In my last post, we explored the "Data Decoupling Debate" and confronted a harsh reality: tearing down data silos and piping everything into a Unified Namespace (UNS) or a data lake is only half the battle. Moving data is not the same as understanding it. If we want to scale Agentic AI, we must bridge the semantic gap.
When Anthropic open-sourced the Model Context Protocol (MCP) late last year, it sent shockwaves through the industrial software ecosystem. Anthropic initiated a new wave of modernization by providing a standardized “universal translator” that allows AI agents to securely connect to enterprise data sources. In effect, it solved a major connectivity and security challenge for enterprise AI.
However, MCP is essentially a grammar framework. It still needs a vocabulary. If an AI agent uses MCP to ask a factory’s data broker for “pump telemetry,” the system still needs to know exactly what a “pump” looks like in the data structure.
This brings us to an emerging development in the industrial interoperability space: CESMII’s Industrial Information Interoperability Exchange (i3X). The increasing engagement across the vendor ecosystem suggests that i3X™ could become an important semantic framework supporting Industrial AI initiatives.
