Artificial intelligence is spreading through MedTech in regulatory work, information access and operations, but speakers at the Veeva MedTech Summit in Amsterdam argued that the central question is not how fast companies can adopt it. It is whether they have the reliable data, consistent processes, governance and people needed to use it well.
Foundations before deployment
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. “We didn’t start with AI. We had to earn AI,” Brasher said.
The warning was that introducing AI into fragmented or inconsistent environments can create more problems than it solves. Without reliable information and standardised processes, outputs become difficult to trust, validate or scale. Medtronic’s experience also underlined the need to prepare employees: technology alone cannot deliver transformation, and staff need knowledge, confidence and oversight to use new tools responsibly.
Governance from the outset
In the closing keynote, Erik Orzechowski and Benjamin Rochette focused on the tension between faster AI adoption and the quality, safety and regulatory standards expected in MedTech. They argued that 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 demonstrate compliance. The speakers also called for proportionate governance: an AI application supporting low-risk administrative work does not need the same controls as one that influences patient safety or regulatory decisions. Clear responsibilities, early risk assessments and appropriate controls can support innovation without weakening obligations.
Human judgment remains central
Despite AI’s growing capabilities, the summit did not treat automation as an end in itself. Brasher said AI should assist human reviewers rather than replace them, and that human judgment will remain essential until organisations build trust that AI agents deliver accurate outputs. AI can analyse large volumes of information, generate documentation and make recommendations, but those outputs still require scrutiny; a convincing answer is not necessarily a correct one in a highly regulated environment.
Orzechowski and Rochette compared relying on AI without understanding its subject matter to using a calculator without knowing the mathematics behind it. The concern extends to workforce development: if junior regulatory and quality professionals lean on AI before building underlying knowledge, companies could end up with fewer people able to challenge inaccurate or inappropriate recommendations. The consensus was that AI should complement expertise, with accountable individuals retaining responsibility for important decisions.
Value through controlled pilots
Speakers also warned against pursuing every possible AI application at once. Organisations should target existing operational challenges and define measures of success. Suggested measures included time savings, reduced process cycle times, less rework, improved quality and employee adoption. Controlled pilots can show where AI is most effective, preserve human oversight and build confidence before successful applications are expanded.
The broader conclusion was that digital transformation is a collective challenge. Technology, regulatory compliance, data management and organisational culture cannot be addressed separately. Progress will depend on closer collaboration within companies and between manufacturers, technology providers, regulators and other stakeholders.
The summit’s message was optimistic but pragmatic. AI offers significant opportunities in 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.”