From pilot to living system: AI governance in pharma

From hype to reality: Operationalizing AI governance in Life Sciences

As AI moves from experimentation to enterprise-level strategy, Life Sciences companies face a pressing challenge: how to scale AI responsibly, without losing momentum.

This isn’t just a technology problem, it’s an organizational and, increasingly, a regulatory one. Governance must be embedded across functions, aligned with compliance, and built to adapt to a changing regulatory environment.

In a recent engagement with a global pharma company, our consultants Alexander Dietrich and Tobias Künkler supported our clients in translating regulatory, IT and compliance requirements into a governance model with organizational structure as well as an implementation and change plan.

What we learned from the frontlines

Drawing from this hands-on experience, here are four lessons that stood out:

• Senior sponsorship isn’t optional, it’s foundational
  Without visible support from senior leaders, governance risks becoming a compliance checkbox. Executive backing helped our client build legitimacy across global functions and secure centralized funding for early pilots.
• Start with pilots that bridge silos
  Rather than drafting a perfect framework from day one, we co-designed small pilot projects that cut across geographies and business lines. This allowed us to test principles in practice, before scaling them systematically.
• Build internal capability early
  While external experts can offer momentum, long-term success depends on embedding roles within the business. We helped define cross-functional governance roles and clarify decision-making across Legal, Data, Compliance, and IT teams.
• Design for global complexity, not rigidity
  Pharma operates across highly regulated regions, what works in the EU may not in the US or China. The framework we helped shape needed to be structured enough to guide and flexible enough to adapt.
• Change management
  Generating buy-in from key stakeholders early

Why it matters now

Regulatory change is accelerating, and it’s global. From the EU AI Act to evolving FDA guidance, compliance can no longer be an afterthought.

While AI regulations are still new and evolving, they require ongoing change management to ensure compliance.
The core question isn’t just “what does good AI governance look like?” It’s:

Are you ready to scale AI use cases responsibly across your organization?

There’s no single framework that fits all, but there is a right way to start: collaboratively, pragmatically, and with a bias for impact over perfection.

At a-connect, we don’t bring standardized frameworks. We bring momentum, structure, and partnership, working side-by-side with internal teams to co-create solutions that stick.

We’ve helped clients move from vision to execution, without slowing innovation. And we believe that’s what makes the difference in AI governance today.

About the author

Alexander Dietrich is a Project Manager focusing on the Life Science sector in the a-connect Zurich office. With a strong focus on helping pharma and Life Sciences clients commercialize their assets, Alex brings expertise in launch strategies, go-to-market execution, and market access initiatives across Europe. As a former strategy consultant at PwC Strategy and Simon-Kucher. Alex holds a MSc from ESADE Business School and Bocconi University.

Tobias Künkler is an Independent Consultant with more than 18 years of experience in Data and Digital transformations in the Life Science sector. As trained Accenture consultant, he recently served as interim Chief Data Officer at various pharma companies. Tobias is experienced in designing and operationalizing Data & AI operating models and in pharma. He has also done work outside pharma, mainly in retail, energy, insurance, and logistics. Tobias holds an Executive MBA from Quantic School of Business & Technology.

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