Since the late 1950s, Mutual Assured Destruction (MAD) has served as a limiting factor on great-power conflict. The doctrine holds that, if two opposing nations have nuclear weapons that can survive one another’s initial strike, then the near-certainty of devastating retaliation will deter each side from launching a large-scale nuclear attack. Despite this logic, military planners have long considered the possibility of a counterforce nuclear attack, where a superpower uses nuclear weapons to cripple the nuclear capabilities of its enemy. If such an attack were executed preemptively, as a so-called “first strike,” it could both start and end a great-power conflict in a matter of hours: without retaliatory capacity, the defender would be at the mercy of the aggressor’s remaining nuclear weapons and forced to surrender.
The reason this does not happen is that a truly successful counterforce strike is nearly impossible to pull off: a would-be attacker doesn’t know the locations of all opposing missile launchers and submarines, nor does it have missiles with sufficient precision and speed to destroy opposing missile silos before they could launch retaliatory nuclear warheads. Thus, if provoked by a first strike, the opposing side would likely be able to launch a large-scale nuclear response, and the attacker, unable to counter all enemy missiles, could face devastating losses. The result of a preemptive counterforce strike, in other words, would be mutual assured destruction.
AI could change this dynamic. By the mid-2030s, AI-assisted research and development could reduce the cost required to develop and manufacture military hardware by an order of magnitude. Such lower costs could enable a nation with an AI lead to quickly and cheaply build military infrastructure projects, making nuclear counterforce strikes a realistic possibility. Nations with weaker AI capabilities would struggle to quickly build the countermeasures needed to retain a credible nuclear deterrent.
