WORKFORCE AUGMENTATION VERSUS AUTOMATION: A CONCEPTUAL FRAMEWORK FOR AI – ERA WORKFORCE MANAGEMENT IN THAILAND'S PRIVATE SECTOR

Abstract

The application of Artificial Intelligence (AI) in organizations is rapidly transforming the nature of work. However, an excessive emphasis on productivity through automation has raised concerns regarding technological dependency, the erosion of human judgment, and the long-term development of workforce capabilities, particularly in the context of Thailand's private sector, which is facing an aging society and the transition toward Industry 5.0. This academic article aimed to develop The Conductor Model, which draws on the metaphor of a conductor's role in coordinating diverse elements to work together, as a conceptual framework for explaining the orchestration of collaboration between humans and AI at the organizational level. The study employed a conceptual literature synthesis integrating theories from management, technology, and human resource management to establish Human–AI Orchestration as the core construct of the proposed model. The synthesis resulted in four theoretical propositions: 1. Task redesign and role clarity, 2. Transparency and calibrated trust, 3. Safe challenge and sustained cognitive engagement, and 4 Continuous capability development and workforce readiness. Together, these propositions facilitated effective Human–AI Orchestration. In addition, the study proposed a Dynamic Reinforcement Mechanism to explain the continuous cycle of organizational learning and capability development. The proposed framework contributed to the literature by integrating AI and organizational management perspectives and extending the role of AI beyond operational efficiency toward the design of human-centered work systems that fostered Human–AI Orchestration, supported human capital development, promoted responsible AI governance, and enhanced organizational sustainability in the Industry 5.0 era.