Univé has embedded AI across the organisation, focusing on broad adoption rather than isolated technical excellence. The insurer’s strategy centres on enabling all employees to work with AI, recognising that uncontrolled adoption will happen anyway if access is restricted.
A key pillar of its approach is organisational redesign. Univé found that AI cannot simply be layered onto existing processes; instead, entire workflows must be rethought with a human-in-the-loop model to fully realise value. This shift is supported by integrating data specialists directly into business teams, ensuring solutions are grounded in real operational needs.
Data infrastructure was also foundational. While Univé benefits from a relatively unified system landscape, challenges remain around data quality, governance, and Machine Learning Operations maturity. The organisation is working to move beyond dashboards toward conversational data access, where employees interact directly with data using AI.
Culturally, the insurer has prioritised adoption through leadership sponsorship, AI champions, and enterprise-wide access to AI tools. Targets such as 80% weekly usage and the development of team-specific AI solutions reinforce this focus. The approach combines top-down direction with bottom-up experimentation through use cases in claims, distribution, and analytics.
Key takeaways for other mutual insurers include focusing on organisation-wide enablement, not just specialist teams; treating AI as a process redesign initiative, not a productivity overlay; investing early in data quality and infrastructure maturity; and using champions, KPIs, and leadership sponsorship to drive adoption.
Speaker:
- Jeroen Heerspink, Innovation Manager, Univé (Netherlands)
