Competencies for AI adoption in public administration: A demand-side study based on job postings from Germany (Online First)
Hauptsächlicher Artikelinhalt
Abstract
Digital competencies have become a central field of interest for politics, academics, and business in the last decade. The relevance and range of AI competencies for e-government have already been addressed by several studies, although generalisable empirical analyses based upon quantitative approaches are rare. The aim of the research presented in this study is to understand which competencies are needed for AI adoption in public administration from the employer’s perspective. For this purpose, a large-scale analysis of N=62,028 public job postings from Germany between July and November 2023 was conducted. Based on a conceptual framework of AI in public administration, text mining methods were used to extract AI competency requirements. The results show that AI currently is not a dominant topic in the light of public job offerings in Germany, with only 0.91% (n=565 job postings) including the term artificial intelligence (“Künstliche Intelligenz”). While this supports the assumption that AI has not yet proliferated as a cross-sectional technology within public administration and remains in an early stage, it also emphasises the need for effective measures to achieve the political goals in national and European strategy documents.
Keywords: AI Adoption, AI Competencies, Job Posting Analysis, Job Mining, E-Government
Bibliography: Auth, Gunnar, Bensberg, Frank & Christ, Julian P. (2026). Competencies for AI adoption in public administration: A demand-side study based on job postings from Germany (Online First). dms – der moderne staat – Zeitschrift für Public Policy, Recht und Management, 19(1-2026), 1-21.
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Literatur
Agarwal, P. K. (2018). Public Administration Challenges in the World of AI and Bots. Public Administration Review, 78(6), 917–921. https://doi.org/10.1111/puar.12979
Akbarighatar, P. (2024). Operationalizing responsible AI principles through responsible AI capabilities. AI and Ethics. https://doi.org/10.1007/s43681-024-00524-4
Almatrafi, O., Johri, A., & Lee, H. (2024). A systematic review of AI literacy conceptualization, constructs, and implementation and assessment efforts (2019–2023). Computers and Education Open, 6, 100173. https://doi.org/10.1016/j.caeo.2024.100173
André, E., & Bauer, W. (Eds.). (2021). Competence development for AI – Changes, needs and Options for action. White paper from Plattform Lernende Systeme (Learning systems platform). https://doi.org/10.48669/pls_2021-2
Angenendt, S., Knapp, N., & Kipp, D. (2023). Germany is looking for foreign labour: How to make recruitment development-orientated, sustainable and fair. SWP Research Paper. https://doi.org/10.18449/2023RP03
Anton, E., Behne, A., & Teuteberg, F. (2020, June 16). The Humans Behind Artificial Intelligence – An Operationalisation of AI Competencies. Proceedings of the 28th European Conference on Information Systems (ECIS). https://aisel.aisnet.org/ecis2020_rp/141
Arifin, A. (2021). Competence, Competency, and Competencies: A Misunderstanding in Theory and Practice for Future Reference. International Journal of Academic Research in Business and Social Sciences, 11(9), 755–764. https://doi.org/10.6007/IJARBSS/v11-i9/11064
Arregui Pabollet, E., Bacigalupo, M., Biagi, F., Cabrera Giraldez, M., Caena, F., Castano Munoz, J. et al. (2019). The changing nature of work and skills in the digital age. European Commission. Joint Research Centre. https://data.europa.eu/doi/10.2760/679150
Auth, G., Jöhnk, J., & Wiecha, D. A. (2021). A Conceptual Framework for Applying Artificial Intelligence in Project Management. 2021 IEEE 23rd Conference on Business Informatics (CBI). https://doi.org/10.1109/CBI52690.2021.00027
Batool, A., Zowghi, D., & Bano, M. (2025). AI governance: A systematic literature review. AI and Ethics. https://doi.org/10.1007/s43681-024-00653-w
Bright, J., Enock, F., Esnaashari, S., Francis, J., Hashem, Y., & Morgan, D. (2024). Generative AI is already widespread in the public sector: Evidence from a survey of UK public sector professionals. Digital Government: Research and Practice, 3700140. https://doi.org/10.1145/3700140
Brynjolfsson, E., Li, D., & Raymond, L. (2023). Generative Ai at Work (SSRN Scholarly Paper 4426942). Social Science Research Network. https://papers.ssrn.com/abstract=4426942
