Enterprise GenAI Transformation in a Regulated Fund Administration Organization

In many organizations, AI is emerging faster than policies, decisions, and accountability. People are testing, tools are multiplying, and enthusiasm is growing—but the impact on outcomes remains unclear. This case study shows how a large, regulated financial institution managed to organize AI without slowing down: from fragmented initiatives to a meaningful, secure, and scalable model that simply works.

Transformacja Enterprise GenAI w regulowanej organizacji administracji funduszy

Project goal

Establish a comprehensive, enterprise-wide AI programme for regulated fund administration organisation, balancing innovation velocity, regulatory compliance, and organizational adoption.

Key objectives included:

  • Defining a clear AI maturity baseline, ambition level, and a pragmatic roadmap to scale AI adoption

  • Deploying the AI6 Framework – Symmetria Partners’ proprietary methodology addressing six critical dimensions of AI adoption, with technology as only one component

  • Building robust AI governance, risk management, and decision frameworks compliant with EU regulatory expectations

  • Developing organizational capability, change management, and AI literacy to ensure sustainable adoption

  • Transitioning from fragmented experimentation to a value-driven, enterprise AI operating model

Assumptions

The organization entered the programme with strong interest in AI, but limited structural readiness:

  • 1,700+ employees across four countries with fragmented, bottom-up AI initiatives

  • Growing “shadow AI” usage, with employees adopting external tools without formal guardrails, increasing compliance and data risk

  • No approved enterprise AI tooling available to employees

  • Low employee engagement (organizational NPS: –32), signalling significant change management risk

  • A complex regulatory environment (multi-jurisdictional supervision) requiring governance to be embedded from day one

Actions taken

1. Business-First Value Focus

  • Shifted AI narrative from experimentation to measurable business value

  • Prioritised low-risk, high-impact use cases aligned with operational efficiency and productivity

  • Created balanced scorecard to track progress of the programme for supervisory board, management board, programme portfolio management and employees.  

2. Innovation & Use Case Selection

  • Designed a use case prioritisation framework based on 8 structured criteria (value, feasibility, risk, scalability, regulatory exposure)

  • Established a transparent pipeline from idea → pilot → scale decision

3. Organization & Change Management

  • Designed and launched an AI Ambassador Programme

  • Selected 30 ambassadors from 100+ applicants, covering all core business functions

  • Positioned ambassadors as Educators, Storytellers, Connectors, Sensing Agents, and Change Agents

4. Training & Capability Development

  • Implemented a tiered AI learning model (executives, managers, ambassadors, general population)

  • Defined a robust communication strategy including rich and lean communication channels

5. Ethics, Risk & Governance

  • Established a dual governance model: AI Governance & Risk Committee (compliance, risk, legal, IT), AI Innovation Committee (business-led value creation)

  • Delivered full governance artefacts: terms of reference, decision rights, agendas, escalation paths

  • Embedded regulatory-by-design principles aligned with EU expectations

6. Data, Analytics & Technology Enablement

  • Defined a business–IT collaboration model using a secure sandbox approach

  • Enabled “test fast, learn fast” experimentation within controlled boundaries

  • Clarified ownership between business, IT, and risk functions

Duration and impact

The entire initiative was implemented within 6 months.

The programme successfully moved the organization from high interest / low structure to:

  • A repeatable enterprise AI operating model

  • Reduced compliance and reputational risk related to uncontrolled AI usage

  • Improved employee engagement through empowerment, clarity, and capability building

  • A scalable foundation for future cost reduction, productivity gains, and innovation

If your organization faces similar challenges – high interest in AI but a lack of structure, clear rules, and risk controls – we help you structure your approach to AI and build a solid foundation for further, secure development.

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