Autonomous Circular Economy Systems: The Role of AI Agents and Digital Twins in Self-Optimizing Sustainable Business Ecosystems

This study examines how autonomous digital technologies are associated with Sustainable Business Performance in circular-economy settings. Drawing on the Resource-Based View and dynamic capabilities theory, it develops a framework linking AI Agent Autonomy, Digital Twin Capability, Self-Optimization Capability, Circular Process Integration, Algorithmic Trust, and Sustainable Business Performance. Cross-sectional survey data were collected from 319 purposively selected managers and decision-makers in Jordanian organisations between January and April 2026 and analysed using Partial Least Squares Structural Equation Modelling in SmartPLS 4. The findings show that AI Agent Autonomy and Digital Twin Capability are positively associated with Self-Optimization Capability, which is subsequently associated with Circular Process Integration. Circular Process Integration and Algorithmic Trust are positively associated with Sustainable Business Performance. However, AI Agent Autonomy had no significant direct relationship with Sustainable Business Performance, while the direct relationship of Digital Twin Capability was weak. The simple and serial mediation results indicate that Self-Optimization Capability, Circular Process Integration, and Algorithmic Trust represent important mechanisms connecting autonomous technologies with sustainable performance. The study contributes by integrating technological, organisational, operational, and behavioural mechanisms within one circular-economy framework. The findings suggest that the organisational value of AI agents and digital twins depends on adaptive capability, circular-process implementation, and stakeholder trust rather than technology adoption alone.