Rationing & Friction
Forms, queues, and deadlines take effort, and that effort has been holding demand down. No one designed them to ration a service; they do it anyway. An AI agent removes most of the effort. Demand is then limited only by what agents can produce, and capacity goes to whoever can submit the most rather than whoever needs it most.
An agency can answer the volume with agents of its own, triaging, verifying, and assessing faster than before. Faster handling raises throughput without settling who the capacity is for. Rationing that no one decided and no one had to defend now has to be chosen and stated. A stated limit is one the public can contest; an undesigned one was never available to argue with.
Policy challenge
Friction (the form, the queue, the deadline) has long rationed government services without anyone designing it to. Because that rationing was never made explicit, its two functions were never separated: the friction that only excludes people entitled to help, and the friction that meters demand or signals genuine need.
As agents make completing any process trivial, that undesigned equilibrium collapses, and policymakers are left to decide deliberately what was previously settled by inertia.
Design challenge
Separate the friction that excludes people who are entitled to help from the friction that rations scarce public sector capacity.
Design limits an agent cannot bypass.
Show the difference between a real rise in need and gaming or overload.
Keep a path open for people who are harder to verify, so new limits don't shut them out.