The message from this year's Veeva MedTech Summit in Amsterdam was that the central question for MedTech is not how quickly artificial intelligence can be adopted, but whether reliable data, consistent processes, appropriate governance and accountable people are already in place to use it well. The point recurred across presentations, panel discussions and interviews at the event.
AI is already being applied in the sector to streamline regulatory processes, improve access to information and support more efficient operations. But the summit heard that introducing it into fragmented or inconsistent environments can create more problems than the technology solves, because outputs become difficult to trust, validate or scale.
Medtronic: 'We had to earn AI'
Becki Brasher of Medtronic described a four-year programme that deliberately did not begin with AI. The company first harmonised processes, improved data consistency, consolidated systems and established governance structures, and only then moved towards implementation. "We didn't start with AI. We had to earn AI," Brasher said during her conference session.
She also stressed that technology alone cannot deliver transformation, and that employees need the knowledge, confidence and oversight to incorporate new tools into their everyday responsibilities.
Governance built in from the start
In the closing keynote, Erik Orzechowski and Benjamin Rochette argued that governance should be embedded in technology development from the outset rather than handled as a final compliance exercise. That, they said, will require closer collaboration between IT teams, which understand the technology and its implementation, and Quality and Regulatory professionals, who assess risks and determine the evidence needed to demonstrate compliance.
The pair also called for proportionate governance. An AI application supporting relatively low-risk administrative activity does not necessarily need the same level of control as one influencing patient safety or regulatory decisions. Establishing clear responsibilities, risk assessments and appropriate controls early can give organisations a more flexible approach, they suggested, with compliance and innovation treated as complementary rather than opposing priorities.
Human judgement retained
Brasher said AI should assist human reviewers rather than replace them, and that human judgement will remain in place as it is today until organisations build trust that what agents deliver is accurate. The closing keynote compared relying on AI without understanding its underlying subject matter to using a calculator without knowing the mathematics behind it, raising questions about how the next generation of regulatory and quality professionals will develop the expertise needed to challenge inaccurate recommendations.
Proving value through pilots
With potential applications multiplying, organisations were advised to resist pursuing every opportunity at once and instead target existing operational challenges with clear measures of success. Suggested measures include 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 expanded.
The summit's wider conclusion was that digital transformation is a collective challenge: technology, regulatory compliance, data management and organisational culture cannot be addressed independently, and progress depends on collaboration inside companies as well as between manufacturers, technology providers and regulators. Orzechowski coined the phrase "slow down to speed up" to capture the argument that getting the foundations right now leaves the industry better placed to take up tomorrow's opportunities, with human expertise still indispensable.