MedTech companies need to put reliable data, consistent processes, appropriate governance and accountable people in place before they can scale artificial intelligence, according to discussions at the Veeva MedTech Summit in Amsterdam. The event focused less on how quickly the sector can adopt AI than on whether organizations have the foundations to use it effectively.
The technology is already being applied to streamline regulatory work, improve access to information and support more efficient operations. But speakers repeatedly warned that introducing AI into fragmented or inconsistent environments can create more problems than it solves, because outputs become difficult to trust, validate or scale.
Medtronic's four-year groundwork
Becki Brasher of Medtronic described a four-year effort to prepare the company for AI. Rather than starting with the technology, Medtronic harmonized processes, improved data consistency, consolidated systems and established governance structures. Brasher said the company did not begin with AI and had to earn it, according to the account of her conference session.
Her remarks underlined that technology alone cannot deliver transformation. Employees also need the knowledge, confidence and oversight to incorporate new tools into their responsibilities. Without that preparation, even well-designed applications may struggle to produce trusted results.
Governance embedded from the start
Balancing innovation with regulatory compliance was a major theme, particularly in the closing keynote by Erik Orzechowski and Benjamin Rochette. They argued that governance should be built into technology development from the outset rather than treated as a final compliance exercise.
That requires closer collaboration among 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 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 organizations a more flexible approach that supports innovation without neglecting obligations. In this view, compliance and innovation are not opposing priorities; governance can help companies move forward with greater confidence.
Human judgment remains central
The summit also emphasized retaining human judgment and professional expertise. Brasher said AI should assist human reviewers rather than replace them. She expects human judgment to remain essential until organizations build enough trust that AI agents are delivering accurate outputs.
AI can analyze large volumes of information, generate documentation and provide 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 the underlying subject matter to using a calculator without knowing the mathematics behind it.
That concern extends to the next generation of regulatory and quality professionals. If employees rely on AI before developing the necessary knowledge, organizations could end up with fewer people able to challenge inaccurate or inappropriate recommendations. The consensus was not to avoid AI but to make it complement human expertise, with accountable individuals retaining responsibility for important decisions.
Pilots and measurable value
With many potential applications available, organizations need to resist pursuing every opportunity at once. The closing keynote recommended identifying areas where AI can address existing operational challenges and establishing clear measures of success, including time savings, reduced process cycle times, less rework, improved quality and employee adoption.
Controlled pilot projects can show where AI is most effective, preserve appropriate human oversight and build confidence before successful applications are expanded. Because the AI landscape will continue to evolve, governance structures must also adapt to new capabilities and changing regulatory expectations.
The summit's broader message was that digital transformation is a collective challenge. Technology, regulatory compliance, data management and organizational culture cannot be addressed independently. Progress will require closer collaboration within companies and continued engagement among manufacturers, technology providers, regulators and other stakeholders.
The tone was optimistic but pragmatic. AI offers significant opportunities for medical technology, yet realizing them requires patience, preparation and a clear understanding of where human expertise remains indispensable. Orzechowski described the need to slow down in order to speed up later, and the summit's examples suggest that getting the foundations right now is intended to position the industry for future adoption.