# Employment of 22-25-year-olds in the two most AI-exposed occupation quintiles fell about 11% from November 2022 to June 2026, while the least-exposed quintiles grew about 10%

Page: https://flyvolo.ai/en/changes/ev-20260812-customer-service-representative-3
Date: 2026-08-12 · Stage: Labour impact
Can this record move a task judgement? yes
Occupation: https://flyvolo.ai/en/careers/customer-service-representative

## Scope

Customer service representatives rank 2nd by employment among the highest-exposure quintile in the paper's appendix, sit in its substitution rather than augmentation column, and are one of two occupations singled out for a case study. US private-sector payroll records from ADP covering millions of workers, November 2022 to June 2026. The 11% fall is for 22-25-year-olds in the two most AI-exposed quintiles; the same age group in the three least-exposed quintiles grew about 10%. Experienced workers show no comparable gap, and the authors state they find no evidence of widespread, economy-wide displacement. The findings are descriptive, not causal, and are measured at occupation level, not task level.

## Source

- Stanford Digital Economy Lab — Brynjolfsson, Chandar & Chen, "Canaries in the Coal Mine?" (August 2026) — https://digitaleconomy.stanford.edu/app/uploads/2026/08/Canaries_August2026.pdf (primary source)

## What this means

This occupation sits second by employment among the most AI-exposed in the paper, and in its substitution rather than augmentation column — meaning the usage pattern here replaces tasks rather than speeding a person up. Paired with the paper's finding that declines concentrate exactly where usage substitutes, the entry-level shortfall is not incidental to this job; it is where the mechanism the paper describes would show up first.

## What it does not show yet

The paper does not measure this occupation on its own; it places it in an exposure quintile and reports the quintile. Nor does it say the work disappeared — a role can shrink at the entry end while the remaining work gets harder, which is what a queue of pre-filtered, already-failed conversations looks like. Descriptive, not causal, by the authors' own statement.

## How to verify it yourself

Ask any contact centre you can reach what share of contacts now arrive already having failed with a bot, and what the average handle time is today versus two years ago. If handle time is up while headcount is down, the work did not vanish — it was concentrated.


More: https://flyvolo.ai/llms.txt