AI strategy and operating model in retail banking – from isolated initiatives to scalable AI impact

Technology alone does not make AI transformations successful. Without a clear vision, unambiguous accountabilities, and resilient governance, AI remains stuck where it starts: in isolated use cases, decentralized initiatives, and limited business impact.

This was exactly the situation our client faced. Several promising AI initiatives had been launched across business units, technically sound but strategically disconnected. Responsibilities were fragmented, decision-making mechanisms were missing, and there was no overarching framework to scale AI beyond individual proofs of concept.

The mandate was clear: overcome this fragmentation by consolidating decentralized activities into a coherent AI strategy, anchored in a scalable operating model and backed by an ambitious investment framework of up to 3% of total revenues.

Eve by Eraneos applied a structured four-step approach, drawing on our core capabilities in AI strategy, operating model design, and transformation enablement:

1. AI Maturity Assessment: Benchmarking the bank’s internal AI capabilities against national and international peers, and identifying untapped market potential.
2. Vision & Strategy Definition: Formulating an ambitious vision for AI’s value contribution and deriving concrete strategic goals and priority strategic priorities.
3. Operating Model Design: Designing an integrative “Hub & Spoke” AI operating model, binding decision-making mechanisms, and a scalable technology and data foundation, purpose-built to evolve the organization into an AI-driven bank.
4. Operationalization Roadmap: Planning the rollout of the AI strategy to ensure measurable growth and efficiency gains from day one.

The engagement delivered a holistic AI operating model with tangible results across seven dimensions, enabling the bank to scale AI enterprise-wide and unlock sustainable growth and efficiency potential:

1. Scalable Organization: A central AI Hub with decentralized Spokes across business units, balancing centralized infrastructure and governance with distributed business knowledge and ownership.
2. Clear Roles & Responsibilities: Dedicated business and tech expert roles within the Hub, complemented by AI Ambassadors in the business units to drive adoption on the ground.
3. Standardized Delivery: Unified use-case processes with adaptive governance depth, enabling consistent yet flexible execution across AI initiatives of varying complexity.
4. AI-Native Processes: Critical business processes redesigned around AI-native principles, with targeted efficiency gains.
5. Future-Ready Technology: A technology foundation for agentic AI, positioning AI as the primary orchestrator of existing and new processes.
6. Regulatory Readiness: Regulatory requirements such as the EU AI Act fully embedded into the operating model, ensuring compliant scaling of AI initiatives.
7. Transformation Momentum: A company-wide enablement and communication program driving phased change management and organization-wide AI adoption.

The bank has moved from fragmented experimentation to a strategically governed, organization-wide AI transformation. With an investment framework of up to 3% of total revenues earmarked for AI and targeted efficiency gains of 30 to 50% in AI-native processes, it is positioning itself as a pioneer of AI adoption in European retail banking and sustainably unlocking growth and efficiency potential.

The client is a leading retail banking group in its home market, operating a broad network of regional banks with nationwide reach and a strong focus on private and SME clients. It combines local proximity with the scale and resources of a major financial institution.