Charles, L., Xia, S., & Coutts, A. P. (2022). Digitalization and Employment: A Review. International Labour Organization. https://www.ilo.org/sites/default/files/wcmsp5/groups/public/@ed_emp/documents/publication/wcms_854353.pdf
Chen, S. (2016). Training and Qualification: Essentials of Skill Management. In M. Zeuch (Ed.), Handbook of Human Resources Management (pp. 213–224). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-44152-7_24
Codagnone, C., Vanini, I., Cibaitė, G., Misuraca, G., Gineikytė, V. et al. (2019). Exploring digital government transformation in the EU: Analysis of the state of the art and review of literature. European Commission, Joint Research Centre, Publications Office. https://data.europa.eu/doi/10.2760/17207
dbb (ed.). (2023). Staff shortages in the public sector – the state is short of over 500,000 employees (Personalmangel im öffentlichen Dienst – Dem Staat fehlen über 500.000 Beschäftigte). https://www.dbb.de/artikel/dem-staat-fehlen-ueber-500000-beschaeftigte.html
Distel, B., Ogonek, N., Becker, J. (2019). eGovernment competences revisited – a literature review on necessary competences in a digitalized public sector. In Proceedings of the 14th International Conference on Wirtschaftsinformatik, (pp. 286–300). https://aisel.aisnet.org/wi2019/track04/papers/1/
European Commission (ed.). (2018). Artificial Intelligence for Europe. https://eur-lex.europa.eu/legalcontent/EN/TXT/?uri=COM:2018:237:FIN
Federal Government (Bundesregierung) (ed.). (2018). Artificial Intelligence Strategy of the Federal Government [of Germany] (Strategie Künstliche Intelligenz der Bundesregierung). https://www.kistrategie-deutschland.de/?file=files/downloads/Nationale_KI-Strategie.pdf&cid=728
Federal Ministry of the Interior (Bundesministerium des Innern) (ed.) (2025). Public sector employees (Beschäftigte im öffentlichen Dienst). https://www.bmi.bund.de/DE/themen/oeffentlicher-dienst/zahlen-daten-fakten/zahlen-daten-fakten-node.html?showtable=1
Federal Statistical Office of Germany (Statistisches Bundesamt) (ed.). (2024). Statistical report – Public service personnel – Reference date: June 30, 2023 (Statistischer Bericht – Personal des öffentlichen Dienstes – Stichtag 30. 06. 2023). https://www.destatis.de/DE/Themen/Staat/Oeffentlicher-Dienst/Publikationen/Downloads-Oeffentlicher-Dienst/statistischer-bericht-personalstand-oeffentlicher-dienst-2140600237005.html
Fischer-Abaigar, U., Kern, C., Barda, N., & Kreuter, F. (2024). Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector. Government Information Quarterly, 41(4), 101976. https://doi.org/10.1016/j.giq.2024.101976
Green, A. (2024). Artificial intelligence and the changing demand for skills in the labour market (OECD Artificial Intelligence Papers 14; OECD Artificial Intelligence Papers, Vol. 14). https://doi.org/10.1787/88684e36-en
Haug, N., Dan, S., & Mergel, I. (2024). Digitally-induced change in the public sector: A systematic review and research agenda. Public Management Review, 26(7), 1963–1987. https://doi.org/10.1080/14719037.2023.2234917
Hofmann, P., Jöhnk, J., Protschky, D., & Urbach, N. (2020). Developing Purposeful AI Use Cases – A Structured Method and Its Application in Project Management. 33–49. https://doi.org/10.30844/wi_2020_a3-hofmann
Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or Not, AI Comes—An Interview Study of Organizational AI Readiness Factors. Business & Information Systems Engineering, 63(1), 5–20. https://doi.org/10.1007/s12599-020-00676-7
Koddebusch, M., Halsbenning, S., Kruse, P., Räckers, M., & Becker, J. (2022). The Increasing e-Competence Gap: Developments over the Past Five Years in the German Public Sector. In F. Fui-Hoon Nah & K. Siau (eds.), HCI in Business, Government and Organizations (vol. 13327, pp. 73–86). Springer International Publishing. https://doi.org/10.1007/978-3-031-05544-7_6
Kölling, A. (2022). Shortage of Skilled Labor, Unions and the Wage Premium: A Regression Analysis with Establishment Panel Data for Germany. Journal of Labor Research, 43(2), 239–259. https://doi.org/10.1007/s12122-022-09334-1
Lintner, T. (2024). A systematic review of AI literacy scales. Npj Science of Learning, 9(1), 50. https://doi.org/10.1038/s41539-024-00264-4
Litecky, C., Aken, A., Ahmad, A., & Nelson, H.J. (2010). Mining for Computing Jobs. IEEE Software, 27(1), 78–85. https://doi.org/10.1109/MS.2009.150
Long, D., & Magerko, B. (2020). What is AI Literacy? Competencies and Design Considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16. https://doi.org/10.1145/3313831.3376727
