MedTech companies are increasingly using artificial intelligence to streamline regulatory work, improve access to information and support more efficient operations. But discussions at the Veeva MedTech Summit in Amsterdam focused on a prior question: whether organisations have the foundations needed to use the technology effectively.
Across presentations and panel discussions, a consistent theme emerged. Successful digital transformation depends on reliable data, consistent processes, appropriate governance and people able to oversee them. Without those elements, introducing AI into fragmented environments can create more problems than it solves, because outputs become difficult to trust, validate or scale.
Medtronic's preparation
Becki Brasher of Medtronic described the company's four-year journey towards AI readiness. The effort did not begin with AI itself. Medtronic instead concentrated on organisational groundwork: harmonising processes, improving data consistency, consolidating systems and establishing governance structures. Brasher summed up the approach by saying the company had to earn AI rather than start with it.
The company also addressed the human side of adoption. Employees need the knowledge, confidence and oversight arrangements to incorporate new tools into their responsibilities. Technology alone, the summit heard, cannot deliver transformation.
Governance built in from the start
In the closing keynote, Erik Orzechowski and Benjamin Rochette examined how MedTech organisations can adopt AI quickly without compromising quality, safety or regulatory standards. They argued that governance should be built into technology development from the outset rather than treated as a final compliance step.
That requires closer collaboration between IT, Quality and Regulatory teams. IT teams understand the technology and how it is implemented, while Quality and Regulatory professionals assess risks and define the evidence needed to demonstrate compliance. The speakers also called for proportionate governance: an AI application supporting low-risk administrative work may not need the same controls as one influencing patient safety or regulatory decisions.
Clear responsibilities, early risk assessments and appropriate controls can give organisations a more flexible route to innovation while keeping obligations in view. Compliance and innovation, the keynote argued, should not be treated as opposing priorities.
Human judgment and business value
Brasher also emphasised that AI should assist human reviewers rather than replace them. She said human judgment would remain essential until organisations build trust that what AI agents deliver is accurate. AI can analyse large volumes of information, generate documentation and make recommendations, but its outputs still require scrutiny. In a highly regulated field, a convincing answer is not necessarily a correct one.
The closing keynote compared relying on AI without understanding its subject matter to using a calculator without knowing the mathematics behind it. The analogy raised a concern for the next generation of regulatory and quality professionals: if employees rely on AI before developing underlying knowledge, organisations may have fewer people able to challenge inaccurate or inappropriate recommendations. The speakers' conclusion was that AI should complement human expertise, with accountable individuals retaining responsibility for important decisions.
On business value, the summit heard that organisations should resist pursuing every potential application at once. They should identify existing operational challenges, set clear success measures and use controlled pilots to learn where AI is most effective. Measures cited in the closing keynote included time savings, shorter process cycle times, less rework, improved quality and employee adoption. Pilot projects can also preserve human oversight and build confidence before successful applications are scaled.
Because AI capabilities and regulatory expectations will continue to evolve, governance structures must adapt as well. Success will depend less on the number of AI initiatives launched than on the ability to turn promising applications into reliable, scalable business capabilities.
The summit presented digital transformation as a collective challenge. Technology, regulatory compliance, data management and organisational culture cannot be addressed in isolation. Progress will require closer collaboration within companies and continued engagement among manufacturers, technology providers, regulators and other stakeholders. The overall message was optimistic but pragmatic: AI offers significant opportunities, but realising them requires patience, preparation and a clear view of where human expertise remains indispensable. Orzechowski's phrase for the approach was to slow down in order to speed up.