The Spatial Characteristics of AI Job Demand Using Online Job Postings

doi:10.25202/JAKG.15.1.10

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2026 Vol.15, Issue 1 Preview Page Next Page

Research Article

The Spatial Characteristics of AI Job Demand Using Online Job Postings 온라인 채용공고 정보를 활용한 AI 직무 채용 수요의 공간적 분포 특성: 채윤식¹ · 류수민^2†
Yoonsik Chae¹ · Sumin Ryu^2†; ¹공동1저자, 경북연구원 경제산업연구실 부연구위원
²공동1저자, 부산과학기술고등교육진흥원 정책연구본부 연구원

¹Associate Research Fellow, Economic & Industry Research office, Gyeongbuk Development Institute
²Researcher, Policy Research Division, Busan Institute of Science & Technology and higher Education Promotion

31 March 2026. pp. 155~168

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Abstract

This study analyzes the functional composition and spatial distribution of AI job demand in South Korea based on job-posting data from major online job portals. The results reveal a multi-layered AI job structure spanning model development, data/platform and software development, embedded and system roles, and infrastructure functions. Spatially, AI job demand is markedly concentrated in the Seoul Capital Area, particularly along the Gangnam (Seoul)–Seongnam (Gyeonggi) axis, with pronounced inter-regional disparities and statistically significant spatial clustering. Meanwhile, R&D as well as embedded and system-related functions show partial potential for dispersion outside the capital region. By identifying functional differentiation and spatial distribution at the job level, this study provides empirical insights into regional labor market dynamics and offers policy implications for place-based talent development.

Keywords

AI talent

Job demand

Job posting

Topic modeling

LDA

본 연구는 민간 채용 플랫폼의 온라인 채용공고 데이터를 활용하여 국내 AI 직무 채용 수요의 기능적 구성과 공간적 분포를 분석하였다. 분석 결과, AI 직무수요는 모델 개발, 데이터·플랫폼 및 소프트웨어 개발, 임베디드·시스템, 인프라 운영·통합 등으로 분화되는 다층적 구조를 보였다. 모든 직무수요에서 서울 강남-경기 성남 축을 중심으로 수도권 편중이 뚜렷하게 나타났으며, 지역 간 불균등성과 공간적 군집성이 함께 확인되었다. 반면 연구개발 및 임베디드·시스템 관련 직무수요에서는 일부 비수도권 지역으로의 분산 가능성도 관찰되었다. 본 연구는 채용공고 빅데이터를 활용해 AI 직무수요의 기능적 분화와 공간적 분포 특성을 직무 단위에서 분석함으로써, 지역 노동시장 분석과 지역 맞춤형 인재 정책 설계를 위한 실증적 근거를 제공한다.

