MedTech companies pursuing artificial intelligence need to fix their data, processes and governance before the technology can deliver, according to discussions at this year's Veeva MedTech Summit in Amsterdam. Speakers described AI as increasingly relevant to regulatory work, information access and operational efficiency, but argued that adoption speed matters less than whether the underlying foundations are in place.
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 set up governance structures. Brasher said the company did not begin with AI but had to earn it, the point being that introducing AI into fragmented or inconsistent environments can create more problems than it solves, producing outputs that are hard to trust, validate or scale.
Brasher also stressed preparing employees, noting that technology alone cannot deliver transformation and that staff need the knowledge, confidence and oversight to use new tools in their daily work.
Governance built in, not bolted on
In the closing keynote, Erik Orzechowski and Benjamin Rochette argued that governance should be embedded in technology development from the outset rather than treated as a final compliance exercise. They called for closer collaboration between IT, Quality and Regulatory teams: IT understands the technology and its implementation, while Quality and Regulatory specialists assess risks and define the evidence needed to show compliance.
They also advocated proportionate governance. An AI application supporting low-risk administrative work does 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 neglecting obligations. On this view, compliance and innovation are not opposing priorities.
Human judgement retained
The summit returned repeatedly to the role of human expertise. Brasher said AI should assist human reviewers rather than replace them, and in an interview due to be published said human judgement would remain in place until trust is built that what agents deliver is accurate.
AI can analyse large volumes of information, generate documentation and make recommendations, but its outputs still need scrutiny; a convincing answer is not necessarily a correct one, particularly in a highly regulated sector. The keynote speakers compared relying on AI without understanding its subject matter to using a calculator without knowing the mathematics behind it. A related concern is the next generation of regulatory and quality professionals: if staff lean on AI before building underlying knowledge, organisations could end up with fewer people able to challenge inaccurate recommendations.
The consensus was not to avoid AI but to treat it as a complement to human expertise, with accountable individuals retaining responsibility for important decisions.
Measuring value and starting small
Speakers also urged organisations to be selective. With many potential applications available, companies should identify where technology addresses existing operational challenges and set clear success measures. Value can be judged through time savings, shorter process cycle times, less rework, improved quality and employee adoption. Controlled pilots can show where AI is most effective, keep human oversight in place and build confidence before successful applications are scaled.
Because the technology and regulatory expectations will keep changing, governance structures need to adapt alongside new capabilities. Success, the summit heard, will depend less on the number of AI initiatives launched than on the ability to turn promising applications into reliable, scalable business capabilities.
The wider message was that digital transformation is a collective challenge: technology, regulatory compliance, data management and organisational culture cannot be tackled separately, and progress requires collaboration inside companies and continued engagement between manufacturers, technology providers, regulators and other stakeholders. Orzechowski's phrase for the approach was to slow down to speed up; getting the foundations right now, speakers argued, leaves the industry better placed to take up tomorrow's opportunities.