Mariana Hebborn

For organisations operating in highly regulated environments, scaling AI can feel like a constant negotiation between innovation and compliance. Requirements under the EU AI Act and GDPR, alongside works council and employee consultation requirements, ethical standards and industry-specific regulation, can be seen as barriers to adoption. But when translated into practical processes, they can provide the guardrails organisations need to move faster and with greater confidence.

Drawing on her experience leading AI and data governance within a highly regulated HR environment, Mariana Hebborn will explore how organisations can enable responsible, self-service AI adoption at scale. Participants will examine how the EU AI Act, GDPR, works council requirements, ethical considerations and industry-specific regulation affect AI adoption, before working together to turn these barriers into practical opportunities for progress.

Through collaborative exercises, participants will identify their most pressing barriers, compare approaches across industries and map out tangible actions that can be applied within their organisations.

Attendees will:

• Identify the regulatory, ethical and organisational barriers slowing AI adoption.
• Explore the implications of the EU AI Act, GDPR and workforce consultation.
• Translate complex requirements into practical processes employees can follow.
• Build an actionable roadmap for responsible AI adoption at scale.

Walk away with a clearer view of how regulation can support rather than stall innovation, alongside practical actions for moving from compliance requirements to responsible AI adoption at scale.

At Merck, AI adoption is being operationalized through workforce design, embedding learning in real workflows rather than through standalone courses. HR leads act as the organizational lighthouse, linking AI fluency to role-specific skills employees can apply immediately. Mariana Hebborn, Head of HR Data & AI Governance, unpacks the operating model, governance, and activation tactics that enable responsible AI to scale across thousands of employees. Responsible AI becomes part of the organization's mindset, data, tooling, and operating model.