MedTech companies are eager to adopt artificial intelligence, but discussions at the Veeva MedTech Summit in Amsterdam focused on a less visible prerequisite: the data, processes, governance and people needed to use the technology reliably. The conference’s presentations, panels and interviews repeatedly returned to the idea that successful digital transformation depends on getting these foundations right first.
Becki Brasher of Medtronic described a four-year effort to prepare the company for AI. Rather than starting with an AI application, Medtronic harmonised processes, improved data consistency, consolidated systems and established governance structures. Brasher’s summary of the approach was direct: “We didn’t start with AI. We had to earn AI.” The example illustrates why introducing AI into fragmented or inconsistent environments can create more problems than it solves. Without reliable information and standardised processes, companies risk producing outputs that are hard to trust, validate or scale.
Preparing employees was part of the same effort. The summit heard that technology alone cannot deliver transformation; staff need the knowledge, confidence and oversight to incorporate new tools into daily work. This point connected to a broader theme at the event: AI adoption is not only a technical programme but an organisational one.
Governance from the outset
In the closing keynote, Erik Orzechowski and Benjamin Rochette argued that MedTech organisations must balance faster AI adoption with the quality, safety and regulatory standards expected in the sector. They said governance should be built into technology development from the start rather than 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.
The speakers also called for proportionate governance. An AI application supporting low-risk administrative work may not need the same controls as one that influences patient safety or regulatory decisions. Clear responsibilities, early risk assessments and appropriate controls can give companies a more flexible approach, allowing innovation without ignoring obligations. In this view, compliance and innovation are not opposing priorities; well-designed governance can help organisations move forward with greater confidence.
Human judgement remains central
Despite AI’s growing capabilities, the summit stressed the continued role of human expertise. Brasher said AI should assist human reviewers rather than replace them. In her view, human judgement will remain necessary until organisations build trust that what agents deliver is accurate. AI can analyse large volumes of information, generate documentation and make recommendations, but its outputs still require scrutiny. A convincing answer is not necessarily a correct one, especially in a highly regulated environment.
Speakers compared relying on AI without understanding its subject matter to using a calculator without knowing the mathematics behind it. The analogy raises a question for employers: how can they bring AI into workflows without weakening the expertise needed to assess its outputs? The concern is particularly relevant for the next generation of regulatory and quality professionals. If employees rely on AI before developing underlying knowledge, organisations could end up with fewer people able to challenge inaccurate or inappropriate recommendations. The consensus was that AI should complement human expertise, not replace it, and that accountable individuals must retain responsibility for important decisions.
Pilots and measurable value
Another message concerned investment discipline. With many possible applications, organisations should not pursue every opportunity at once. Instead, they should target existing operational challenges and define clear measures of success. The closing keynote cited 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 wider deployment.
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 collaboration inside companies and continued engagement among manufacturers, technology providers, regulators and other stakeholders. The mood was described as optimistic but pragmatic: AI offers significant opportunities for medical technology, but realising them requires patience, preparation and a clear view of where human expertise remains indispensable. As Orzechowski put it, organisations sometimes need to “slow down to speed up.”