Beyond Targeting

Center for Security and Emerging Technology  |  Igor Mikolic-Torreira, Emelia Probasco

The United States military is expanding its deployment of artificial intelligence-enabled decision support systems to accelerate operational planning and targeting processes beyond traditional fires. By integrating tools like the Maven Smart System, combatant commands aim to replicate the massive efficiency gains demonstrated during Operation Epic Fury, where small teams replaced thousands of manual planners.

Historically, complex workflows such as the Joint Air Tasking Cycle have relied on rigid, 72-hour deliberate planning timelines due to the difficulty of manually processing disparate data streams. Transitioning these legacy processes to automated platforms requires overcoming severe data accessibility bottlenecks, as critical logistics and ammunition resupply information remains trapped in unstructured formats across individual units. To resolve these friction points, the Chief Digital and Artificial Intelligence Office is leveraging authority from a January 9, 2026, secretarial memorandum to standardize data flows. Deploying these capabilities directly to active command centers will ultimately foster a specialized user base capable of refining algorithmic warfare tools.

Comment

Compressing the Joint Air Tasking Cycle from 72 hours to near-real-time operations fundamentally challenges established Western joint air doctrine. This algorithmic compression demands a transition from centralised, hierarchical air operations centres to highly distributed execution nodes. Without updated rules of engagement, rapid algorithmic recommendations within the Joint Air Tasking Cycle risk outpacing human cognitive capacity during high-intensity peer conflicts. Consequently, the traditional doctrinal distinction between deliberate and dynamic targeting phases in air warfare becomes obsolete.

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