Research Article
BibTex RIS Cite

The future of public governance transition from e-government to a-government: A comparative analysis of Türkiye and Estonia

Year 2025, Volume: 15 Issue: ISRIS 2025, 87 - 116, 31.07.2025
https://doi.org/10.48146/odusobiad.1728265

Abstract

Artificial intelligence (AI) is increasingly becoming a crucial component in public administration, enabling governments to enhance service delivery efficiency, transparency, and effectiveness. AI is being effectively utilized across all countries. AI-driven digital governance models offer impactful solutions across various domains, from policy-making to citizen services. This study compares the AI-supported public administration strategies of Turkey and Estonia, analyzing their similarities and differences in AI implementation. Turkey has made significant progress in integrating AI into public services, particularly in security and education. However, challenges such as regulatory gaps, infrastructural limitations, and a shortage of AI professionals restrict its full potential. In contrast, Estonia’s centralized and integrated digital infrastructure allows for more effective AI-driven governance applications. This study evaluates AI policies in both countries and provides policy recommendations for improving AI integration in public administration. The findings emphasize that robust digital infrastructure, ethical regulations, and citizen engagement are essential factors for the success of AI-powered governance.

Ethical Statement

HERHANGİ BİR ETİK BEYAN GEREKTİRECEK ÇALIŞMA OLMAMIŞTIR.

Supporting Institution

HERHANGİ BİR KURUM TARAFINDAN DESTEKLENMEMİŞTİR.

