MedTech companies seeking to adopt artificial intelligence need to address fundamental organisational issues before pursuing ambitious applications, according to discussions at the Veeva MedTech Summit in Amsterdam. Presentations, panels and interviews at the event pointed to reliable data, consistent processes, appropriate governance and clear human accountability as prerequisites for effective use of the technology.
Becki Brasher of Medtronic described a four-year effort to prepare the company for AI. Rather than starting with the technology, Medtronic harmonised processes, improved data consistency, consolidated systems and established governance structures. Brasher said the company did not begin with AI but had to earn the capability. Her account illustrated the risk of introducing AI into fragmented or inconsistent environments, where outputs may be difficult to trust, validate or scale. She also emphasised preparing employees for change, since technology alone cannot deliver transformation and staff need the knowledge, confidence and oversight to use new tools in their work.
Governance and collaboration
In the closing keynote, Erik Orzechowski and Benjamin Rochette addressed the tension between faster AI adoption and the need to maintain quality, safety and regulatory standards. They argued that governance should be built into technology development from the beginning 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 determine 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 approach that supports innovation without ignoring their obligations.
Human judgement and trust
Brasher said AI should assist human reviewers rather than replace them. She said human judgement would remain in place until organisations build trust that what AI agents deliver is accurate. The summit discussions noted that 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. The analogy raised questions about how organisations can introduce AI into everyday workflows without weakening the expertise needed to assess its outputs. If employees rely on AI before developing fundamental knowledge, organisations could have fewer people able to challenge inaccurate or inappropriate recommendations. The consensus was that AI should complement human expertise, with accountable individuals retaining responsibility for important decisions.
Value and piloting
Organisations should resist the temptation to pursue every possible AI application at once, according to the summit discussions. Instead, they should identify areas where technology can address 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 help organisations learn where AI is most effective, retain human oversight and build confidence before expanding successful applications.
The discussions also stressed that governance structures must adapt as AI capabilities and regulatory expectations evolve. Success will depend less on the number of initiatives launched than on the ability to turn promising applications into reliable, scalable business capabilities. The summit’s message was described as optimistic but pragmatic: digital transformation is a collective challenge involving technology, regulatory compliance, data management and organisational culture, and progress requires collaboration within companies and across manufacturers, technology providers, regulators and other stakeholders. Orzechowski described the need to slow down in order to speed up later by getting the foundations right today.