MedTech companies are eager to adopt artificial intelligence, but discussions at the Veeva MedTech Summit in Amsterdam focused on a less visible prerequisite: building the data, process and governance foundations needed to use the technology reliably. Speakers and panel participants repeatedly returned to the idea that successful digital transformation depends on getting the fundamentals right before scaling AI.
Medtronic’s experience was presented as a case in point. Becki Brasher described a four-year effort to prepare the company for AI. Rather than starting with an AI application, 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 right to use it.
That sequence matters because applying AI in fragmented or inconsistent environments can create more problems than it solves. Without reliable information and standardised processes, organisations risk producing outputs that are hard to trust, validate or scale. Medtronic’s account also underlined the need to prepare employees: technology alone does not deliver transformation, and staff need the knowledge, confidence and oversight to incorporate new tools into daily work.
Governance embedded from the start
Balancing innovation with regulatory compliance was another theme, particularly in the closing keynote by Erik Orzechowski and Benjamin Rochette. As adoption accelerates, MedTech organisations must move quickly without compromising quality, safety or regulatory standards. The speakers 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 understands implementation, while Quality and Regulatory professionals assess risks and define the evidence needed to demonstrate compliance. The keynote also called for proportionate governance: a low-risk administrative AI application does not need the same controls as one that affects patient safety or regulatory decisions. Clear responsibilities, early risk assessments and appropriate controls can give organisations a more flexible route to innovation while preserving their obligations.
Human judgement and measurable value
Despite AI’s growing capabilities, the summit stressed that human judgement remains essential. Brasher said AI should assist human reviewers rather than replace them, and she argued that judgement will remain necessary until organisations build trust that agents deliver accurate results. AI can analyse information, generate documentation and make recommendations, but its output still requires scrutiny. A convincing answer is not necessarily a correct one, especially in a highly regulated sector.
The closing keynote illustrated the point by comparing reliance on AI without understanding its subject matter to using a calculator without knowing the mathematics behind it. The concern extends to 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.
Speakers also urged companies to focus on business value rather than pursuing every possible application at once. They suggested identifying operational challenges, setting clear success measures and starting with controlled pilots. Potential measures include time savings, shorter process cycle times, less rework, improved quality and employee adoption. Pilots can show where AI is most effective, preserve human oversight and build confidence before wider deployment.
The summit’s broader message was that digital transformation is a collective challenge. Technology, compliance, data management and organisational culture cannot be addressed in isolation. Progress will require collaboration within companies and continued engagement among manufacturers, technology providers and regulators. Orzechowski described the approach as slowing down in order to speed up: by establishing foundations now, the industry can be better placed to adopt future capabilities.