References

  • Arslan, K. (2020). Eğitimde yapay zeka ve uygulamalari [Artificial Intelligence and Applications in Education]. Batı Anadolu Eğitim Bilimleri Dergisi [Western Anatolia Journal of Educational Sciences], 11(1), 71-88.
  • Brynjolfsson, E., & McAfee, A. (2017). The Business of artificial intelligence: What it can - and cannot - do for your organization. Harvard Business Review. https://hbr.org/2017/07/the-business-of-artificial-intelligence
  • Birinci, Ş. (2023). A Digital Opportunity for Patients to Manage Their Health: Turkey National Personal Health Record System (The e Nabız). Balkan Medical Journal, 40(3), 215–221. https://doi.org/10.4274/balkanmedj.galenos.2023.2023-2-77
  • Cath, C., & Jansen, F. (2021). Dutch Comfort: The limits of AI governance through municipal registers. Technology in Society, 67, 101764. https://doi.org/10.1016/j.techsoc.2021.101764
  • Creemers, R. (2018). China’s Social Credit System: An evolving practice of control. Leiden Law Review, 31(1), 53–64.
  • Chen, Z., Wang, L., & Li, K. (2021). AI driven urban informatics and smart nation infrastructure in Singapore. NPJ Urban Sustainability, 1(1), Article 8. https://doi.org/10.1038/s43762-025-00190-0
  • Cumhurbaşkanlığı Dijital Dönüşüm Ofisi [CBDDO]. (2021). 2021–2025 ulusal yapay zekâ stratejisi [2021–2025 national artificial intelligence strategy]. T.C. Cumhurbaşkanlığı Dijital Dönüşüm Ofisi Yayınları.
  • European Commission. (2022). E-Government and digital transformation in public administration. European Union Publications.
  • European Commission. (2023). Digital Economy and Society Index (DESI) 2023: AI in public governance. European Union Publications.
  • E Estonia. (2025). Estonia and automated decision making: Challenges for public administration. e Estonia.
  • Heeks, R. (2006). Benchmarking eGovernment: Improving the national and international measurement, evaluation and comparison of eGovernment (iGovernment Working Paper No. 18). Global Development Institute, University of Manchester. https://doi.org/10.2139/ssrn.3540043
  • Heeks, R. (2021). Digital government: Theory and practice. Routledge.
  • Istanbul Chronicle. (2023). Digital governance strategies and ai in Turkish public administration. Istanbul Chronicle Publications.
  • Janssen, M., & Helbig, N. (2018). Dashboards in public governance: How AI and machine learning enable data-driven decision making. Government Information Quarterly, 35(1), 105–121. https://doi.org/10.1016/j.giq.2017.08.002
  • Janssen, M., & Kuk, G. (2016). The challenges and limits of big data algorithms in technocratic governance. Government Information Quarterly, 33(3), 371–377. https://doi.org/10.1016/j.giq.2016.08.011
  • Kaya, B., & Demir, O. (2022). Artificial intelligence in Turkish education sector: The role of EBA virtual assistant. Journal of Digital Transformation Studies, 10(3), 45-60.
  • Kerikmäe, A., & Rull, A. (2018). Legal aspects of digital transformation in governance: The case of Estonia. Springer
  • Kerikmäe, T., & Pärn Lee, E. (2020). Legal dilemmas of Estonian artificial intelligence strategy: In between of e society and global race. AI & Society, 36, 561-571. https://doi.org/10.1007/s00146-020-01009-8
  • Krishnamurthy, R., & Desouza, K. C. (2014). Big data analytics: The case of the Social Security Administration. Information Polity, 19(3–4), 165–178. https://doi.org/10.3233/IP-140337
  • Meijer, A. J., & Bolívar, M. P. R. (2016). Governing the smart city: A review of the literature on smart governance. International Review of Administrative Sciences, 82(2), 392–408. https://doi.org/10.1177/0020852314564308
  • Margetts, H., & Dunleavy, P. (2013). The second wave of digital era governance: A quasi paradigm for government on the Web. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 371(1987), Article 20120382. https://doi.org/10.1098/rsta.2012.0382
  • Mergel, I., Edelmann, N., & Haug, N. (2019). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 36(4), 101385. https://doi.org/10.1016/j.giq.2019.101385
  • Mergel, I., Edelmann, N., & Haug, N. (2019). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 36(4), 101385. https://doi.org/10.1016/j.giq.2019.101385
  • OECD. (2023). Artificial intelligence in public sector: Enhancing government decision-making. OECD Publishing.
  • Republic of Türkiye Digital Transformation Office. (2022). [Türkiye’s digital governance strategies and ai policies]. T.C. Cumhurbaşkanlığı Yayınları.
  • Schwab, K. (2016). The fourth industrial revolution: What it means and how to respond. World Economic Forum. https://www.weforum.org/agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and-how-to-respond.
  • SETAV [Foundation for Political, Economic and Social Research] (2021). Turkey’s open government data meets AI. SETA. https://www.setav.org/en/turkiyes-open-government-data-meets-ai
  • Tamm, R. (2023). The role of ai in digital governance: Estonia's experience. Tallinn University Press.
  • The Istanbul Chronicle. (2023). Turkey’s adaptation to artificial intelligence: Challenges and opportunities. The Istanbul Chronicle. https://www.theistanbulchronicle.com/post/turkey-s-adaptation-to-artificial-intelligent-challenges-and-opportunities
  • TÜBİTAK. (2022). Yapay zekâ araştırma ve geliştirme stratejisi [Artificial intelligence research and development strategy]. TÜBİTAK Yayınları.
  • United Nations. (2022). E-Government survey 2022: The Future of digital government. United Nations Publications.
  • United Nations Department of Economic and Social Affairs. (2024). United Nations E Government Survey 2024: The future of digital government. United Nations. https://publicadministration.un.org/egovkb
  • Yang, J., & Lee, M. (2023). Smart city and remote services: The case of South Korea’s national strategic smart city program. Land, 14(5), 928. https://doi.org/10.3390/land14050928
  • Yayla, A., Świerczewska, K. S., Kaya, M., Karaca, B., Arayici, Y., Ayözen, Y. E., & Tokdemir, O. B. (2022). Artificial intelligence (AI)-based occupant-centric heating ventilation and air conditioning (HVAC) control system for multi zone commercial buildings. Sustainability, 14(23), Article 16107. https://doi.org/10.3390/su142316107
  • Yorgancıoğlu Tarcani, G., Yalçın Balçık, P., & Sebik, N. B. (2024). Türkiye ve dünyada sağlık hizmetlerinde yapay zekâ [Artificial intelligence in healthcare in Türkiye and the world]. Mersin Üniversitesi Tıp Fakültesi Lokman Hekim Tıp Tarihi ve Folklorik Tıp Dergisi, 14(1), 50–60. https://doi.org/10.31020/mutftd.1278529

Kamu yönetiminin geleceği e-devletten a-devlete geçiş: Türkiye ve Estonya’nın karşılaştırmalı analizi

Year 2025, Volume: 15 Issue: ISRIS 2025, 87 - 116, 31.07.2025
https://doi.org/10.48146/odusobiad.1728265

