Agentic AI Deployment Readiness and Responsible Value Realization in Sustainable Banking

Agentic artificial intelligence (AI) is a consequential technological frontier in banking because it shifts AI from passive assistance and generative interaction toward goal-directed workflow execution. Responsible and sustainable banking transformation thus depends on the readiness conditions under which agentic AI can move from pilots to governed production and value realization. This study develops a configurational forecasting framework for agentic AI deployment readiness in banking. Because comparable initiative-level evidence remains scarce and commercially sensitive, the paper adopts a transparent, case-informed synthetic configurational simulation rather than claiming to analyze actual bank projects. Drawing on public banking AI cases, technology-diffusion and foresight literature, AI governance research, and role-based stakeholder archetypes, we construct a synthetic dataset of 90 banking-related agentic AI initiatives and apply fuzzy-set Qualitative Comparative Analysis (fsQCA). The bounded simulation indicates that production maturity is associated with the conjunction of data readiness, leadership commitment, governance maturity, workflow redesign capability, human-agent collaboration maturity, and low legacy-system complexity. A supplementary analysis shows that deployment alone is insufficient: value is realized only when deployment is combined with redesigned workflows, governed data use, and human-agent collaboration, whereas non-deployment arises from distinct failure configurations rather than the mere inverse of success. These patterns reframe governance as an enabler of bounded autonomy rather than a constraint. The study offers a reproducible readiness logic for responsible value realization, customer protection, workforce capability, and financial-system resilience.