A Risk-Based Ethical Governance Framework for Retail AI with Proportionality, Oversight, and Regulatory Alignment

Purpose: This paper proposes an Ethical Governance Framework for intelligent retail systems, addressing algorithmic bias, privacy intrusions, and limited customer recourse that erode trust and attract regulatory scrutiny. Methodology: The framework synthesizes six principles (fairness, privacy by design, proportionality, transparency, accountability, human oversight) drawing on OECD AI Principles, NIST AI RMF, GDPR [13], and EU AI Act [12]. Evaluation comprises scenario-based ethical risk analysis, regulatory requirement mapping, and assessment against documented incidents. Findings: The framework demonstrates 87.5% scenario mitigation, 92% GDPR coverage, 100% EU AI Act prohibited practice coverage, and ROI of 100% to 430% with 6-to-18-month payback. Key innovations include a four-level Proportionality Ladder for graduated interventions, structured external stakeholder engagement, and implementation economics. Unique contribution to theory, practice and policy: This work provides a system-agnostic governance layer for intelligent retail platforms, operationalizing abstract ethical principles into concrete technical controls and organizational processes aligned with emerging regulatory requirements.