How advances in AI and autonomous systems, new tech, and lower costs are shifting global wars towards “precise mass”, or the mass deployment of uncrewed systems
"Militaries are beginning to realize that they don't have to choose between precision and mass; they can have both." https://www.foreignaffairs.com/ ... Shashank Joshi / @shashj : “One report suggests the [Iranian] strike [on Israel] cost about $80 million to launch but $1 billion to defend against. A wealthy country and its allies could afford that sort of expense a few times—but maybe not 20 times, 30 times, or 100 times.” https://www.foreignaffairs.com/ ... Michael C. Horowitz / @mchorowitz : Excited to share my latest - Battles of Precise Mass - in @ForeignAffairs! https://www.foreignaffairs.com/ .... From Ukr to the Middle East to the Indo-Pacific, the intersection of precision and mass is driving a shift in the character of war - mastering it is key to the US staying ahead! Shashank Joshi / @shashj : “Through Replicator, [DoD] has made progress in developing capability in less than a year that would generally take multiple years to complete—leading Hicks to announce that the Defense Department is on track to achieve Replicator's 2025 goals for attritable autonomous systems.” Dan Black / @danwblack : The search for precise mass is also an apt way to explain Russia's approach to sustaining cyber effects in Ukraine (and it's wartime arsenal management strategy more generally). More effort needed to ground cyber conflict research within the “cheap, scalable, attritable” arc
Context & Ripple Effects
This analysis extends a shift already visible in Ukraine, where the war had prompted greater military investment in AI and a NATO startup fund for priority technologies such as AI as militaries stepped up AI investment. The Defense Department's Project Maven had also made AI-enabled target identification a flagship battlefield application, alongside concerns about adversaries corrupting training data AI-assisted target identification.
The importance of “precise mass” is that it joins two objectives often treated as a trade-off: accurate effects and large-scale deployment. It also sharpens an unresolved policy debate over autonomous weapons, for which dozens of countries had supported a total ban calls for a ban on autonomous weapons.
First-order effects
- Military planners gain a stronger rationale to procure and field attritable uncrewed systems at scale, rather than reserving precision effects for a limited number of costly platforms.
- The reported Iran-Israel cost imbalance makes air and missile defense economics more consequential: defenders may have to expend far more per interception than attackers spend to generate repeated threats.
Second-order effects
- Defense programs such as Replicator face pressure to turn “low-cost” autonomy into dependable production, deployment, and command-and-control capacity; prototypes alone do not deliver mass.
- Demand shifts toward the enabling stack around uncrewed systems—AI targeting, communications, sensors, electronic resilience, and training-data security—while defensive systems are judged increasingly on their cost per defended threat.
Third-order effects
- If cheap, networked systems can repeatedly impose disproportionate defensive costs, force planning may move from platform-centric arsenals toward mixes of expendable systems and selective high-end defenses.
- The spread of AI-enabled autonomous capabilities is likely to intensify governance disputes over human control, target-validation reliability, and accountability, rather than resolve them through technical progress alone.
The trend: Warfare is moving toward AI-enabled, lower-cost uncrewed mass that seeks precision effects while putting sustained pressure on the economics of defense.