The changing nature of modern warfare, marked by emerging and asynchronous threats, constantly reminds the defense industry of the risks of standing still. Falling behind can be catastrophic.
Pressure flows all the way from the battlefield to the factory floor, where new capabilities must be envisioned, tested, developed, and produced at a rapid pace. Program managers and acquisition leaders are demanding solutions that are better, faster, and less expensive.
Against this backdrop comes a technology with the potential to reshape defense manufacturing: digital twins.
When paired with artificial intelligence (AI), digital twins enable manufacturers and program managers to collaborate on digital representations of the end product and the processes that develop it.
But these go far beyond static CAD drawings. Digital twins are continuously updated as they receive real-time data from design, production, and sustainment systems. It’s like the metaverse meeting a real-world application, with consequences measured not in clicks or likes, but rather in readiness and mission assurance.
The data flowing into digital twins enables program managers to see how parts and systems will perform long before the first unit rolls off the line. They permit risk-free testing of technology and concepts, helping to uncover flaws earlier and allowing for corrections without having to start over.
Perhaps most significantly, digital twins are poised to re-engineer defense manufacturing in a way that benefits the entire DoD enterprise, freeing people and resources to support other aspects of modernization and defense readiness.
The emergence of digital twins reflects a convergence of trends: ever-improving analytics, advances in simulation techniques and interoperability protocols, integration with CAD systems, and the proliferation of inexpensive, connected sensors. AI accelerates adoption by bringing predictive power and real-time optimization into the manufacturing process.
By enabling risk-free, lower-cost iteration at multiple stages, digital twins speed decision-making and shorten the path to new capabilities. DoD program managers, contractors, and engineers can validate configurations, detect flaws, and optimize performance without committing time and resources to costly prototypes or tooling changes.
For a cost-sensitive department ultimately accountable to lawmakers and taxpayers, this is no small benefit. What once required physical infrastructure can now be virtualized, lowering expense and reducing waste.
Industry studies already forecast faster development cycles and improved products, including in defense. McKinsey & Company reports that organizations adopting digital twins are seeing 20–50% reductions in development lead times. Defense and Munitions notes that investment in digital twins increased by 40% in 2022, and most organizations now incorporate them into long-term roadmaps for enhanced efficiency, sustainability, and readiness. A CapGemini study also shows aerospace and defense increasingly “turning to digital twin technology to advance their digital transformation journeys, achieve digital continuity, and add intelligence to their operations.” Nearly three-quarters of respondents reported that digital twins are included on their product roadmaps.
The largest defense contractors are leading the way. Lockheed Martin, for instance, has developed a “digital twin maturity model” that spans from prototyping to a fully integrated common operating picture. Its goal is to promote standardization across the defense ecosystem. As the company writes, “we cannot go it alone.”
Digital twins extend far beyond static models. Their real value comes from AI-enabled predictive analytics, which interpret streaming data to forecast how design changes or production adjustments will perform at scale. This transforms the virtual model into a living testbed where outcomes can be evaluated before committing resources on the shop floor—an essential advantage when production delays can cascade into mission risk.
Within the factory, managers can simulate stress points like bottlenecks, unplanned downtime, or cascading line failures. By anticipating where throughput will stall, they can intervene before production slips jeopardize delivery schedules tied to operational requirements. Real-time visibility at the system and component levels creates a factory-wide common operating picture that strengthens decision-making and shortens response cycles.
The reach of a digital twin does not end at the plant walls. Defense suppliers linked into the model gain visibility into schedules and requirements, improving the precision of their deliveries and reducing variability in upstream inputs. Program managers and production teams benefit from forward-looking insight that surfaces anomalies before they erode schedule, quality, or readiness. These capabilities directly support fleet availability and sustainment.
Feeding live production data into the twin reduces quality escapes and scrap, with efficiency gains cascading into logistics and maintenance pipelines. The resilience of the defense industrial base is strengthened by ensuring that equipment, parts, and sustainment resources are ready when warfighters need them.
When disruptions occur—whether due to material shortages, maintenance delays, or equipment failures—the digital twin can propose optimized reconfiguration plans in real time. A study from Cornell University found that this approach recovered up to 63% of lost throughput in virtual manufacturing tests, running more than 400 times faster than physical trial-and-error methods.
By reducing waste and accelerating throughput, digital twins protect schedules and readiness, creating budgetary and operational headroom that can be redirected to other mission-critical priorities across the Department.
Beyond immediate gains, digital twins create a cascading effect. Efficiencies on the factory floor translate into time and resources that can be reinvested across the enterprise, enabling deployed forces and senior leaders alike to focus on strategic objectives rather than firefighting operational or acquisition bottlenecks.
Across government—and particularly in defense and intelligence—digital twin technology provides an “innovation playground” where systems and processes evolve continuously through adaptive learning, rather than being constrained by static standards. This iterative approach naturally drives momentum toward open systems and interoperability. Suppliers and manufacturers must align to common standards to collaborate effectively, breaking down friction in acquisition and production and improving overall mission readiness.
As software engineer Yun Zhou notes in Military Embedded Systems, digital twins lay a strong foundation for network modernization, enabling the Department to develop with an end-state in mind rather than a product-by-product approach. They provide capabilities to manage and modernize complex networks efficiently amid data-transport challenges, siloed departments, and limited joint interoperability.
The bottom line is that digital twins are a future-oriented capability that positions the DoD to stay ahead of tomorrow’s challenges.
Digital twins are no longer just a promising concept; they’re proving to be a critical tool for efficiency, agility, and precision across defense manufacturing and the broader business world. Emerging from the Internet of Things, they may be the next big development to help organizations maintain a competitive edge.
For the DoD, digital twins accelerate decision-making, reduce waste, and strengthen readiness, offering a future-ready approach to modernization that matches the pace of today’s threats.
As the defense ecosystem continues to evolve, the organizations that harness digital twin technology will be best positioned to deliver mission success—not only on the factory floor but also across the entire enterprise.
Digital twins and AI bring real-time foresight and control into defense manufacturing. Whether building new systems or sustaining legacy platforms, these technologies empower DoD leaders to reduce cost, mitigate risk, and ensure production resilience at scale. Contact us for help with the strategic integration of advanced technologies and methods to streamline and optimize the development, maintenance, and operation of systems and infrastructures.