight and build confidence before expanding successful applications.
The summit's broader message was that digital transformation is a collective challenge. Technology, regulatory compliance, data management and organisational culture cannot be addressed independently. Progress will require closer collaboration within companies and continued engagement among manufacturers, technology providers, regulators and other stakeholders. AI offers significant opportunities for medical technology, but realising them will require patience, preparation and a clear understanding of where human expertise remains indispensable. Orzechowski described the approach as slowing down in order to speed up.