Tractors did not cause this phenomenon because jevons paradox kicked in and induced demand rendered the problem moot, or demand eventually exceeded what mere tractors were capable of doing for agricultural productivity.
The same can probably be said for contemporary AI, but it's tough to tell right now. There's some scant indications we've scaled LLMs as far as they can go without another fundamental discovery similar to the attention paper in 2017. GPT-5 was underwhelming, and each new Claude Opus is an incremental improvement at best, still unable to execute an entire business idea from a single prompt. If we don't continue to see large leaps in capability like circa 2021-2022, then it can be argued jevons paradox will kick in here and at best LLMs will be a productivity multiplier for already experienced white collar workers - not a replacement for them.
All this being said, technological unemployment is not something that will be sudden or obvious, nor will human innovation always stay under jevons paradox, and I think policymakers need to seriously entertain taboo solutions for it sooner or later. Such as a WPA-style infrastructure project or basic income.