Abstract

Yapay zekâ (YZ), kamu yönetiminde giderek daha önemli bir bileşen hâline gelmekte ve devletlerin hizmet sunumunda etkinlik, şeffaflık ve verimlilik sağlamasına imkân tanımaktadır. YZ tüm ülkelerde etkin şekilde kullanılmaktadır. YZ destekli dijital yönetişim modelleri, politika oluşturma süreçlerinden vatandaş hizmetlerine kadar çeşitli alanlarda etkili çözümler sunmaktadır. Bu çalışma, Türkiye ve Estonya’nın YZ destekli kamu yönetimi stratejilerini karşılaştırmakta ve YZ uygulamalarındaki benzerlikleri ile farklılıklarını analiz etmektedir. Türkiye, özellikle güvenlik ve eğitim alanlarında YZ’yi kamu hizmetlerine entegre etme konusunda önemli ilerlemeler kaydetmiştir. Ancak, düzenleyici boşluklar, altyapısal sınırlılıklar ve YZ uzmanı eksikliği gibi faktörler, bu potansiyelin tam olarak gerçekleştirilmesini engellemektedir. Buna karşılık, Estonya’nın merkezi ve entegre dijital altyapısı, YZ destekli yönetişim uygulamalarının daha etkili bir şekilde hayata geçirilmesine olanak tanımaktadır. Çalışmada her iki ülkenin YZ politikaları değerlendirilmekte ve kamu yönetiminde YZ entegrasyonunun iyileştirilmesine yönelik politika önerileri sunulmaktadır. Bulgular, güçlü dijital altyapı, etik düzenlemeler ve vatandaş katılımının YZ destekli yönetişimin başarısı için temel unsurlar olduğunu ortaya koymaktadır.

