Kesiapan dan Kompetensi Kecerdasan Buatan Kontekstual ASN: Kerangka Konseptual Integratif dalam Manajemen SDM Sektor Publik Contextual Artificial Intelligence Readiness and Competence of ASN: An Integrative Conceptual Framework in Public Sector SDM Management

Crossmark

Article Sidebar

Vol 6 No 6 (2026): YASIN: Jurnal Pendidikan dan Sosial Budaya
Page Numbers: 7382-7401
Download PDF
Published: Oct 4, 2026
Digital Object Identifier:
Save this to:
Save to Mendeley Download RIS

Article Metrics:
Viewed: 62 times
Downloaded: 17 times
Article can trace at:

Author Fee:
Free Publication Fees for Foreign Researchers (USD 0.00)
Check for article on SINTA:

LYAS Publisher cordially invites qualified professionals to serve as Editors or Reviewers. Your expertise will make an important contribution to maintaining and strengthening the academic quality of our publications. Interested applicants are kindly requested to complete the application form at the following link: Editors & Reviewers

Connected Papers:
Connected Papers


Please feel free to contact us if you need any further information about the submission process or if you have any additional questions.


Authors:
Muhammad Dendi Krisnadi1*, Sri Hartati2
Copyright :

Authors retain copyright and grant the journal right of first publication.

Explore Our Journals
Find the journal that best fits your research. If this journal does not match your manuscript’s scope, explore our portfolio below to select a more suitable publication venue.

Main Article Content

Muhammad Dendi Krisnadi
Google Scholar
Institut Pemerintahan Dalam Negeri
Sri Hartati
Institut Pemerintahan Dalam Negeri

Abstract

Although the adoption of artificial intelligence (AI) in public administration has been widely studied, the integration of AI readiness and competency frameworks for Indonesia’s Aparatur Sipil Negara (ASN) remains limited, while the contextualization of competencies remains normative and has yet to be operationalized. Indonesia ranks 42nd among 193 countries in the Government AI Readiness Index 2023. This study aims to explain the separation between AI readiness and competency frameworks, specify how structural contextualization can be operationalized, and develop an integrative framework for ASN. The study employed a narrative literature review approach involving 26 iterative search queries, with inclusion and exclusion criteria for publications from 2022–2026. The initial search yielded 17 verified sources, while targeted follow-up searches added 19 journal articles, resulting in a total of 36 sources analyzed through synthesis at five levels: findings, concepts, theory, methodology, and policy. The synthesis results indicated that individual competencies and attitudes were more influential in determining AI readiness than technical infrastructure. The competency frameworks of UNESCO, AI4Gov Canvas, and the European Commission have also yet to be integrated with readiness models or the human resource development cycle. Based on these findings, the study formulated a framework integrating Technology–Organization–Environment (TOE), Unified Theory of Acceptance and Use of Technology (UTAUT), and Ability–Motivation–Opportunity (AMO). Contextualization is positioned as a structural moderator shaped by digital maturity, service risk, and employee characteristics. No direct precedent for this pattern of integration was found in the reviewed literature. This framework makes a conceptual contribution to public sector human resource management by bridging the literature on AI readiness and competencies. Its practical implications include preliminary guidance for BKN and Kementerian PANRB in designing AI competencies suited to the characteristics of organizational units to support the operationalization of Law No. 20 of 2023 on ASN. This framework remains conceptual and requires empirical validation of its structural weights.

Keywords:
Download Full-Text PDF Direct PDF file • 12224.pdf
Share Article:

Citation Metrics:

Scopus

Downloads

Download data is not yet available.

Citation Metrics & Similar Scopus Articles

Citation data unavailable from the configured source
Check Secondary Documents in Scopus
Open this article in Scopus, then check the Secondary documents tab. Use Manual Citation Fallback only for counts you have verified manually.
Open in Scopus
Similar Scopus Articles
Scopus
  1. Nainggolan A.W. (2026)
    Development of the TUKKOT ASI Application Based on Batak Mambosuri Culture to Enhance Readiness for Exclusive Breastfeeding among Third-Trimester Pregnant Women
    Amerta Nutrition, 10(1), 83-95
  2. Jaswandi (2026)
    Comparative Assessment of Sperm Motility, Kinematics and Sperm-Cell Protein Band Profiles in Fresh, Frozen and Routine-Processed Y-Sexed Semen of Beef Bulls
    International Journal of Veterinary Science, 15(5), 1301-1311
  3. Catrin C. (2026)
    Emotional Intelligence, Work Engagement, and Turnover Intention Among Hospital Nurses: A Hierarchical Component Analysis
    Jurnal Keperawatan Indonesia, 29(2), 162-173

