A Triple-Intelligence Framework for Sustainable AI-Driven Workforce Analytics: Integrating Artificial Intelligence, Human Judgment, and Organizational Governance

The use of Artificial Intelligence (AI) within workforce analytics represents a paradigm shift in how organizations make decisions regarding their employees. While AI-enabled workforce analytics can enable proactive and predictive decision-making, the literature identifies multiple substantive risks associated with the use of AI in workforce analytics, namely: algorithmic opacity, automation bias, proxy-based discrimination, and employee surveillance. This literature gap was addressed through developing and validating a Triple-Intelligence Framework (TIF), which integrates three interdependent components - AI intelligence for scalable pattern identification, human intelligence for contextualized interpretation of results and ethical decision-making, and organizational intelligence for governance and accountability. A systematic literature review of explainable AI, algorithmic fairness, and governance of people analytics research (between 2017-2025) produced a TIF for four high-risk decision domains related to workforce decision-making. These included: hiring/mobility, performance management, workforce planning, and remote/hybrid work analytics. The study identified that sustainable workforce analytics requires coordinated action across each of the three intelligence layers and provided a practical path forward consistent with the principles of Industry 5.0.