Having thousands of applicants is only an issue if you give yourself the contrived problem of hiring the best person who sent you a resume. Your true objective is to strike a balance between cost of search and hiring someone from the top N% of potential people. Nobody has ever walked into a grocery store and bemoaned that there's no way they could locate the ripest banana in the building. You pick a number, evaluate that many at random, move on.
I think it galls people that they are likely cutting the best candidate out of the sample, but to be real: you don't have a magic incredibly sensitive, deterministic and bias free hiring method that can reliably pick the single best candidate out of thousands anyways. Any kind of cheapo ai-driven interview step you run is very possibly doing worse things to your sample than just cutting it down to size.
One of the refreshing things about the Amazon/AWS hiring approach was basically this. Did we agree this person can do the job? First one to get to a yes gets an offer. No interviewing all the candidates and stack ranking and trying juggle them to have a plan A and plan B (though people could influence that somewhat through scheduling). First qualified candidate succeeds and everyone gets back to work.
> No interviewing all the candidates and stack ranking and trying juggle them to have a plan A and plan B (though people could influence that somewhat through scheduling).
A lot of places I've worked end up coming up with a prioritised list of who they think they want to hire as candidates are going through the pipeline. The first preference for various reasons might not be the first to finish the interview process. What typically happens is if a strong candidate finishes the process first they'll get a "our team need time to discuss their feedback, we'll get back to you in 10 days" type of answer. The X days is often less to do with the team getting together to compare notes and more to do with when another candidate is expected to finish their interview. At which point the two candidates can be compared to each other and a decision made. There's also the expectation that if _we_ rank someone highly in our pipeline they are probably high in someone else's and so we might just lose them to a better offer. So having a plan b to send an offer to is useful.
At Amazon there wasn't meant to be that kind of candidate comparisons/ranking. If you're first through and pass you get an offer. But... if a team felt strongly about a specific person it was entirely feasible to prioritise them by giving them first option on potential interview dates, and offering later dates to other people. Thereby increasing the chances the preferred candidate was the first one to successfully complete the process.
I think it galls people that they are likely cutting the best candidate out of the sample, but to be real: you don't have a magic incredibly sensitive, deterministic and bias free hiring method that can reliably pick the single best candidate out of thousands anyways. Any kind of cheapo ai-driven interview step you run is very possibly doing worse things to your sample than just cutting it down to size.