Article Details

How to Cite
Krisnadi, M. D., & Hartati, S. (2026). Kesiapan dan Kompetensi Kecerdasan Buatan Kontekstual ASN: Kerangka Konseptual Integratif dalam Manajemen SDM Sektor Publik. YASIN, 6(6), 7382-7401. https://doi.org/10.58578/yasin.v6i6.12224

Creative Commons License
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

References

Akbar, R. S., Soemartono, T., Sukmana, P., & Rachmatsyah, T. H. (2025). Developing a human resource management model for e-government implementation in the public sector. Jurnal Ilmiah Manajemen Kesatuan, 13(5), 3491–3502. https://doi.org/10.37641/jimkes.v13i5.3789

Alamäki, A. (2026). Expanding AI adoption in public sector organizations: Perspectives on management practices. Transforming Government: People, Process and Policy, 20(2), 165–187. https://doi.org/10.1108/TG-05-2025-0124

Ali, W., & Khan, A. Z. (2025). Factors influencing readiness for artificial intelligence: A systematic literature review. Data Science and Management, 8(2), 224–236. https://doi.org/10.1016/j.dsm.2024.09.005

Annapureddy, R., Fornaroli, A., & Gatica-Perez, D. (2024). Generative AI literacy: Twelve defining competencies. arXiv. https://arxiv.org/abs/2412.12107

Babsek, M., Murko, E., & Aristovnik, A. (2025). Organisational AI readiness for public administration: A comprehensive review and framework for conceptual modelling. International Journal of Economics and Business Administration, 13(3), 24–47. https://doi.org/10.35808/ijeba/894

Badan Kepegawaian Negara. (2026, June 11). Prof. Zudan: BKN & Microsoft Indonesia Bekerja Sama Latih 145 Ribu ASN Hadapi Era AI. https://www.bkn.go.id/prof-zudan-bkn-microsoft-indonesia-bekerja-sama-latih-145-ribu-asn-hadapi-era-ai/

Batool, A., Zowghi, D., & Bano, M. (2025). AI governance: A systematic literature review. AI and Ethics, 5(3), 3265–3279. https://doi.org/10.1007/s43681-024-00653-w

Bos-Nehles, A., Townsend, K., Cafferkey, K., & Trullen, J. (2023). Examining the ability, motivation and opportunity (AMO) framework in HRM research: Conceptualization, measurement and interactions. International Journal of Management Reviews, 25(4), 725–739. https://doi.org/10.1111/ijmr.12332

Chen, T., Gascó-Hernandez, M., & Esteve, M. (2024). The adoption and implementation of artificial intelligence chatbots in public organizations: Evidence from U.S. state governments. The American Review of Public Administration, 54(3), 255–270. https://doi.org/10.1177/02750740231200522

Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023). Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human Resource Management Review, 33(1), Article 100899. https://doi.org/10.1016/j.hrmr.2022.100899

Fahrisky, A., Nurmandi, A., Younus, M., & Lawelai, H. (2025). The role of artificial intelligence in digital maturity models: A bibliometric analysis (2015–2024). Society, 13(2), 659–674. https://doi.org/10.33019/society.v13i2.783

Felemban, H., Sohail, M., & Ruikar, K. (2024). Exploring the readiness of organisations to adopt artificial intelligence. Buildings, 14(8), Article 2460. https://doi.org/10.3390/buildings14082460

Gao, Q., Wang, S., Liang, Z., Wang, G., & Guo, L. (2025). Sailing with the cultural winds: The impact of national culture on government AI adoption. Global Public Policy and Governance, 5, 251–273. https://doi.org/10.1007/s43508-025-00122-y

Haesevoets, T., Verschuere, B., & Roets, A. (2025). AI adoption in public administration: Perspectives of public sector managers and public sector non-managerial employees. Government Information Quarterly, 42(2), Article 102029. https://doi.org/10.1016/j.giq.2025.102029

Hankins, E., Fuentes Nettel, P., Martinescu, L., Grau, G., & Rahim, S. (2023). Government AI readiness index 2023. Oxford Insights. https://oxfordinsights.com/wp-content/uploads/2023/12/2023-Government-AI-Readiness-Index-1.pdf

Hržica, R., Debelak, K., & Pevcin, P. (2025). A dual-level model of AI readiness in the public sector: Merging organizational and individual factors using TOE and UTAUT. Systems, 13(8), Article 705. https://doi.org/10.3390/systems13080705

