Digital Twin

A virtual replica of a physical object, process, or system — kept synchronized with the real-world counterpart via sensors, data feeds, or simulation — used for monitoring, analysis, and optimization. AI is increasingly embedded in digital twins to predict failures, optimize operations, and run 'what if' simulations without risk to the real system. Digital twins appear on the EU AI Act's list of high-risk AI applications when used in critical infrastructure (energy grids, water systems, transport). From a governance perspective, digital twins that inform real-world decisions need the same documentation, accuracy assurance, and human oversight as any high-stakes AI system — data quality in the twin directly determines the quality of decisions made from it.

A manufacturing company runs a digital twin of its production line, using AI to predict equipment failures 48 hours in advance. The twin's predictions trigger maintenance work orders — making the AI's accuracy and the quality of sensor data governance-critical.