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What this paper covers

This is an executive briefing for bank leadership teams on the current state of AI adoption in financial services. It frames AI as a core leadership issue — not a technology experiment — and provides a structured maturity model for moving from awareness to governed execution. The paper was produced through the Business AI Alliance initiative.

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What is the central argument?

AI readiness in banking is not a measure of how many tools have been purchased. It is a measure of how well the institution can apply AI to real work, with trusted data, clear governance, and measurable business value. Banks that treat AI as a tool procurement exercise will stall. Banks that treat it as an operating model question will build advantage.

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What are the key concepts?

The paper introduces a nine-stage maturity model — from awareness through shadow AI, tool standardisation, workflow integration, business-aware systems, supervised autonomy, role-based AI teammates, unified intelligence platform, to adaptive organisation. Each stage is described with practical characteristics and risks specific to banking. It identifies five dimensions across which AI affects the executive agenda: productivity, customer proposition, risk and governance, operating model, and competitive advantage. The paper closes with five immediate actions for a bank executive team: identify high-value workflows, assign business ownership, establish a unified control framework, define levels of AI agency, and build the roadmap around measurable outcomes.

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How does this relate to the AI Maturity Roadmap framework?

This briefing is the executive summary layer of the AI Maturity Roadmap framework, which documents the full nine-stage model with inputs, outputs, metrics, and implementation guidance.