Sophie applied to fifty-two graduate schemes and was rejected from forty-eight of them without interview. First-class Computer Science degree from Edinburgh. Placement year at a fintech. Dissertation on natural language processing. On paper she is exactly the person the graduate pipeline was built for.
Now, the rejections are not the story. Everyone in her cohort has rejections. The story is what she did with them.
Sophie did something most of her cohort did not. She tracked every application in a spreadsheet. And the spreadsheet started talking to her. She noticed “entry-level” roles asking for two to three years of experience, which is a contradiction in terms, and a tell. She saw the pattern.
Then she thought about what the pattern meant. The filter was doing the reading. Her profile was the same shape as a thousand others going through the same sift. The thing being selected for was no longer visible in the application, and nothing in the advice she had been given about how to get a graduate job said anything about that. The plan she had been following since sixth form had stopped being a plan.
I keep meeting versions of this in my advisory work, usually from the other side of the desk, the side deciding not to hire. If a thousand people are chasing the same role and an AI is doing the sifting, it is looking at like for like, making a small decision based on one tiny difference. Graduate schemes that used to take four hundred are taking sixty. The arithmetic does not favour the applicant, and no amount of CV polishing changes the arithmetic. Most of Sophie’s cohort are still checking their inboxes, still doing what the careers advice says, because the careers advice was written for a labour market that has kind of quietly stopped existing.
Sophie got angry, briefly. Then she got strategic. She stopped queueing at the front door. What she actually did, the specific move and why it works, and the honest costs of it, because there are costs, is in Chapter 4. I am not going to spell it out here, partly because the reasoning behind the move matters more than the move itself, and the reasoning takes a chapter.
What I will say is that she is not where she planned to be, and she understood, earlier than most of her cohort, that the plan was based on a labour market that no longer exists. That understanding, arrived at early, is currently worth more than the first-class degree. Which is a strange thing to write, and I checked myself when I wrote it, but I think it holds.
The chapter she comes from is full of people at different rungs of the same ladder. A candidate whose job was cancelled before it was ever posted. A freelancer who cannot bring himself to update his rate card. A team of eight that became five without anyone being fired. None of them would describe what happened to them as displacement. That is exactly what makes it hard to see.
This is from Chapter 4 of The Next Rung, my book on what AI displacement actually looks like from inside. It’s open for pre-order now: