By
Andrew Collins
Research Fellow, OT Architecture and Operations
April 14, 2026
Digital twin technology, the creation of dynamic virtual models that replicate the behavior of physical assets and systems in real time, has moved from an engineering concept to an operational reality across significant portions of the industrial sector. Manufacturers, energy operators, and infrastructure managers are deploying digital twin platforms to optimize performance, predict failures, accelerate engineering decisions, and reduce the cost of physical testing. The operational value proposition is genuine and substantial.
What has not kept pace is the governance framework surrounding these deployments. Digital twins are, by definition, highly detailed representations of physical infrastructure. They contain operational parameters, engineering specifications, process logic, and performance data that, in the wrong hands, constitute a comprehensive blueprint for disrupting or attacking the systems they model.
The Data Exposure Question
A digital twin’s value is proportional to the fidelity of the data it contains. The same richness that makes these models operationally powerful makes them attractive intelligence targets. An adversary with access to a high-fidelity digital twin of a power generation facility, a chemical plant, or a water treatment system gains operational knowledge that would otherwise require years of physical reconnaissance to develop.
Executive leadership should ask a direct question about any digital twin deployment: who has access to this model, where does the underlying data reside, and what security controls govern that access and storage? The answers at many organizations are insufficient for the sensitivity of the information involved.
Vendor and Cloud Dependency
Most industrial digital twin platforms are delivered through third-party vendors, often with data hosted in cloud environments that the asset-owning organization does not directly control. This creates a data custody question that procurement and legal frameworks frequently address inadequately. Understanding where operational data resides, what contractual protections govern its use, and what happens to that data in the event of a vendor transition or acquisition is a governance baseline that organizations should establish before deployment rather than after.
Integration with Operational Technology
Digital twins that integrate directly with live operational technology systems introduce a bidirectional data flow that requires the same security rigor as any operational technology network connection. A compromised digital twin platform that has write access to physical control systems represents a potentially serious attack vector, not only a data exposure risk. The governance standards applied to this integration should reflect that possibility.
Capturing the Value Responsibly
None of this analysis argues against digital twin adoption. The technology delivers real operational and economic benefits that organizations across industrial sectors are right to pursue. It argues for governance that matches the sensitivity of the environments being modeled.
Organizations that establish clear data classification policies, access controls, vendor oversight requirements, and security architecture standards for digital twin deployments will be positioned to capture the technology’s benefits while managing its risks. Those that deploy first and govern later are building operational dependencies on a foundation they have not fully secured.