키워드

AI 인력

직무수요

채용공고

토픽모델링

LDA

References

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박소현·이금숙, 2016, “한국 직업구조의 변화와 고용분포의 공간적 특성,” 대한지리학회지, 51(3), 401-420.
박정일, 2023, “채용공고 빅데이터를 활용한 괜찮은 일자리 공급의 산업 및 지역입지 특성분석,” 지역연구, 39(4), 19-32.
박주섭·홍순구·김종원, 2017, “토픽모델링을 활용한 과학기술동향 및 예측에 관한 연구,” 한국산업정보학회, 22(4), 19-28.
손정렬, 2024, “서울 대도시권 외국인 노동자 거주 분포 집중도와 분리도에 대한 공간통계 분석-국적별 집적 혹은 사회경제적 집적?-,” 대한지리학회지, 59(1), 55-72.
이대영·이현숙, 2021, “LDA 토픽 모델링의 적정 토픽 수 결정 방법 탐색: 혼잡도와 조화평균법 활용을 중심으로,” 교육평가연구, 34(1), 1-30.
최다인·민무홍, 2025, “온라인 채용정보를 활용한 보안 채용시장 분석,” 인터넷정보학회논문지, 26(3), 99-109.
Acemoglu, D., Autor, D., Hazell, J., and Restrepo, P., 2022, Artificial intelligence and jobs: Evidence from online vacancies, Journal of Labor Economics, 40(1), 293-340. 10.1086/718327
Bathelt, H. and Storper, M., 2023, Related variety and regional development: A critique, Economic Geography, 99(5), 441-470. 10.1080/00130095.2023.2235050
Berry, C.R. and Glaeser, E.L., 2005, The divergence of human capital levels across cities, Papers in Regional Science, 84(3), 407-444. 10.1111/j.1435-5957.2005.00047.x
Blei, D.M., Ng, A.Y., and Jordan, M.I., 2003, Latent Dirichlet allocation, Journal of Machine Learning Research, 3, 993-1022.
Blei, D.M., 2012, Probabilistic topic models, Communications of the ACM, 55(4), 24-27. 10.1145/2133806.2133826
Boschma, R., 2017, Relatedness as driver of regional diversification: A research agenda, Regional Studies, 51(3), 351-364. 10.1080/00343404.2016.1254767
Deming, D. and Kahn, L.B., 2018, Skill requirements across firms and labor markets: Evidence from job postings for professionals, Journal of Labor Economics, 36(1), 337-369. 10.1086/694106
Draca, M., Nathan, M., Nguyen-Tien, V., Oliveira-Cunha, J., Rosso, A., and Valero, A., 2024, The new wave? The role of human capital and STEM skills in technology adoption in the UK, IZA Discussion Paper, 17329, Institute of Labor Economics(IZA), Bonn. 10.2139/ssrn.4981216
Florida, R., 2002, The Economic Geography of Talent, Annals of the Association of American Geographers, 92(4), 743-755. 10.1111/1467-8306.00314
Florida, R. and Mellander, C., 2018, Talent, skills, and urban economies, In G. Clark, M.P. Feldman, M.S. Gertler and D. Wójcik (eds.), The new Oxford handbook of economic geography, 499-518. UK: Oxford. 10.1093/oxfordhb/9780198755609.013.23
Giambona, F., Kahlawi, A., Buzzigoli, L., Grassini, L., and Martelli, C., 2024, Skills in online job ads: An analysis of Italian regions, Socio-Economic Planning Sciences, 94, 101916. 10.1016/j.seps.2024.101916
Glaeser, E.L., Ponzetto, G.A., and Tobio, K., 2014, Cities, skills and regional change, Regional Studies, 48(1), 7-43. 10.1080/00343404.2012.674637
Goldfarb, A., Taska, B., and Teodoridis, F., 2023, Could machine learning be a general purpose technology? A comparison of emerging technologies using data from online job postings, Research Policy, 52(1), 104653. 10.1016/j.respol.2022.104653
Greene, D., O’Callaghan, D., and Cunningham, P., 2014, How many topics? Stability analysis for topic models, ECML PKDD 2024: Machine Learning and Knowledge Discovery in Database, 498-513. 10.1007/978-3-662-44848-9_32
Håkanson, C., Lindqvist, E., and Vlachos, J., 2021, Firms and skills: The evolution of worker sorting, Journal of Human Resources, 56(2), 512-538. 10.3368/jhr.56.2.0517-8801R2
Henning, M., Eriksson, R., Garefelt, P., Martin, H., and Elekes, Z., 2025, Job relatedness, local skill coherence and economic performance: A job postings approach, Regional Studies, Regional Science, 12(1), 95-122. 10.1080/21681376.2025.2459148
Jelodar, H., Wang, Y., Yuan, C., Feng, X., Jiang, X., Li, Y., and Zhao, L., 2019, Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey, Multimedia Tools and Applications, 78(11), 15169-15211. 10.1007/s11042-018-6894-4
Kalyani, A., Bloom, N., Carvalho, M., Hassan, T., Lerner, J., and Tahoun, A., 2025, The diffusion of new technologies, The Quarterly Journal of Economics, 140(2), 1299-1365. 10.1093/qje/qjaf002
Koo, J., 2005, How to analyze the regional economy with occupation data, Economic Development Quarterly, 19(4), 356-372. 10.1177/0891242405279910
Mellander, C. and Florida, R., 2021, The rise of skills: Human capital, the creative class, and regional development, in M.M. Fischer and P. Nijkamp., eds., Handbook of Regional Science, Germany: Springer, 707-719. 10.1007/978-3-662-60723-7_18
Moretti, E., 2012, The New Geography of Jobs, US: Houghton Mifflin Harcourt.
Neffke, F. and Henning, M., 2013, Skill relatedness and firm diversification, Strategic Management Journal, 34(3), 297-316. 10.1002/smj.2014
Neffke, F., Henning, M., and Boschma, R., 2011, How do regions diversify over time? Industry relatedness and the development of new growth paths in regions, Economic Geography, 87(3), 237-265. 10.1111/j.1944-8287.2011.01121.x
Newman, M., 2010, Networks : An Introduction, UK: Oxford University Press. 10.1093/acprof:oso/9780199206650.003.0001
Rodríguez-Pose, A. and Tselios, V., 2009, Education and income inequality in the regions of the European Union, Journal of Regional Science, 49(3), 411-437. 10.1111/j.1467-9787.2008.00602.x
Stolarick, K., Mellander, C., and Florida, R., 2010, Creative jobs, industries and places, Industry and Innovation, 17(1), 1-4. 10.1080/13662710903573794
Zhang, G., Tranos, E., and Zhu, R., 2025, Local demand for AI skills: A multiscale perspective in Great Britain, Annals of the American Association of Geographers, 1-20. 10.1080/24694452.2025.2511939

