Digital twins in manufacturing have evolved from single-asset simulations into ecosystem-scale constructs spanning suppliers, OEMs, and standards bodies, since no single organization holds all the data, models, or expertise needed. Snowflake's AI Data Cloud is positioned as the coordination layer solving IT/OT data fragmentation, semantic interoperability, and data sovereignty concerns through zero-copy sharing and semantic views. Agentic AI, delivered via Snowflake Cortex (Agents, Analyst, Search), turns passive digital twins into active decision-making systems for use cases like predictive maintenance, cross-functional decision support, and supply chain intelligence, governed by a data-model-agent security framework.
Table of contents
How Snowflake AI Data Cloud and Agentic AI Enable Cross-Organizational IntelligenceFrom Asset Models to Ecosystem ConstructsThe Evolution TrajectoryWhy Platform Economics Explains Digital Twin EcosystemsWhy No Single Actor Can Build a Complete Digital TwinSnowflake AI Data Cloud as the Ecosystem Coordination LayerSnowflake AI Data Cloud as Ecosystem FoundationGet Antti Sirkka’s stories in your inboxSemantic Views as Dynamic Twin InterfacesAgentic AI: From Passive Twins to Active Decision SystemsCortex AI: The Intelligence Layer for Manufacturing TwinsManufacturing Use Cases: From Insight to ActionGovernance: The Data-Model-Agent Security FrameworkThe Bottom Line380 Impressions