OPC Foundation Enhances OPC UA for the AI Era with Companion Specifications

[Semih Asil]

The OPC Foundation has taken a significant step to make the OPC UA standard compatible with artificial intelligence (AI). It is expanding its efforts to transform over 430 existing OPC UA Companion Specification files to be suitable for AI-powered engineering assistants, semantic search, and intelligent automation processes.

### What are Companion Specifications?
OPC UA Companion Specifications are machine-readable and consistent information models built on OPC UA for specific industries, devices, and use cases. These models include written specifications and UA NodeSet files for implementation. The OPC Foundation develops these specifications with its working groups or partners.

Companion Specifications provide semantic interoperability in data sharing between different manufacturers and industries through standardized data structures and meanings. This allows industrial applications to discover and integrate data more easily.

### OPC Foundation's Expanding AI Initiatives
Following a successful prototype, the OPC Foundation plans to extend this structure to cover all Companion Specifications. The goal is to make these standards more accessible for applications such as AI-powered engineering assistants, semantic search, automatic documentation, and user adaptation.

In this process, Companion Specifications documents will be converted into AI-specific formats like RAG (retrieval-augmented generation) and MCP (model context protocol) to facilitate their use in AI systems.

### Technical Details and Benefits

• The OPC UA protocol and Companion Specifications are being converted into AI-optimized formats such as Markdown files, visual descriptions, token-optimized RAG chunks, and vector embeddings.
• This will enable more effective integration with AI-based solutions in engineering and automation processes.
• The OPC Foundation offers machine-readable access to this content through existing resources: the UA-NodeSet repository and the UA Cloud Library.

Dr. Holger Kenn, leader of the OPC Foundation AI working group, emphasized that basing agentic AI systems on OPC UA's semantic interoperability principles is critical for their reliability. Stefan Hoppe, President of the OPC Foundation, stated that this step is of great importance for the effective use of industrial data.

### Conclusion
The OPC Foundation is expanding the OPC UA ecosystem to meet the requirements of the AI era to increase reliability and standardization in industrial AI applications. This development is seen as an important step that will support the widespread adoption of AI-based engineering solutions in the manufacturing and automation sectors.