Embodied Artificial Intelligence-Driven Integrated Development Environment for Industrial Automation Systems: Requirements and Framework

As industrial automation moves toward more intelligent, adaptive, and human-centered operation in the context of Industry 5.0, embodied artificial intelligence (AI) is becoming increasingly relevant to real-world industrial systems. However, existing development environments and toolchains remain fragmented, making it difficult to support embodied AI in industrial automation systems consistently across development, deployment, and runtime operation. To address this gap, this article examines two converging trajectories in current research and practice: the evolution of traditional industrial development environments toward embodied AI capabilities and the emergence of integrated development environment (IDE)-oriented support for embodied AI workflows. Based on this analysis, the article synthesizes a set of functional, deployment, and performance requirements for embodied AI-driven IDEs in industrial automation and further derives a conceptual framework organized around modular architecture, enhanced functional modules, and lifecycle-oriented workflow integration. The article also highlights four research directions for advancing such IDEs, including lifecycle management, autonomous development support, hardware-agnostic deployment, and safety and security mechanisms. By connecting requirement analysis with framework design, this work provides a structured perspective on the development infrastructures needed to make embodied AI in industrial automation systems more deployable, maintainable, interoperable, and trustworthy.