How Banks Can Assess AI Readiness Before Production

Banks often prove that an AI use case can work before establishing whether it can operate reliably in their data, systems, controls, and organisation. This insight maps the readiness gap across data and infrastructure, security and governance, legal and compliance, organisational ownership, strategic prioritisation, and vendor dependencies. It explains why controlled pilot conditions conceal integration, data-quality, monitoring, and accountability weaknesses that emerge in production. Technology leaders should use a use-case-specific assessment to identify material gaps and make an evidence-based go, prepare, or stop decision before scaling.