Case Study
ABN AMRO, one of Europe's leading banks, needed a centralized approach to govern and manage the growing number of AI systems within its IT landscape. These complex AI systems were being developed and deployed across the organization.
With regulatory expectations rising on the heels of the EU Artificial Intelligence (AI) Act, the bank faced challenges in maintaining a unified view of its AI initiatives. Its existing Confluence-based administration model offered limited visibility. With heavy reliance on manual, time-intensive processes, it became increasingly difficult to track lifecycle progress and ownership, demonstrate compliance, and ensure accountability for high-risk AI systems.
Following a successful proof of concept (POC), Infosys led the end-to-end implementation of the bank’s AI registry. This included integration with existing systems, data migration, and operational readiness activities required for enterprise-wide adoption. The engagement also involved close collaboration with stakeholders across the risk, compliance, and technology teams. This ensured the platform met both regulatory and operational requirements.
The solution is now live, establishing a centralized AI registry. It strengthens governance, improves lifecycle visibility, and supports EU AI Act compliance readiness across ABN AMRO's growing AI landscape.
275
AI systems centrally governed; 103 in production, 172 in progress
35000+
Employees with automated, enterprise-wide access to the AI registry
876
Active users driving AI governance and compliance
6200+
Platform logins reflecting consistent, ongoing usage.
Key Challenges
The bank faced several challenges in establishing a scalable and transparent approach to AI governance, including:
- A lack of a centralized, scalable approach to AI governance across the bank’s Confluence-based administration
- Limited lifecycle visibility into AI use cases and their status
- Inconsistent compliance processes to meet the requirements of the EU AI Act
- Limited accountability for high-risk and low-risk AI use cases
- Siloed stakeholder processes delaying the capture and maintenance of critical technical and business metadata for AI systems
- Limited access to records for regulatory review
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Infosys Approach
Assessed AI governance requirements and identified the right platform to support enterprise-wide adoption and EU AI Act readiness
Executed a POC to validate governance workflows, compliance requirements, and business adoption needs
Configured AI system lifecycle workflows from ideation to production
Added assessment journeys and governance templates to standardize AI system management
Integrated application, data, and AI information to establish end-to-end visibility and traceability
Delivered and operationalized the AI registry to enable adoption across AI delivery teams and governance stakeholders
The Solution
A centralized AI registry replacing manual processes with structured, enterprise-wide AI governance
- Centralized AI registry supporting EU AI Act compliance readiness, replacing the Confluence-based administration model
- Structured lifecycle management enabling AI initiative registration, assessments, and end-to-end status tracking
- Assessment capabilities supporting AI systems across different risk levels, with versioning and governance controls to track lifecycle changes
- Integrated AI information providing greater visibility into how AI systems are developed and governed
- Secure authentication and automated provisioning via Azure Active Directory (AD), improving transparency and accountability across the platform
Business Outcomes
Strengthened EU AI Act compliance readiness through centralized AI governance
Established a single source of truth for 275 AI systems, increasing visibility across the AI landscape
Enhanced accountability and ownership for high-risk AI systems
Simplified regulatory reporting and audit evidence preparation
Connected DataOps, DevOps, and AI/ML Ops governance workflows
Enabled continuous oversight through periodic AI system assessments
Benefits
Enterprise-wide advantages delivered through centralized AI governance and compliance readiness
Simplified oversight through a single platform for the full AI lifecycle
Easier compliance with internal policies and EU AI Act requirements
Reduced governance effort through centralized AI administration
Faster AI system delivery through integrated governance workflows
Improved visibility across data, applications, and AI systems
Enhanced collaboration among data scientists as well as machine learning (ML) and AI engineers
Reduced documentation burden for maintaining AI governance records
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