The defense industrial base is facing pressure from several directions at once. Stockpiles are shrinking as munitions are consumed in the conflict with Iran, major programs such as Golden Dome require specialized materials and complex components, and persistent supply-chain shortages threaten to slow every effort.
“The reality we’re facing is that the traditional way we build military platforms – where it takes years, sometimes a decade, to move a system from a whiteboard to operational deployment – is a strategic liability,” said Ana Garcia Olson, Managing Director, Navy & Marine Corps Business Lead, Accenture Federal Services.
To accelerate design, development and manufacturing, the defense industrial base is evaluating new tools. Artificial intelligence stands out for its potential to streamline workflows, speed up processes and analyze vast volumes of data to support better decisions.
“When you look at the immediate constraints, it almost always comes down to capacity,” said Amy Bahrani, Managing Director, AI and Data, Defense Industrial Base Lead, Accenture Federal Services. “It’s the material constraints, space constraints, and workforce shortages putting pressure on the system from every angle. To break through that pressure, we must stop treating the DIB as a reactive or even passive supply chain function.”
A more connected defense industrial base
Digital twins, advanced modeling and robotic automation are already widely used across the defense industrial base. What has changed is the ability of AI to accelerate these technologies, shorten design cycles and improve manufacturing.
Designers and engineers can use virtual environments to detect design flaws, test alternatives and make corrections before committing resources to physical prototypes. Once an optimal configuration is identified, it can be produced and evaluated in the real world.
“When you can securely share cross-domain data and run high-performance simulations, you unlock the ability to field advanced military technology at commercial speed and industrial scale,” said Bahrani. “That is how you build a resilient ecosystem where industry partners can see their innovations reaching the frontline faster.”
Implementing this approach requires secure, cloud-based data infrastructure that enables information to be shared and distributed effectively. Data has limited value if teams cannot access it, so engineers, manufacturers and other project participants must be able to work from the same reliable source of information.
People remain essential to these processes. AI can reduce routine workloads, but humans must still review the results, assess feasibility and make final decisions. Because AI models depend on high-quality data, personnel should validate information throughout the workflow rather than at only the final stage.
“It’s not enough to drop information into data lakes or insert a human into a legacy business process at discrete points,” said Olson. “The most effective AI-powered operations are redesigned from the ground up with humans in the lead. You need real-time data to give leaders decision advantage, but humans must be positioned from the start to steer the system, not just validate a machine’s work.”
Strengthening the supply chain
A supply chain is only as resilient as its most vulnerable link—a weakness that has become increasingly apparent in recent years. Shortages of rare earth minerals and computer chips, workforce gaps and disruptions such as the ongoing struggle to access the Strait of Hormuz can all expose serious fragilities.
Increased materiel support for Ukraine and munitions consumption in Iran have placed additional strain on supply chains. Meeting present and future requirements will demand rapid expansion not only of manufacturing capacity, but also of the sourcing networks needed for components and materials used in systems such as air and missile defense interceptors. Component shortages and rising costs add further complexity, while expanding capacity requires substantial capital investment.
In a recent Accenture report, the company identified three primary factors driving the growing gap between demand and delivery:
- Supply chains designed for peacetime are struggling to meet surge requirements;
- Military needs, including autonomy and counter-drone capabilities, are advancing faster than industrial systems can adapt;
- Order volumes now exceed available delivery capacity across every major defense system category.
These constraints can delay production, while supplier consolidation and the arrival of new defense competitors are adding further pressure, Bahrani said.
“You might have a bottleneck where there are four applications that all have a dual-use product, and it might be for applications across four different OEMs,” she said. “But you’re relying on one company or a small set of companies to be able to feed that supply chain, so that can be extremely hard.”
AI can also reinforce supply-chain resilience. These tools can map networks, trace materials and components, flag likely bottlenecks and identify alternative suppliers. Faster detection of potential disruptions would allow defense-industry companies to prevent or limit their impact before production is halted.
The continuing role of people
AI is a powerful capability, but it cannot perform every task—and it should not be expected to. People will continue to lead defense-industrial operations at every stage, although the way they work and the skills they need will evolve.
Digital fluency is becoming essential. Companies may need to retrain workers or rethink how they prepare people for design and manufacturing roles. As AI assumes a larger role, that preparation will have to change to keep pace.
In some organizations, technology adoption may need to reflect employees’ existing digital skills rather than requiring workers to conform entirely to outdated systems.
“The younger generation entering the workforce grew up in a real-time data environment,” said Olson. “They are incredibly sophisticated with all things digital. If they step onto a submarine or a shipyard floor and find themselves cut off from basic data access, they are underutilized. We must give them the intuitive, modern tools that match their aptitudes, so they are empowered to solve problems on the fly.”
New employees have typically used tablets and smartphones throughout their personal lives and education, which can shorten the learning curve in a manufacturing or design setting. To benefit from that familiarity, companies should provide digital tools that improve productivity instead of requiring traditional training or paper-based documentation.
“If a technician encounters an error code they’ve never seen on an assembly line, they shouldn’t have to halt production or track down a supervisor,” said Bahrani. “We are deploying AI-powered systems that ingest standard operating procedures, documentation, and blueprints in real time. The technician can ask a question, get the exact fix surfaced instantly, and keep the line moving.”
The broader challenge
The defense industrial base has reached a critical juncture. Demand is shifting rapidly, emerging technologies are challenging established processes and new competitors are entering the market. To respond effectively, companies must adopt tools such as AI that can make operations faster, more agile and more efficient. That capability will be vital to ensuring warfighters have the equipment they need now and as the security environment continues to change.
“We need both government and industry to accelerate their own internal operations into an ‘Intelligent Enterprise’ so they can collectively support a true ‘National Enterprise,’” said Bahrani. “That means driving end-to-end data integration with agentic AI across the entire product lifecycle – from initial ideation and design through engineering, manufacturing, and field service.”