Humanoid robotics and agentic AI: reframing management theories and future research directions

Abstract

The development of humanoid robots and artificial intelligence (AI) agents represents two distinct but complementary advancements in replicating human capabilities in physical and digital environments. This duality reflects a broader shift toward physical AI a term used to describe embodied AI systems capable of interacting with the physical world through movement and perception - of which humanoid robots are a prominent example. Our paper explores how these technologies reshape and extend established management theories across three disciplines—human resource management (HRM), marketing and consumer behavior (CB), and operations management (OM). Specifically, we propose that in HRM, humanoid robots challenge team role theory by introducing machine-oriented roles, such as trainers and testers, while AI agents prompt a rethinking of social learning theory through their capacity to enable behavior simulation and dynamic feedback loops. In marketing and CB, AI agents reconfigure value co-creation within service-dominant logic by acting as autonomous co-creators of value, while humanoid robots influence social agency theory by altering perceptions of trust and power dynamics. In OM, these technologies drive new opportunities for throughput, agility, and process optimization by integrating real-time predictive analytics and adaptive workflow automation. These insights emphasize that while many traditional theories remain relevant, they require adaptation to account for human–machine collaboration, machine agency, and the hybrid roles emerging in organizational contexts.