TL;DR: Traditional test automation solves test creation once, then the maintenance cost scales roughly proportionally with the codebase until the suite itself becomes a project. AI-assisted automation targets that maintenance cost specifically: generation tied to real changes, anomaly detection instead of brittle assertions, and coverage that adjusts instead of accumulating. Four components, one clear limit, and a quick way to tell if it's worth it yet.
The problem, stated precisely
A regression suite is cheap to justify when it's new. It's expensive later, not because automation stopped working, but because the maintenance cost scales with the codebase. New features mean new test cases. New test cases mean a longer regression cycle. At some point the suite costs nearly as much to keep green as it saves.
This is not the same problem as "can AI write tests." Test generation alone doesn't touch the maintenance side of the equation. The interesting part is the combination below.
The pattern
