Human-in-the-Loop AI Agentic Model Implementation in Financial Institutions

Artificial intelligence (AI) adoption can improve banking operations while unsettling employees’ roles, professional identities, and sense of value. This qualitative multiple-case study examined adoption strategies that bank executives may employ to enhance employees’ jobs and self-worth in commercial banks. Sociotechnical systems theory and stakeholder theory guided semi-structured interviews with professionals from seven banks. Each participant constituted a case. Interview data were supplemented by document reviews and reflexive field notes and analyzed through hybrid deductive–inductive coding, within-case pattern matching, and cross-case synthesis. Six themes emerged: system effectiveness through structured design; integration stress and job insecurity; limited stakeholder participation and transparency; varied engagement and capability building; balancing profitability and Human-in-the-Loop values; and external pressures and emergent context. Participants described operational benefits alongside uneven training, restricted employee voice, and uncertainty about career continuity. More supportive accounts emphasized human oversight, leadership communication, learning opportunities, and redeployment. The findings informed of a proposed Human-in-the-Loop AI Integration Wheel connecting inclusive strategy, sociotechnical design, workforce integration, and Human-in-the-Loop evaluation within an adaptive contextual hub. The framework offers a basis for executive planning and future testing; the study did not establish causal effects or validate the framework’s effectiveness.