Information

Publisher :The Association of Korean Geographers
Publisher(Ko) :한국지리학회
Journal Title :Journal of the Association of Korean Geographers
Journal Title(Ko) :한국지리학회지
Volume : 15
No :1
Pages :155~168
DOI :https://doi.org/10.25202/JAKG.15.1.10

[1] 김선욱·양기덕, 2022, “LDA와 BERTopic을 이용한 토픽모델링의 증강과 확장 기법 연구,” 정보관리학회지, 39(3), 99-132.

[2] 남기찬, 2023, “공간 미스매치 실업과 지역노동시장권의 효용성에 대한 연구,” 지역연구, 39(4), 3-17.

[3] 박소현·윤정원·김민수·구양미, 2024, “지역산업 경로창출의 시공간적 특성 탐색 방법론: 인천 바이오의약산업을 사례로,” 도시연구, 0(25), 309-342.

[4] 박소현·이금숙, 2016, “한국 직업구조의 변화와 고용분포의 공간적 특성,” 대한지리학회지, 51(3), 401-420.

[5] 박정일, 2023, “채용공고 빅데이터를 활용한 괜찮은 일자리 공급의 산업 및 지역입지 특성분석,” 지역연구, 39(4), 19-32.

[6] 박주섭·홍순구·김종원, 2017, “토픽모델링을 활용한 과학기술동향 및 예측에 관한 연구,” 한국산업정보학회, 22(4), 19-28.

[7] 손정렬, 2024, “서울 대도시권 외국인 노동자 거주 분포 집중도와 분리도에 대한 공간통계 분석-국적별 집적 혹은 사회경제적 집적?-,” 대한지리학회지, 59(1), 55-72.

[8] 이대영·이현숙, 2021, “LDA 토픽 모델링의 적정 토픽 수 결정 방법 탐색: 혼잡도와 조화평균법 활용을 중심으로,” 교육평가연구, 34(1), 1-30.

[9] 최다인·민무홍, 2025, “온라인 채용정보를 활용한 보안 채용시장 분석,” 인터넷정보학회논문지, 26(3), 99-109.

[10] Acemoglu, D., Autor, D., Hazell, J., and Restrepo, P., 2022, Artificial intelligence and jobs: Evidence from online vacancies, Journal of Labor Economics, 40(1), 293-340. 10.1086/718327

[11] Bathelt, H. and Storper, M., 2023, Related variety and regional development: A critique, Economic Geography, 99(5), 441-470. 10.1080/00130095.2023.2235050

[12] Berry, C.R. and Glaeser, E.L., 2005, The divergence of human capital levels across cities, Papers in Regional Science, 84(3), 407-444. 10.1111/j.1435-5957.2005.00047.x

[13] Blei, D.M., Ng, A.Y., and Jordan, M.I., 2003, Latent Dirichlet allocation, Journal of Machine Learning Research, 3, 993-1022.

[14] Blei, D.M., 2012, Probabilistic topic models, Communications of the ACM, 55(4), 24-27. 10.1145/2133806.2133826

[15] Boschma, R., 2017, Relatedness as driver of regional diversification: A research agenda, Regional Studies, 51(3), 351-364. 10.1080/00343404.2016.1254767

[16] Deming, D. and Kahn, L.B., 2018, Skill requirements across firms and labor markets: Evidence from job postings for professionals, Journal of Labor Economics, 36(1), 337-369. 10.1086/694106

[17] Draca, M., Nathan, M., Nguyen-Tien, V., Oliveira-Cunha, J., Rosso, A., and Valero, A., 2024, The new wave? The role of human capital and STEM skills in technology adoption in the UK, IZA Discussion Paper, 17329, Institute of Labor Economics(IZA), Bonn. 10.2139/ssrn.4981216

