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Building data governance for regulatory readiness with AI

A regulated financial services organization partnered with Norrin to strengthen its data governance capabilities in response to evolving regulatory requirements. Working together with stakeholders, Norrin co-created and implemented a data governance operating model that established clear ownership and sustainable ways of working.

As part of the transformation, we developed and embedded AI agents directly into governance processes to accelerate implementation, improve quality, and support adoption of new practices.

  • Solution

    Norrin designed and implemented a data governance operating model with AI agents embedded directly into governance processes. We established clear structures, roles, responsibilities, and metadata management capabilities across both business and technical domains. The AI agents were integrated from the start to help teams scale activities, reduce manual effort, and support adoption of new practices.

  • Business value add

    • Established a scalable data governance operating model co-created with stakeholders.

    • Embedded practices into everyday operations across the organization.

    • Improved the quality, consistency, and maintainability of both business and technical metadata.

    • Accelerated implementation and reduced manual effort for teams managing critical data.

    • Supported organizational adoption of new practices through AI-enabled guidance and day-to-day support.

    • Strengthened transparency and accountability of critical data supporting reporting and risk management.

The governance challenge

The organization faced increasing expectations regarding data quality, ownership, traceability, and control. Activities were fragmented across business and technology teams and relied heavily on manual processes which made it difficult to maintain high-quality metadata and scale practices.

At the same time, multiple stakeholders, including data owners, stewards, business experts, and technology teams, needed to adopt new responsibilities and ways of working. The organization needed an operating model that would both define structures and make them practical and sustainable to execute.

Co-creating governance capabilities

Norrin worked alongside the client's experts to build a governance model tailored to the organization's operating environment and regulatory requirements.

Together, the teams established clear structures, clarified responsibilities for data owners and stewards, and introduced common processes and ways of working. We developed metadata management capabilities covering both business and technical domains and enabled consistent execution across teams. We introduced new responsibilities and ways of working, requiring adoption and capability building throughout.

To support this transformation, we integrated AI agents directly into daily work. Teams could use expert agents to access guidance, clarify their approach, and support decision-making. Metadata-focused agents assisted with documentation, descriptions, and workflows, helping teams execute activities more efficiently and consistently. The agents increased productivity and reinforced new practices, supporting organizational change by making processes easier to adopt and follow in daily work.

From program to sustainable governance

The program identified and prioritized critical data elements supporting key reporting and risk management capabilities. We established processes, ownership structures, metadata management practices, and supporting procedures and embedded them into day-to-day operations.

By combining transformation, organizational change, and AI-enabled operations, the organization moved from fragmented and manual practices to a scalable operating model.

 

 

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