“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.
Ana Garcia Olson on timelines, data and humans in the lead
Olson framed the problem bluntly: long procurement and production timelines are no longer acceptable given current operational demands. Her prescription is not to automate for automation’s sake but to redesign workflows so that "the most effective AI-powered operations are redesigned from the ground up with humans in the lead." That requires secure, real-time data and a cultural shift so leaders and technicians steer systems from the start rather than simply validating outputs at the end.
Amy Bahrani on capacity constraints and the widening gap
"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. Bahrani points to material shortages, space limits and workforce shortfalls as simultaneous pressures. Those pressures intensify when demand surges — for example, stockpile drawdowns tied to the conflict with Iran and materiel support for Ukraine — and when industry consolidation leaves single suppliers holding strategic chokepoints.
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See what we buildDigital DIB: digital twins, cloud infrastructure and simulations
Digital twins, modeling and robotic automation are already widespread across the defense industrial base (DIB), but Accenture's experts argue AI is changing how those tools are used. Designers can now identify and correct flaws in virtual models instead of rebuilding physical prototypes, and once optimal configurations are found they can move more rapidly into real-world testing. As Bahrani put it, "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." That capability depends on secure, cloud-based data infrastructure and a single source of accessible information for distributed teams.
Supply chains, surge demand, and where AI can help
The report identifies a widening gap between demand and delivery driven by three concrete factors:
- Supply chains built for peacetime are buckling under surge demand;
- Military requirements (e.g., autonomy and counter-drone capabilities) are evolving faster than industrial processes can respond;
- Order volumes are exceeding current delivery capacity in every major defense system category.
These pressures are compounded by depletion of stockpiles after expenditures in the conflict with Iran and by large-scale projects such as Golden Dome that require specialized materials and components. Accenture highlights how single suppliers can become bottlenecks — "You might have a bottleneck where there are four applications that all have a dual-use product... but you’re relying on one company or a small set of companies to be able to feed that supply chain," Bahrani said. AI tools, the report argues, can map supply chains, trace component flows, surface alternate suppliers and identify likely points of disruption faster than manual analysis, reducing the risk that a single failure halts production.
What this means for government, industry, and technicians
- Government and procurement leaders: accelerate internal operations into an "Intelligent Enterprise" and coordinate with industry to create a collective "National Enterprise," driving end-to-end data integration and adopting agentic AI across the product lifecycle, as Bahrani recommends.
- Industry and OEMs: invest in secure cloud-based data sharing, reuse digital twins and simulation to shorten design-to-field timelines, and plan capital expenditures that expand manufacturing capacity while diversifying supplier bases to avoid chokepoints.
- Technicians and frontline workers: expect workflows to change. Younger, digitally native recruits will be more effective if given modern, intuitive tools and continuous data access; meanwhile, AI-powered systems that "ingest standard operating procedures, documentation, and blueprints in real time" can surface fixes instantly so a technician does not have to halt a line to find a supervisor, Bahrani said.
The central argument of the report is both practical and procedural: AI can accelerate design, manufacturing and supply-chain resilience, but only if organizations rebuild processes around secure data, human oversight and modern tooling. That dual requirement — faster, AI-driven systems and "humans in the lead" — frames the choice facing the DIB. As Bahrani put it, the goal is collective transformation: "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.'" The question the facts leave open is whether public- and private-sector leaders will move quickly enough to close the gap between demand and delivery before shortages and chokepoints further constrain operational options.