[18] Florida, R., 2002, The Economic Geography of Talent, Annals of the Association of American Geographers, 92(4), 743-755. 10.1111/1467-8306.00314

[19] Florida, R. and Mellander, C., 2018, Talent, skills, and urban economies, In G. Clark, M.P. Feldman, M.S. Gertler and D. Wójcik (eds.), The new Oxford handbook of economic geography, 499-518. UK: Oxford. 10.1093/oxfordhb/9780198755609.013.23

[20] Giambona, F., Kahlawi, A., Buzzigoli, L., Grassini, L., and Martelli, C., 2024, Skills in online job ads: An analysis of Italian regions, Socio-Economic Planning Sciences, 94, 101916. 10.1016/j.seps.2024.101916

[21] Glaeser, E.L., Ponzetto, G.A., and Tobio, K., 2014, Cities, skills and regional change, Regional Studies, 48(1), 7-43. 10.1080/00343404.2012.674637

[22] Goldfarb, A., Taska, B., and Teodoridis, F., 2023, Could machine learning be a general purpose technology? A comparison of emerging technologies using data from online job postings, Research Policy, 52(1), 104653. 10.1016/j.respol.2022.104653

[23] Greene, D., O’Callaghan, D., and Cunningham, P., 2014, How many topics? Stability analysis for topic models, ECML PKDD 2024: Machine Learning and Knowledge Discovery in Database, 498-513. 10.1007/978-3-662-44848-9_32

[24] Håkanson, C., Lindqvist, E., and Vlachos, J., 2021, Firms and skills: The evolution of worker sorting, Journal of Human Resources, 56(2), 512-538. 10.3368/jhr.56.2.0517-8801R2

[25] Henning, M., Eriksson, R., Garefelt, P., Martin, H., and Elekes, Z., 2025, Job relatedness, local skill coherence and economic performance: A job postings approach, Regional Studies, Regional Science, 12(1), 95-122. 10.1080/21681376.2025.2459148

[26] Jelodar, H., Wang, Y., Yuan, C., Feng, X., Jiang, X., Li, Y., and Zhao, L., 2019, Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey, Multimedia Tools and Applications, 78(11), 15169-15211. 10.1007/s11042-018-6894-4

[27] Kalyani, A., Bloom, N., Carvalho, M., Hassan, T., Lerner, J., and Tahoun, A., 2025, The diffusion of new technologies, The Quarterly Journal of Economics, 140(2), 1299-1365. 10.1093/qje/qjaf002

[28] Koo, J., 2005, How to analyze the regional economy with occupation data, Economic Development Quarterly, 19(4), 356-372. 10.1177/0891242405279910

[29] Mellander, C. and Florida, R., 2021, The rise of skills: Human capital, the creative class, and regional development, in M.M. Fischer and P. Nijkamp., eds., Handbook of Regional Science, Germany: Springer, 707-719. 10.1007/978-3-662-60723-7_18

[30] Moretti, E., 2012, The New Geography of Jobs, US: Houghton Mifflin Harcourt.

[31] Neffke, F. and Henning, M., 2013, Skill relatedness and firm diversification, Strategic Management Journal, 34(3), 297-316. 10.1002/smj.2014

[32] Neffke, F., Henning, M., and Boschma, R., 2011, How do regions diversify over time? Industry relatedness and the development of new growth paths in regions, Economic Geography, 87(3), 237-265. 10.1111/j.1944-8287.2011.01121.x

[33] Newman, M., 2010, Networks : An Introduction, UK: Oxford University Press. 10.1093/acprof:oso/9780199206650.003.0001

[34] Rodríguez-Pose, A. and Tselios, V., 2009, Education and income inequality in the regions of the European Union, Journal of Regional Science, 49(3), 411-437. 10.1111/j.1467-9787.2008.00602.x

[35] Stolarick, K., Mellander, C., and Florida, R., 2010, Creative jobs, industries and places, Industry and Innovation, 17(1), 1-4. 10.1080/13662710903573794

[36] Zhang, G., Tranos, E., and Zhu, R., 2025, Local demand for AI skills: A multiscale perspective in Great Britain, Annals of the American Association of Geographers, 1-20. 10.1080/24694452.2025.2511939

Journal of the Association of Korean Geographers ISSN:2287-4739(Print) 2733-8991(Online) 한국지리학회지

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