The U.S. Army is committed to building a “Digital Twin” network system, aiming to enhance network warfare, defense, and testing capabilities through the use of artificial intelligence. This will profoundly change the future forms of warfare and combat readiness.
On August 20, 2026, at the Military Network and Information Technology Conference (TechNet Augusta 2026) hosted by the Armed Forces Communications and Electronics Association (AFCEA) in Georgia, Denise McPhail, the commander of the U.S. Army Network Enterprise Technology Command (NETCOM), expressed the Army’s urgent need for the industry to construct a comprehensive simulation system covering the entire “Department of Defense Information Network – Army portion” (DoDIN-A), also known as a “Digital Twin” network environment.
She pointed out that this system will allow the Army to test artificial intelligence, train network operators and defense forces, analyze network vulnerabilities and resilience in a virtual environment closely resembling a real network. This enables repeated testing and simulated exercises without directly interfering with the real military network.
“Digital Twin” can be understood as a companion simulation system that establishes a dynamic model corresponding to real physical systems, networks, equipment, or processes in a digital space. It can be continuously updated in real-time with data generated by the real system, maintaining a certain level of dynamic synchronization between the simulation system and the real physical world. This allows for testing, training, vulnerability analysis, and risk assessment without directly interrupting the operation of real-world systems.
The core features of “Digital Twin” lie in “bi-directional real-time data synchronization” and “full lifecycle mapping”. This technology, originally conceived by NASA during the Apollo program, was used to monitor the real-time status of spacecraft on the ground.
McPhail admitted that this is no easy task for the industry. She described it as a “big ask” that challenges the physical limits of current information engineering and emphasized the need to “start small and expand gradually.”
A complete digital twin requires a large number of Internet of Things (IoT) sensors deployed on physical equipment and cloud servers. These sensors continuously collect various physical variables such as weather, geography, vibrations, weapons, and logistics systems, transmitting this real-time data to cloud servers via the network. A dynamic model that is fully synchronized with the real-world state is then reconstructed in the virtual space.
The virtual model reflects real changes in the physical world in real-time. Engineers can adjust parameters on the virtual model to observe or test trends in situational changes. This is a digital simulation technology based on massive computing power, big data analysis, and real-time communication.
In recent years, this technology has mostly been applied to establish digital models of specific physical systems, such as aerodynamic models of fighter jets, integrated simulations of multiple systems, logistics supply chain network simulations, and even virtual wounded soldiers used for medical training. Its comprehensive application across the entire Army combat system is unprecedented.
It allows military personnel to conduct realistic stress tests in a virtual environment that may be extremely dangerous in the real world, try different hardware design solutions, avoid costly losses of real operational resources, and analyze potential risks and performance bottlenecks. Commanders can visually see how data centers, tactical nodes, and satellite communication links interweave, enabling them to understand the state of the entire command and control system and identify vulnerabilities.
The intervention of artificial intelligence and machine learning allows any abnormal data flow in the sea of data to be identified in a very short time. This behavior-based dynamic analysis capability surpasses what traditional combat systems can achieve. However, concerns about the deep involvement of artificial intelligence in the military domain persist due to the involvement of lethal weapons.
McPhail pointed out that digital twin models can safely leverage artificial intelligence, allowing algorithms to engage in countless offensive and defensive exercises to deeply understand the system’s vulnerabilities, gaps, and nodes with sufficient defensive resilience. This secure, lossless trial-and-error mechanism can help accelerate the maturity and stability of combat systems involving artificial intelligence.
In addition to serving as a testbed for artificial intelligence, the value of “Digital Twin” in U.S. Army training cannot be underestimated.
Lonnie Dunbar III, an official from the U.S. Army Space and Missile Defense Command, emphasized that “Digital Twin” technology ensures that soldiers can undergo highly realistic training using threat models, achieving training effects “similar to actual combat.” Soldiers can enter a virtual space identical to a real combat environment, observe soldiers’ real-time responses and resource coordination in large-scale network attacks, and learn how to maintain operational command in situations where parts of the network are paralyzed. This high-fidelity training based on real network architecture will fundamentally change traditional U.S. Army training methods.
“Digital Twin” is also a crucial tool for maintaining system stability.
McPhail pointed out that the military not only needs to identify what went wrong but also what did not go wrong to avoid unnecessary losses. This predictive testing mechanism will significantly enhance the reliability of military systems and infrastructure.
Securing and protecting digital twins poses another challenging issue. The twin contains detailed information on U.S. military network architecture, defense mechanisms, operational logic, and nearly all potential system vulnerabilities. Once infiltrated, the U.S. Army network would be completely compromised. The Army demands that defense contractors integrate zero trust and top-level encryption technologies, including Homomorphic Encryption and Quantum Key Distribution (QKD), into the system. Only an absolutely secure isolated environment can ensure the actual strategic value of the system.
“Digital Twin” will expedite the decision-making process and combat tempo. Modern warfare theory believes that the key to determining battlefield outcomes lies in who can complete the “Observe, Orient, Decide, Act” (OODA) loop faster. Traditional defense systems typically react only when an attack occurs, inevitably resulting in decision-making lagging behind the opponent’s initial actions.
“Digital Twin” will break this passive cycle. By endlessly simulating various attack scenarios in a virtual environment, the U.S. military can predict potential confrontations and devise corresponding solutions. Whenever similar signs of an attack appear, the system can instantly invoke defense solutions that have been repeatedly verified in the twin environment, compressing real-world response times from hours or minutes to an order of magnitude faster. The implications of this for future warfare are self-evident.
Moreover, the “Joint All-Domain Command and Control” (JADC2) and “Digital Twin” initiatives being vigorously pursued by the Pentagon are closely interconnected. The essence of “Digital Twin” technology is to ensure the resilience and reliability of networks in extreme conditions. The fully network-operated JADC2 undeniably benefits from the contributions of “Digital Twin,” making it more robust and efficient.
The U.S. Army’s drive to establish “Digital Twin” reflects its strategic awakening to information domain dominance. Despite facing multiple challenges such as real-time data synchronization, system security protection, and computing power bottlenecks, the U.S. Army remains determined to “start small and expand gradually.”
This demonstrates that the U.S. Army has recognized the undeniable value of this digital battlefield in maintaining a competitive edge in future warfare scenarios.