Europe Pushes AI to the Battlefield Edge as Defense Spending Surges
Leonardo DRS executive outlines how networked radars, vehicle-resident AI, and battle management systems are reshaping European military modernization.
Europe's defense inflection point
European defense spending is climbing sharply after years of hovering near NATO's two-percent GDP threshold, driven by geopolitical pressure and a transformed threat landscape. Bill Guyan, Senior Vice President at Leonardo DRS, told Breaking Defense that while some U.S. Army programs face budget constraints, European nations are pouring resources into air and missile defense, counter-drone systems, and next-generation command and control.
The challenge: many European militaries lack the industrial capacity to absorb their enlarged budgets quickly, and legacy systems need urgent modernization. The result is a continent racing to field capabilities that can counter threats ranging from hypersonic missiles to $500 quadcopters.
Battle management becomes essential infrastructure
Battle management systems—once a luxury that allowed forces to share GPS locations and text messages—have become foundational. Modern systems enable graphic overlays, orders distribution, and maintenance of a common operational picture (COP) across dispersed units.
With robotic and unmanned systems proliferating on European battlefields, that shared awareness is no longer optional. "The ability to have the command and control that battle management systems provide is even more imperative," Guyan said. When sensors detect incoming drones, battle management networks instantly alert every vehicle and soldier in the threat zone.
Why mesh radar beats exquisite systems
Traditional integrated air-and-missile-defense relied on expensive, fixed-site radars—exactly the kind adversaries target first. Iran's strikes on billion-dollar U.S. radar installations using inexpensive drones proved the vulnerability of centralized architectures.
Guyan argues for a different approach: networked constellations of mobile, lower-cost radars that provide overlapping coverage. "The quantity of those radars provides a quality unto itself because it provides built-in resiliency," he explained. When exquisite sensors are destroyed or unavailable, these distributed systems continue feeding the common operating picture.
Leonardo DRS has deployed such networks in Ukraine and Israel, where they fill gaps and provide redundancy against systems designed to defeat high-value targets. No single radar type can address every threat—from fast-movers to slow drones—so layered, integrated detection becomes the standard.
Why it matters
The shift from centralized, cloud-dependent AI to edge computing resident in tanks and fighting vehicles represents a fundamental change in how militaries will operate under contested communications. If networks fail—and adversaries will ensure they do—forces need onboard intelligence to identify targets, prioritize threats, and coordinate fires without waiting for data center processing.
AI moves to the platform
The U.S. Army's Next Generation C2 experiments demonstrate AI's potential on the battlefield, but current approaches depend on uninterrupted networks and cloud processing. That's a vulnerability.
Leonardo DRS is embedding AI-enabled computers directly into vehicles through its SAGEcore software architecture. These systems integrate data from night-vision sensors, active protection radars, and GPS to give commanders real-time situational awareness—even when networks are jammed.
"By moving tactical computing that is AI-enabled to the edge—in other words, putting it inside of the tanks, the infantry fighting vehicles, the unmanned platforms—you can start to enable AI-based operations at the very edge," Guyan said.
Edge AI can automatically identify and prioritize targets, slew weapons toward threats, and coordinate fire distribution among nearby vehicles to prevent multiple platforms from engaging the same target. When networks function, these vehicle-resident systems become sensors feeding the larger picture. When communications fail, commanders retain decision advantage.
The approach reduces cognitive load and enables faster targeting decisions—critical when facing massed drone attacks or coordinated armor.
These details were first reported by Breaking Defense in coverage from Eurosatory 2026.
This is an original analysis by the Omega editorial team. Source reporting: AI Watch.
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