Jonathan, G. M., Yalew, S. D., Gebremeskel, B. K., & Watat, J. K. (2025). AI adoption in the public sector: Organizational readiness and the pursuit of public value. Complex Systems Informatics and Modeling Quarterly, 45, 43–70. https://doi.org/10.7250/csimq.2025-45.03

Lāma, G., & Lastovska, A. (2025). Exploring public sector workforce attitudes toward AI competence and its impact on AI competence self-assessment. Social Sciences & Humanities Open, 12, Article 101809. https://www.sciencedirect.com/science/article/pii/S2590291125005376

Lan, Z., Wu, X., Xing, X., & Wang, Y. (2026). The combined impact of ability, motivation, and opportunity factors on employees’ sustained workplace proactivity. Frontiers in Psychology, 17, Article 1772119. https://doi.org/10.3389/fpsyg.2026.1772119

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), Article 101774. https://doi.org/10.1016/j.giq.2022.101774

Madanchian, M., & Taherdoost, H. (2025). Barriers and enablers of AI adoption in human resource management: A critical analysis of organizational and technological factors. Information, 16(1), Article 51. https://doi.org/10.3390/info16010051

Medaglia, R., Gil-Garcia, J. R., & Pardo, T. A. (2023). Artificial intelligence in government: Taking stock and moving forward. Social Science Computer Review, 41(1), 123–140. https://doi.org/10.1177/08944393211034087

Medaglia, R., Mikalef, P., & Tangi, L. (2024). Competences and governance practices for artificial intelligence in the public sector. Publications Office of the European Union. https://doi.org/10.2760/7895569

Mergel, I., Dickinson, H., Stenvall, J., & Gascó, M. (2023). Implementing AI in the public sector. Public Management Review, 1–14. https://doi.org/10.1080/14719037.2023.2231950

Miller, S., & Ghaffarzadegan, N. (2025). Dynamic capabilities in the public sector: A systematic literature review. International Journal of Public Sector Management, 38(6), 717–734. https://doi.org/10.1108/ijpsm-05-2024-0154

Misuraca, G. C., Medaglia, R., Feijoo, C., Mortati, M., & van Noordt, C. (2025). Developing competences for artificial intelligence in the public sector: The AI4Gov Canvas. Conference on Digital Government Research, 26. https://doi.org/10.59490/dgo.2025.951

Mwita, K. M., & Kitole, F. A. (2025). Potential benefits and challenges of artificial intelligence in human resource management in public institutions. Discover Global Society, 3, Article 35. https://doi.org/10.1007/s44282-025-00175-8

Neumann, O., Guirguis, K., & Steiner, R. (2022). 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

Praja, N. R., Suryanto, Suaedi, F., & Nasution, Z. (2026). Strategi Pengembangan Kompetensi ASN melalui Integrasi Manajemen Talenta di Sektor Publik: Systematic Literature Review. Cakrawala, 20(1), 41–56. https://doi.org/10.32781/cakrawala.v20i1.966

Rahim, R. (2024). Strategi Pengembangan Kompetensi ASN di Era Transformasi Digital. Jurnal Transformasi Administrasi, 14(2). https://jta.lan.go.id/index.php/jta/article/view/438

Robles, P., & Mallinson, D. J. (2025). Advancing AI governance with a unified theoretical framework: A systematic review. Perspectives on Public Management and Governance, 8(4), 213–227. https://doi.org/10.1093/ppmgov/gvaf013

Selten, F., & Klievink, B. (2024). Organizing public sector AI adoption: Navigating between separation and integration. Government Information Quarterly, 41(1), Article 101885. https://doi.org/10.1016/j.giq.2023.101885

Tangi, L., Müller, A. P. R., & Janssen, M. (2025). AI-augmented government transformation: Organisational transformation and the sociotechnical implications of artificial intelligence in public administrations. Government Information Quarterly, 42(3), Article 102055. https://doi.org/10.1016/j.giq.2025.102055

Undang-Undang Republik Indonesia Nomor 20 Tahun 2023 tentang Aparatur Sipil Negara. (2023). https://peraturan.bpk.go.id/Details/269470/uu-no-20-tahun-2023

UNESCO. (2022). Artificial intelligence and digital transformation: Competencies for civil servants. https://www.unesco.org/en/articles/artificial-intelligence-and-digital-transformation

Van Noordt, C., & Misuraca, G. (2022). Artificial intelligence for the public sector: Results of landscaping the use of AI in government across the European Union. Government Information Quarterly, 39(3), Article 101714. https://doi.org/10.1016/j.giq.2022.101714