Madan, R., & Ashok, M. (2023). AI adoption and diffusion in public administration: A systematic literature review and future research agenda. Government Information Quarterly, 40(1), 101774. https://doi.org/10.1016/j.giq.2022.101774
Medaglia, R., Mikalef, P., & Tangi, L. (2024). Competencies and governance practices for AI in the public sector. European Commission, Joint Research Centre, Publications Office. https://data.europa.eu/doi/10.2760/7895569
Mikalef, P., Islam, N., Parida, V., Singh, H., & Altwaijry, N. (2023). Artificial intelligence (AI) competencies for organizational performance: A B2B marketing capabilities perspective. Journal of Business Research, 164, 113998. https://doi.org/10.1016/j.jbusres.2023.113998
Mikalef, P., Lemmer, K., Schaefer, C., Ylinen, M., Fjørtoft, S. O., Torvatn, H. Y., Gupta, M., & Niehaves, B. (2022). Enabling ai capabilities in government agencies: A study of determinants for european municipalities. Government Information Quarterly, 39(4), 101596. https://doi.org/10.1016/j.giq.2021
Neumann, O., Guirguis, K., & Steiner, R. (2024). Exploring artificial intelligence adoption in public organizations: A comparative case study. Public Management Review, 26(1), 114–141. https://doi.org/10.1080/14719037.2022.2048685
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041
Oesterreich, T. D., Teuteberg, F., Bensberg, F., & Buscher, G. (2019). The controlling profession in the digital age: Understanding the impact of digitisation on the controller’s job roles, skills and competences. International Journal of Accounting Information Systems, 35, 100432. https://doi.org/10.1016/j.accinf.2019.100432
O’Kane, L., Narasimhan, R., Nania, J., & Taska, B. (2020). Digitalization in the German Labor Market: Analyzing Demand for Digital Skills in Job Vacancies. Bertelsmann Stiftung. https://www.bertelsmann-stiftung.de/doi/10.11586/2019073
Rackwitz, M., Hustedt, T., & Hammerschmid, G. (2021). Digital transformation: From hierarchy to network-based collaboration? The case of the German “Online Access Act.” dms – Zeitschrift für Public Policy, Recht und Management, 14(1–2021), 101–120. https://doi.org/10.3224/dms.v14i1.05
Santana, M., & Díaz-Fernández, M. (2023). Competencies for the artificial intelligence age: Visualisation of the state of the art and future perspectives. Review of Managerial Science, 17(6), 1971–2004. https://doi.org/10.1007/s11846-022-00613-w
Schiff, D. S., Schiff, K. J., & Pierson, P. (2022). Assessing public value failure in government Adoption of artificial intelligence. Public Administration, 100(3), 653–673. https://doi.org/10.1111/padm.12742
Sun, T. Q., & Medaglia, R. (2019). Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly, 36(2), 368–383. https://doi.org/10.1016/j.giq.2018.09.008
Tangi, L., Van Noordt, C., & Rodriguez M., A. P. (2023). The challenges of AI implementation in the public sector. An in-depth case studies analysis. Proceedings of the 24th Annual International Conference on Digital Government Research, 414–422. https://doi.org/10.1145/3598469.3598516
van Noordt, C., & Misuraca, G. (2022a). Artificial intelligence for the public sector: Results of landscaping the use of AI in government across the European Union. Government Information Quarterly, 39(3), 101714. https://doi.org/10.1016/j.giq.2022.101714
van Noordt, C., & Misuraca, G. (2022b). Exploratory Insights on Artificial Intelligence for Government in Europe. Social Science Computer Review, 40(2), 426–444. https://doi.org/10.1177/0894439320980449
van Noordt, C., & Tangi, L. (2023). The dynamics of AI capability and its influence on public value creation of AI within public administration. Government Information Quarterly, 40(4), 101860. https://doi.org/10.1016/j.giq.2023.101860
Vuorikari, R., Kluzer, S., Punie, Y. (2022). DigComp 2.2, The Digital Competence framework for citizens: With new examples of knowledge, skills and attitudes. European Commission, Joint Research Centre, Publications Office. https://doi.org/10.2760/115376
Wilson, C., & Mergel, I. (2022). Overcoming barriers to digital government: Mapping the strategies of digital champions. Government Information Quarterly, 39(2), 101681. https://doi.org/10.1016/j.giq.2022.101681
Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial Intelligence and the Public Sector—Applications and Challenges. International Journal of Public Administration, 42(7), 596–615. https://doi.org/10.1080/01900692.2018.1498103