From algorithmic engagement to sustainable work: a TRUST-AI framework for human-centered HR analytics in emerging economy workplaces

Abstract

AI-enabled HR analytics is changing how organizations understand employee engagement, workforce risk, and managerial intervention. These tools can help organizations identify problems earlier and design more targeted responses. However, they also raise an important governance question: when does analytics support employees, and when does it become a source of surveillance, opacity, and control? This question is especially important in emerging economy workplaces, where rapid digital adoption often occurs alongside uneven digital literacy, developing data-governance systems, hierarchical managerial cultures, and limited employee voice mechanisms. This conceptual analysis argues that AI-enabled HR analytics should be understood as a human-centered governance practice, not only as a predictive tool. The article develops the TRUST-AI framework for responsible and sustainable HR analytics. The framework includes six dimensions: transparent data relations, responsible algorithmic stewardship, user and employee voice, sustainable well-being orientation, trust-building managerial use, and accountable intelligence. Together, these dimensions show how organizations can move beyond algorithmic engagement measurement toward sustainable work by strengthening data legitimacy, interpretive fairness, employee participation, managerial responsibility, and long-term human sustainability. The article contributes to digital HRM, responsible AI, employee engagement, and sustainable HRM scholarship. It shows that the value of AI-enabled HR analytics lies not only in prediction or efficiency, but also in whether employees experience data-driven HRM as understandable, contestable, fair, supportive, and trustworthy. Practically, the framework offers HR leaders, line managers, technology vendors, and policymakers a governance guide for implementing AI-enabled HR analytics in ways that strengthen transparency, employee voice, accountability, trust, and sustainable work.