A digital twin is a virtual model that mirrors a real-world asset, system, or process. It enables organizations to simulate scenarios, monitor performance, and predict outcomes. Using continuous data feeds, the digital twin updates in near-real time to reflect the state and performance of its counterpart.
Combined with advances in artificial intelligence (AI), cloud computing, and real-time analytics, digital twins are evolving from experimental tools into operational assets that can transform how government programs are designed, managed, and secured.
Digital Twins Powered by AI
The use of digital twins is not new. NASA pioneered the use of a digital twin in the 1960s for the Apollo 13 mission, adapting and modifying existing simulations to explore the causes of, and solutions for, an explosion that took the astronauts far off their path and deprived them of life-sustaining resources. As the technology to create digital models has advanced, the use of digital twins has expanded to a wide range of scenarios.
AI has supercharged the use of digital twins. With AI layered on, digital twins go beyond being models and can now make predictions, diagnose issues, and recommend actions in real time. AI can analyze the incoming data faster, simulate different scenarios, and predict future outcomes, such as testing changes to a production line before implementing them in the physical environment, identifying potential equipment failures before they occur, or optimizing logistics and supply chains.
For example, NASA’s Jon McBride Software Testing and Research group (JSTAR) creates software-based replicas of spacecraft and mission systems to test flight software, inject faults, and validate system behavior long before hardware is available.
The Department of Energy’s Oak Ridge National Laboratory (ORNL) recently created the digital twin for a water purification project focused on reducing energy consumption and costs. The project paired a digital twin with a physical system so that they would provide constant feedback to each other while operating. Most water treatment plants run at fixed rates and require manual adjustments, but ORNL’s digital twin prompts the pilot plant to alter flows as electricity prices fluctuate during the day. This new model removes the need for time- and computation-consuming simulations by using data-driven models to predict power demand and minimize costs.
In 2025, the Army brought together executives from leading technology and industrial companies for a tabletop exercise focused on advancing key AI goals. This resulted in the Army’s Rapid Implementation of Artificial Intelligence initiative, organized around three main efforts—one of which is creating a digital twin of the service’s industrial base to enable a more efficient, AI-driven supply chain. Many of the service’s depots still rely on outdated, manual processes that limit visibility into parts and maintenance needs. This digital twin effort aims to organize data to create a real-time picture of supply and demand, allowing the Army to improve visibility, reduce bottlenecks, and make faster “make or buy” decisions.
Digital Twins Powering AI
In addition to benefiting from AI, digital twins are advancing their use by allowing agencies to experiment with their applications and implications within digital twin models.
Before an agency spends millions on hardware, launches an AI-powered service, or stands up a new AI workflow, a digital twin environment could be used to identify risks, measure behavior, and validate controls without real data or infrastructure being impacted.
In fact, the National Institute of Standards and Technology (NIST) and the General Services Administration (GSA) are collaborating to improve the USAi evaluation platform. This environment can help agencies evaluate AI systems before deployment, supporting emerging requirements for AI governance, security, and transparency.
The Naval Postgraduate School (NPS) is using digital twins to run batches of what-if tests and letting operators and engineers adjust the same model together. This collaborative approach is foundational to the NPS Artificial Intelligence Task Force, which focuses on accelerating AI readiness through education, research, and development.
To learn more about how digital twins can become a foundational technology for government operations, check out these resources from GovWhitePapers and GovEvents:
- Top 10 Geospatial Government Trends (white paper) – This report explores how agencies are using GeoAI, digital twins, drone mapping, cloud GIS, satellite remote sensing, and interoperable data standards to improve decision-making and operational efficiency.
- Digital Twin Lab (white paper) – NIST has launched a Digital Twin Lab to accelerate innovation in U.S. manufacturing. This lab serves as a testbed for developing standards, prototyping systems, and evaluating enabling technologies like Industrial Internet of Things, robotics, and simulation tools. By demonstrating use cases and fostering collaboration, the lab helps industry stakeholders explore digital twin applications that improve efficiency, quality, and integration across manufacturing.
- Growing Use Cases for the Ever-Evolving Digital Twin (white paper) – Digital twin technology is expanding rapidly, bridging the physical and digital worlds to improve design, operations, and decision-making. By integrating AI, IoT, and analytics, organizations can simulate real-world assets to enhance product quality, predict maintenance needs, and reduce operational risk. Scalable, identity-centric IoT platforms now make it possible to securely connect people, systems, and devices across entire ecosystems.
- Moving AI from Pilot to Production (July 8, 2026; virtual) – This event will examine what is needed to move AI from pilot programs to agency-wide implementation, including the obstacles that must be addressed in order to scale up.
- 14th Annual 930gov (July 28, 2026; Washington, DC) – This event focuses on the intersection of mission-critical objectives and innovative technologies, providing a platform for exploring how emerging technologies can drive enterprise transformation and enhance mission success. Attendees will gain insight into the latest trends in enterprise architecture, records management, cyber security, data management, artificial intelligence, business transformation, and technology integration.
- Global Expeditionary Logistics Symposium (GELS) 2026 (August 4-6, 2026; Newport News, VA) – Marine Corps, Joint Force, industry, academic, and allied leaders address the most pressing challenges in expeditionary logistics and contested sustainment. Sessions will discuss building the data architecture and digital infrastructure required to enable decision-quality visibility, digital twins, and more; examining unmanned and automated distribution and sustainment capabilities of import in contested environments; and applying AI-enabled analytics to forecast readiness, anticipate demand signals, and shift sustainment to a predictive postures.
Search GovWhitePapers and GovEvents to find even more details on the government’s use of digital twins.
