<![CDATA[Purpose: This conceptual study develops a framework for governing AI-assisted customer service in community banking. Approach: A purposive narrative synthesis connects service quality, operational resilience, accountability, and AI risk management literature published before November 2026. No primary observations or statistical estimates are reported. Conceptual contribution: The framework distinguishes task delegation, decision authority, customer explanation, and effective redress. It proposes that automation supports service quality when staff can identify consequential errors, suspend unsafe recommendations, and resolve complaints through an accountable process. Organisational conditions include accessible alternative channels, proportionate record keeping, and independent challenge. Implications: Banks should evaluate completed and corrected customer journeys rather than automated response volume alone. The paper offers proposed controls, indicators, and research propositions; their effectiveness requires subsequent empirical testing.]]>
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