What happened
The Korea Employment Information Service runs the AI job recommendation service on Worknet, the public jobs portal. Since July 2020 it has compared jobseekers' résumés with the skills that job postings require and recommended postings to them. It made 1,361,159 recommendations in 2024. In an audit report published on 5 January 2026, South Korea's Board of Audit and Inspection examined job recommenders for bias by occupation. The board reports that the service's hit rate is about 78.0%, an F1 score shown as a percentage. The board analyzed the results itself and found that the hit rate was about 80% both for the 10 most recommended of 1,097 occupations and for the rest. A recommender run by the workers' compensation agency varied far more by occupation. In an audit released in April 2022, the board had compared live use with an older rule-based recommender. Jobseekers applied after 9.45% and 12.99% of their views of AI recommendations in two periods, against 15.22% and 18.36% for the older system. The 2026 hit rate measures matching on evaluation data and does not count hires.
Sources
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Audit report, by authors with no tie to the system.
Board of Audit and Inspection of Korea (감사원). 감사보고서 - 인공지능 대비실태 Ⅰ(신뢰성 확보 분야) - [Performance audit report, AI preparedness I: ensuring reliability]. Report dated December 2025, published 5 January 2026. Chapter 3, section 4, printed p. 54 and footnotes 52 and 53.
'AI 일자리 추천서비스'의 평가데이터상 추천직종은 총 1,097개이며 추천 상위 10개 직종 및 그 외 직종 그룹의 추천 적중률 모두 약 80% 수준임
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Audit report, by authors with no tie to the system. Context or contrary evidence.
Board of Audit and Inspection of Korea (감사원). 감사보고서 - 취업알선정보망 구축 및 관리실태 - [Performance audit report, construction and management of the employment placement information network]. Report dated March 2022, released April 2022. Printed pp. 20-24 and [표 13].
새로 개발한 AI 기반 매칭 시스템의 입사지원율 (1차 시행기간 9.45%, 2차 시행기간 12.99%)이 같은 기간 기존의 추천 시스템의 입사지원율 15.22% 및 18.36%에 비해 오히려 각각 5.77%p, 5.37%p 낮은 것으로 확인되었다.
Details
AI system
- Workflow
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The service compared each jobseeker's résumé with the skills that job postings require and recommended postings. A DeepFM machine-learning model trained on past applications scored candidate postings, and the service showed up to 50 of them.
Follow-up
- Conditions for replication
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The evaluation data must span the occupations that the service recommends, and the 2026 data covered 1,097 of them. Matching scores must track whether jobseekers apply, and in 2022 the board found almost no correlation between them.
Entry details
- Sector
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Public employment services (job matching).
- Purpose
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The Korea Employment Information Service built the AI job recommendation service to match jobseekers' résumés with the skills that job postings require and to recommend suitable postings.
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Cite this record
Peter H. Vartanian. (2026). AI job recommendation service scores evenly but drew fewer applicants (AIBD-1011). Artificial Intelligence Benefits Database, edition of 1 November 2026. https://petervartanian.xyz/aibd/records/AIBD-1011.html (archived at https://doi.org/10.7910/DVN/AADSII, version 7.0)