The US Army is deploying artificial intelligence and machine learning to revolutionize its combat logistics through the Next Generation Command and Control system (NGC2). This advanced software platform is transforming how the military predicts ammunition, fuel, and supply needs by simulating enemy attack scenarios in real-time.
Currently being tested at Fort Carson, Colorado, the NGC2 system represents a fundamental shift from reactive to predictive logistics. The platform integrates data from weapons, vehicles, sensors, and multiple data streams to create comprehensive operational scenarios. James Craven, NGC2 program director at Anduril, explained that the system allows operational plans to be “quickly shaped off of logistics data and commander guidance and then stress-tested against simulated enemy actions.”
The AI-powered system analyzes magazine depth, consumption rates, and equipment status in real-time, enabling planners to examine multiple combat scenarios and predict how demand for critical supplies might change based on adversary actions. This capability addresses a critical weakness in the Army’s traditional supply chain, where sustainment units often respond only after shortages appear—a problem that Lt. Gen. Michelle Donahue recently warned can leave front-line units dangerously undersupplied.
Beyond ammunition tracking, the NGC2 platform uses machine learning algorithms to predict maintenance needs and potential equipment failures before they occur. This predictive maintenance capability allows crews to intervene earlier, reducing operational disruptions and keeping combat systems operational.
The development process itself reflects a Silicon Valley-style approach to military technology. Anduril and other industry partners are working with the Army to incorporate soldier feedback rapidly, sometimes implementing changes overnight or within days—a dramatic departure from traditional defense procurement that could take months or years. Tom Keane, Anduril’s senior vice president, noted that new capabilities are provided “at least weekly, sometimes daily or hourly.”
The long-term vision extends beyond individual units, with plans to make the system accessible across the entire service and to key partners, allowing suppliers to estimate future demand earlier in the logistics chain. This represents a fundamental transformation in military-industrial collaboration, emphasizing agile, adaptive development and software-based solutions over traditional hardware-focused approaches.
Key Quotes
it’s no longer, ‘Hey, operations, what is your next 24-hour plan or what’s your next 48-hour plan?’
James Craven, NGC2 program director at Anduril, explained how the AI-powered system is changing military planning from reactive short-term cycles to proactive, data-driven operational planning that can adapt to multiple scenarios simultaneously.
we can see magazine depth, consumption rates, and how those change over time, in real time, and then that data can be analyzed thanks to artificial intelligence and machine learning to estimate the downstream effects on operations
Craven described the core AI capabilities of NGC2, highlighting how machine learning algorithms process real-time combat data to predict future supply needs and operational impacts—a capability that could prevent critical shortages in combat situations.
new or upgraded capabilities are provided at least weekly, sometimes daily or hourly, depending on what’s being worked on
Tom Keane, Anduril’s senior vice president, emphasized the unprecedented speed of development enabled by the software-based approach, contrasting sharply with traditional defense procurement timelines that often span years.
Our Take
The NGC2 system represents a watershed moment in military AI adoption, moving beyond experimental applications to mission-critical logistics operations. What’s particularly significant is the integration of AI into the operational planning cycle itself, rather than treating it as a separate analytical tool. This embedded approach suggests maturity in military AI applications that could accelerate adoption across other government agencies.
The partnership model between the Army and companies like Anduril is equally noteworthy, demonstrating that defense organizations can successfully adopt agile development methodologies traditionally associated with commercial tech companies. This could reshape the defense industrial base, favoring software-focused companies capable of rapid iteration over traditional hardware contractors. The predictive maintenance and supply forecasting capabilities being developed have immediate commercial applications, potentially creating a technology transfer pathway from military to civilian logistics operations.
Why This Matters
This development represents a critical intersection of AI technology and national defense, demonstrating how machine learning is transforming military operations at their most fundamental level. The shift from reactive to predictive logistics could provide decisive advantages in future conflicts, where supply chain efficiency often determines battlefield outcomes.
The NGC2 system exemplifies broader trends in AI adoption across defense and enterprise sectors—using real-time data analysis and predictive algorithms to optimize complex operations. The Army’s embrace of rapid, iterative development with industry partners like Anduril signals a fundamental change in how government agencies approach technology procurement and implementation.
For the AI industry, this represents significant opportunities in defense contracting and enterprise logistics applications. The techniques being developed for military supply chain prediction have clear applications in commercial sectors facing similar challenges in inventory management, predictive maintenance, and demand forecasting. As AI proves its value in high-stakes military environments, adoption across other industries is likely to accelerate.
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Source: https://www.businessinsider.com/new-us-army-software-predicts-ammo-supply-needs-enemy-actions-2026-2