The Pentagon rehearses a faster kill chain, and calls it a drill

The Pentagon has wrapped up the latest round of Scarlet Dragon, a joint exercise with defence contractors that has run in various forms since 2020 and is built around one question: how much faster can artificial intelligence make the process of finding a target, deciding on it, and striking it. The answer, by the organisers’ own account, was faster than the current human-paced system allows, with AI tools used to identify targets and share data across units in something closer to real time than the layered approval chains that normally govern lethal force.

Exercises are, by design, provisional. Nothing tested in a simulated environment automatically becomes policy, and the Pentagon has been careful for years to describe its AI targeting work as decision support rather than autonomous killing. But the gap between a capability that exists and a capability that gets used tends to close under pressure, and the entire point of accelerating the kill chain is to remove the delay that a cautious human introduces into it.

The exercise did not prove AI can make war-fighting decisions. It proved the infrastructure for letting it do so is already being built and tested at scale.

What makes this notable is not the technology itself, which has been in development for years, but the fact that it keeps being rehearsed in the same venue. A recurring joint military-industry exercise is where doctrine gets tested and refined before it is written down, and the contractors involved have every commercial incentive to make the case that speed is safety. The slower version of that argument, made by arms-control advocates and some inside the Pentagon itself, is that a faster kill chain is only a virtue until an adversary’s faster kill chain starts making mistakes nobody has time to catch.