A digital twin framework for enhancing human–agentic AI–machine collaboration

This paper defines a framework for improving collaboration between humans and machines using digital twins and Agentic AI and provides guidelines for collaboration. Human–agentic, AI, and machine collaboration is an innovative approach that combines human intelligence, agentic AI systems, digital twins, and machines to improve productivity, efficiency, and decision-making in various industries. Defining a framework for agentic AI, supported by digital twins, requires a multi-layered innovation approach encompassing artificial intelligence algorithms, persons, products, technologies, processes, and business models. This paper emphasizes that this comprehensive approach is not just a strategy, but a necessity in the current global context. This paper defines a framework for human–machine collaboration using Agentic AI and digital twins, including the benefits and challenges. It also provides guidelines for collaboration. This framework implies a more integrated interaction between three parties: humans, automation (agentic AI and digital twins), and machines, rather than just two-party relationships between humans and machines or robots. The existence of a multi-party system requires effective, efficient, economic, functional, and technical frameworks, which are included in the guidelines annexed to this paper. The paper discusses the use of an advanced framework. It applies to any organization. The framework is innovative compared to existing models (e.g., frameworks for human–robot collaboration) and emphasizes novel components (e.g., the role of AAI in orchestration).