MedTech companies are being urged to treat artificial intelligence as an outcome of organisational readiness rather than a starting point, after a summit in Amsterdam brought manufacturers, technology providers and quality specialists together to discuss how the sector can adopt the technology without weakening regulatory standards.
Across presentations, panel sessions and interviews at the Veeva MedTech Summit, a consistent theme emerged: reliable data, consistent processes, appropriate governance and clear ownership of oversight have to be in place before AI tools can be trusted to support regulated work. Speakers described adoption speed as secondary to that groundwork.
Medtronic's four-year groundwork
Becki Brasher of Medtronic described a four-year programme to prepare the company for AI implementation. Rather than starting with the technology, the company harmonised processes, improved data consistency, consolidated systems and established governance structures. Brasher's summary of the effort was that Medtronic did not begin with AI, but had to earn the right to use it.
The reasoning is that introducing AI into fragmented or inconsistent environments can create more problems than it solves. Without reliable information and standardised processes, organisations risk generating outputs that are hard to trust, validate or scale. Brasher also stressed that technology alone cannot deliver transformation, and that employees need the knowledge, confidence and oversight arrangements to fold new tools into their everyday responsibilities.
Governance built in, not added at the end
The summit's closing keynote, given by Erik Orzechowski and Benjamin Rochette, focused on the tension between faster adoption and the quality, safety and regulatory expectations of the medical technology sector. Their argument was that governance should be embedded in technology development from the outset rather than treated as a final compliance exercise.
That, they said, requires closer cooperation between IT, quality and regulatory functions: IT understands the technology and how it is implemented, while quality and regulatory professionals assess risk and define the evidence needed to demonstrate compliance. They also advocated proportionate governance, noting that an AI application supporting relatively low-risk administrative work does not require the same level of control as one influencing patient safety or regulatory decisions. Clear responsibilities, early risk assessments and appropriate controls were presented as the route to a more flexible approach that supports innovation without overlooking obligations.
Human judgement and measurable value
Speakers also argued that human expertise should remain central. Brasher said AI should assist human reviewers rather than replace them, and said in an interview with Med-Tech Insights that human judgement is likely to stay in place as it is today until organisations build trust that what agents deliver is accurate. AI can analyse large volumes of information, draft documentation and make recommendations, but its output still needs 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 the underlying subject matter to using a calculator without knowing the mathematics behind it. The concern raised for the sector is a next generation of quality and regulatory professionals who lean on AI before developing the knowledge needed to challenge inaccurate or inappropriate recommendations.
On business value, the keynote listed time savings, reduced process cycle times, less rework, improved quality and employee adoption as measures of success. Organisations were advised to resist pursuing every available application at once, to target existing operational problems, and to begin with controlled pilot projects that keep human oversight in place before scaling what works.
Orzechowski's phrase for the approach was that companies sometimes need to slow down in order to speed up — a point that framed the summit's broader conclusion that technology, regulatory compliance, data management and organisational culture cannot be addressed independently.