Scalable Artificial Intelligence for Robotics-Enabled Sustainable Construction: A Socio-Technical Perspective

Abstract

The integration of artificial intelligence (AI), robotics, and digital decision-support systems is increasingly reshaping the operational logic of construction management. However, the value of these technologies depends not only on computational capability but also on scalability, human–AI collaboration, organizational readiness, workforce transformation, and sustainable value creation. This research and review paper develops a socio-technical perspective on scalable AI for robotics-enabled sustainable construction by synthesizing the supplied literature on artificial intelligence, future work, organizational decision-making, automation, human–computer collaboration, scientific management, and value-chain optimization. The study adopts a conceptual review methodology and organizes the literature around four interconnected dimensions: intelligent decision support, robotic operational execution, human–AI coordination, and value-oriented sustainability. The analysis indicates that scalable construction intelligence should not be understood as simply increasing computational capacity or deploying more robots. Rather, scalability requires interoperable AI capabilities, adaptable robotic systems, human-centered organizational structures, and measurable operational value. The paper further identifies a critical gap between technological automation and socio-technical implementation: AI can improve decision quality and process consistency, while robotics can translate digital decisions into physical actions, but both require appropriate human oversight and organizational integration. The proposed conceptual framework therefore positions scalable AI as an orchestration layer connecting data-driven intelligence, robotics, construction workflows, workforce capabilities, and sustainability objectives. The findings contribute a theoretically grounded perspective for understanding how AI-enabled robotics can evolve from isolated automation tools into scalable systems for sustainable construction management.