MedTech companies risk undermining artificial intelligence projects if they adopt the technology before putting reliable data, standardised processes and governance in place, according to discussions at the Veeva MedTech Summit in Amsterdam.
Across presentations, panel sessions and interviews at the event, speakers argued that digital transformation depends less on how quickly tools are adopted than on whether the organisational groundwork exists to use them safely and at scale.
Medtronic spent four years preparing
Becki Brasher of Medtronic described a four-year programme in which the company prepared for AI rather than starting with it. The work focused on harmonising processes, improving data consistency, consolidating systems and establishing governance structures. Brasher summed up the approach by saying the company did not begin with AI but had to “earn” it.
The summit heard that introducing AI into fragmented or inconsistent environments can create more problems than it solves, because outputs built on unreliable information and non-standard processes are difficult to trust, validate or scale. Preparing employees was presented as part of the same effort: staff need the knowledge, confidence and oversight arrangements to fold new tools into their daily responsibilities.
Governance built in, not bolted on
In the closing keynote, Erik Orzechowski and Benjamin Rochette addressed the tension between moving quickly and maintaining the quality, safety and regulatory standards expected of the industry. Their argument was that governance should be designed into technology development from the outset rather than treated as a final compliance exercise.
That requires closer collaboration between IT, Quality and Regulatory teams, they said: IT understands the technology and how it is implemented, while quality and regulatory specialists assess risk and define the evidence needed to demonstrate compliance. They also called for proportionate controls, noting that an AI application supporting relatively low-risk administrative work does not need the same level of oversight as one influencing patient safety or regulatory decisions. Clear responsibilities, early risk assessments and appropriate controls were presented as a route to a more flexible model that supports innovation without losing sight of obligations.
Human judgement retained
Speakers also stressed that AI should support rather than replace professional expertise. Brasher said AI should assist human reviewers, and argued that human judgement will remain in place until organisations build trust that what agents deliver is accurate. The summit heard that AI can analyse large volumes of information, generate documentation and make recommendations, but its output still requires scrutiny, since a convincing answer is not necessarily a correct one.
Orzechowski and Rochette compared relying on AI without understanding its underlying subject matter to using a calculator without knowing the mathematics behind it. The point carries particular weight for the next generation of regulatory and quality professionals: if staff lean on AI before developing the necessary knowledge, companies could end up with fewer people able to challenge inaccurate or inappropriate recommendations.
Measuring value through pilots
On business value, the closing keynote urged organisations to resist pursuing every available application at once and instead target existing operational challenges with clear measures of success. Suggested metrics included time savings, shorter process cycle times, less rework, improved quality and employee adoption. Controlled pilots were recommended so that companies can learn where AI is most effective, retain appropriate human oversight and build confidence before expanding successful applications.
The summit’s broader message was that technology, regulatory compliance, data management and organisational culture cannot be addressed independently, and that progress depends on collaboration within companies and between manufacturers, technology providers and regulators. Orzechowski’s phrase for the approach was to “slow down to speed up”.