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What this paper covers

This is a structured guide for banking leadership teams navigating AI adoption. It expands the nine-stage AI maturity model into three distinct phases — foundational, integration, and transformational — with detailed characteristics, hidden risks, and practical actions at each stage. The paper was produced through the Business AI Alliance initiative.

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What is the central argument?

Banks still treating AI primarily as a tool question are already falling behind. The real task is to decide where AI belongs in the operating model and which moves must happen in the next six to twelve months. The goal is to move from experimentation to governed execution that delivers real commercial and customer value.

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How is the roadmap structured?

The guide organises the nine maturity stages into three phases: Phase one — foundational stages (awareness, shadow AI, tool standardisation) focus on bringing informal AI use under institutional control. The hidden risks at this phase are superficiality, data leakage, and stalling at tool access without achieving transformation. Phase two — integration stages (workflow integration, business-aware systems, supervised autonomy) move AI from generic assistant to specialised component of the bank’s operating model. This is where AI becomes operationally useful and begins working with the institution’s own data, policies, and context. Phase three — transformational stages (role-based AI teammates, unified intelligence platform, adaptive organisation) represent a fundamental shift in how the bank operates. AI reshapes roles, runs on a shared enterprise layer, and enables continuous organisational learning. The guide measures progress across five dimensions of AI impact: productivity, customer proposition, risk and governance, operating model, and competitive advantage.

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What is the action plan for execution?

The paper closes with five actions for moving from discussion to execution: identify high-value workflows, assign business ownership, establish a control framework, define levels of AI agency, and build the roadmap around measurable outcomes rather than demonstrations.

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How does this relate to the AI Maturity Roadmap framework?

This guide is the detailed companion to the AI Maturity Roadmap framework, providing the narrative context, phased structure, and hidden-risk analysis that supports the framework’s practical application.