References

  • Arslan, K. (2020). Eğitimde yapay zeka ve uygulamalari [Artificial Intelligence and Applications in Education]. Batı Anadolu Eğitim Bilimleri Dergisi [Western Anatolia Journal of Educational Sciences], 11(1), 71-88.
  • Brynjolfsson, E., & McAfee, A. (2017). The Business of artificial intelligence: What it can - and cannot - do for your organization. Harvard Business Review. https://hbr.org/2017/07/the-business-of-artificial-intelligence
  • Birinci, Ş. (2023). A Digital Opportunity for Patients to Manage Their Health: Turkey National Personal Health Record System (The e Nabız). Balkan Medical Journal, 40(3), 215–221. https://doi.org/10.4274/balkanmedj.galenos.2023.2023-2-77
  • Cath, C., & Jansen, F. (2021). Dutch Comfort: The limits of AI governance through municipal registers. Technology in Society, 67, 101764. https://doi.org/10.1016/j.techsoc.2021.101764
  • Creemers, R. (2018). China’s Social Credit System: An evolving practice of control. Leiden Law Review, 31(1), 53–64.
  • Chen, Z., Wang, L., & Li, K. (2021). AI driven urban informatics and smart nation infrastructure in Singapore. NPJ Urban Sustainability, 1(1), Article 8. https://doi.org/10.1038/s43762-025-00190-0
  • Cumhurbaşkanlığı Dijital Dönüşüm Ofisi [CBDDO]. (2021). 2021–2025 ulusal yapay zekâ stratejisi [2021–2025 national artificial intelligence strategy]. T.C. Cumhurbaşkanlığı Dijital Dönüşüm Ofisi Yayınları.
  • European Commission. (2022). E-Government and digital transformation in public administration. European Union Publications.
  • European Commission. (2023). Digital Economy and Society Index (DESI) 2023: AI in public governance. European Union Publications.
  • E Estonia. (2025). Estonia and automated decision making: Challenges for public administration. e Estonia.
  • Heeks, R. (2006). Benchmarking eGovernment: Improving the national and international measurement, evaluation and comparison of eGovernment (iGovernment Working Paper No. 18). Global Development Institute, University of Manchester. https://doi.org/10.2139/ssrn.3540043
  • Heeks, R. (2021). Digital government: Theory and practice. Routledge.
  • Istanbul Chronicle. (2023). Digital governance strategies and ai in Turkish public administration. Istanbul Chronicle Publications.
  • Janssen, M., & Helbig, N. (2018). Dashboards in public governance: How AI and machine learning enable data-driven decision making. Government Information Quarterly, 35(1), 105–121. https://doi.org/10.1016/j.giq.2017.08.002
  • Janssen, M., & Kuk, G. (2016). The challenges and limits of big data algorithms in technocratic governance. Government Information Quarterly, 33(3), 371–377. https://doi.org/10.1016/j.giq.2016.08.011
  • Kaya, B., & Demir, O. (2022). Artificial intelligence in Turkish education sector: The role of EBA virtual assistant. Journal of Digital Transformation Studies, 10(3), 45-60.
  • Kerikmäe, A., & Rull, A. (2018). Legal aspects of digital transformation in governance: The case of Estonia. Springer
  • Kerikmäe, T., & Pärn Lee, E. (2020). Legal dilemmas of Estonian artificial intelligence strategy: In between of e society and global race. AI & Society, 36, 561-571. https://doi.org/10.1007/s00146-020-01009-8
  • Krishnamurthy, R., & Desouza, K. C. (2014). Big data analytics: The case of the Social Security Administration. Information Polity, 19(3–4), 165–178. https://doi.org/10.3233/IP-140337
  • Meijer, A. J., & Bolívar, M. P. R. (2016). Governing the smart city: A review of the literature on smart governance. International Review of Administrative Sciences, 82(2), 392–408. https://doi.org/10.1177/0020852314564308
  • Margetts, H., & Dunleavy, P. (2013). The second wave of digital era governance: A quasi paradigm for government on the Web. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 371(1987), Article 20120382. https://doi.org/10.1098/rsta.2012.0382
  • Mergel, I., Edelmann, N., & Haug, N. (2019). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 36(4), 101385. https://doi.org/10.1016/j.giq.2019.101385
  • Mergel, I., Edelmann, N., & Haug, N. (2019). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 36(4), 101385. https://doi.org/10.1016/j.giq.2019.101385
  • OECD. (2023). Artificial intelligence in public sector: Enhancing government decision-making. OECD Publishing.
  • Republic of Türkiye Digital Transformation Office. (2022). [Türkiye’s digital governance strategies and ai policies]. T.C. Cumhurbaşkanlığı Yayınları.
  • Schwab, K. (2016). The fourth industrial revolution: What it means and how to respond. World Economic Forum. https://www.weforum.org/agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and-how-to-respond.
  • SETAV [Foundation for Political, Economic and Social Research] (2021). Turkey’s open government data meets AI. SETA. https://www.setav.org/en/turkiyes-open-government-data-meets-ai
  • Tamm, R. (2023). The role of ai in digital governance: Estonia's experience. Tallinn University Press.
  • The Istanbul Chronicle. (2023). Turkey’s adaptation to artificial intelligence: Challenges and opportunities. The Istanbul Chronicle. https://www.theistanbulchronicle.com/post/turkey-s-adaptation-to-artificial-intelligent-challenges-and-opportunities
  • TÜBİTAK. (2022). Yapay zekâ araştırma ve geliştirme stratejisi [Artificial intelligence research and development strategy]. TÜBİTAK Yayınları.
  • United Nations. (2022). E-Government survey 2022: The Future of digital government. United Nations Publications.
  • United Nations Department of Economic and Social Affairs. (2024). United Nations E Government Survey 2024: The future of digital government. United Nations. https://publicadministration.un.org/egovkb
  • Yang, J., & Lee, M. (2023). Smart city and remote services: The case of South Korea’s national strategic smart city program. Land, 14(5), 928. https://doi.org/10.3390/land14050928
  • Yayla, A., Świerczewska, K. S., Kaya, M., Karaca, B., Arayici, Y., Ayözen, Y. E., & Tokdemir, O. B. (2022). Artificial intelligence (AI)-based occupant-centric heating ventilation and air conditioning (HVAC) control system for multi zone commercial buildings. Sustainability, 14(23), Article 16107. https://doi.org/10.3390/su142316107
  • Yorgancıoğlu Tarcani, G., Yalçın Balçık, P., & Sebik, N. B. (2024). Türkiye ve dünyada sağlık hizmetlerinde yapay zekâ [Artificial intelligence in healthcare in Türkiye and the world]. Mersin Üniversitesi Tıp Fakültesi Lokman Hekim Tıp Tarihi ve Folklorik Tıp Dergisi, 14(1), 50–60. https://doi.org/10.31020/mutftd.1278529
There are 35 citations in total.

Details

Primary Language English
Subjects Other Fields of Education (Other), Public Administration
Journal Section Research Article
Authors

Tuğba Damgacı 0000-0002-7379-242X

Publication Date July 31, 2025
Submission Date June 26, 2025
Acceptance Date July 2, 2025
Published in Issue Year 2025 Volume: 15 Issue: ISRIS 2025

Cite

APA Damgacı, T. (2025). The future of public governance transition from e-government to a-government: A comparative analysis of Türkiye and Estonia. Ordu Üniversitesi Sosyal Bilimler Enstitüsü Sosyal Bilimler Araştırmaları Dergisi, 15(ISRIS 2025), 87-116. https://doi.org/10.48146/odusobiad.1728265

With the wish to be enlightened by the light of knowledge…
ODÜSOBİAD