Triple helix model and artificial intelligence in public administration

Androniceanu, Armenia (author), Colesca, Sofia Elena (author)

Although the Triple Helix model has been widely analysed in the context of innovation ecosystems, its contribution to fostering the adoption of artificial intelligence (AI) within public administration remains insufficiently explored. This study addresses this research gap by examining how interactions among universities, industry, and government facilitate AI integration into digital governance across selected EU countries. Purposes: The main research objectives are to: (a) assess the digital maturity of the selected EU countries; (b) evaluate how Triple Helix interactions shape AI adoption in public administration; (c) analyse the interrelationships among the three actors within the context of AI governance; and (d) explore the connections between each country’s AI strategy and its broader governance mechanisms. Design/Methodology/Approach: The research combines both quantitative and qualitative methods, utilizing data from AI Watch, the European Commission, Eurostat, Oxford Insights, and the OECD. Findings: The findings reveal significant disparities among the selected EU member states and identify critical factors that either facilitate or constrain AI integration within public administration, offering new insights into the evolving role of the Triple Helix model in the era of algorithmic governance. Practical Implications: The results are particularly relevant for public sector decision-makers, researchers in governance and innovation studies, and policymakers seeking sustainable models for digital transformation and collaborative innovation. Originality/Value: This research presents the first cross-national empirical study linking Triple Helix dynamics to AI-driven innovation in the public sector, incorporating a range of indicators. The originality of this research lies in its conceptual integration of the Triple Helix framework with the transformative capacities of artificial intelligence in reconfiguring public governance and innovation dynamics within a few EU countries.

• Language: English
• Keywords: Triple Helix model, artificial intelligence, public administration, innovation ecosystems, European Union, comparative analysis, digital transformation, digital governance
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FU - Faculty of Administration
• Publication status: Published
• Publication version: Version of Record
• Year: 2025
• Number of pages: Str. 63-91
• Numbering: Vol. 23, no. 2
• PID: 20.500.12556/RUL-176860
• UDC: 35:004.8(4-6EU)
• ISSN on article: 2591-2240
• DOI: 10.17573/cepar.2025.2.03
• COBISS.SI-ID: 257934339
• Publication date in RUL: 11.12.2025

Record is a part of a journal

• Title: Central European public administration review
• Shortened title: CEPAR
• Publisher: Fakulteta za upravo
• ISSN: 2591-2240
• COBISS.SI-ID: 293849600

Licences

• License: CC BY-SA 4.0, Creative Commons Attribution-ShareAlike 4.0 International
• Link: http://creativecommons.org/licenses/by-sa/4.0/
• Description: This Creative Commons license is very similar to the regular Attribution license, but requires the release of all derivative works under this same license.

Secondary language

• Language: Slovenian
• Title: Model trojne vijačnice in umetna inteligenca v javni upravi

Abstract

Čeprav je model trojne vijačnice široko analiziran v kontekstu inovacijskih ekosistemov, je njegov prispevek k spodbujanju uvajanja umetne inteligence (UI) v javni upravi premalo raziskan. Ta študija zapolnjuje raziskovalno vrzel z analizo, kako interakcije med univerzami, industrijo in vlado pospešujejo vključevanje UI v digitalno upravljanje v izbranih državah EU. Nameni: glavni raziskovalni cilji so: (a) oceniti digitalno zrelost izbranih držav EU; (b) ovrednotiti, kako interakcije v okviru trojne vijačnice oblikujejo sprejemanje UI v javni upravi; (c) analizirati medsebojna razmerja med tremi akterji v kontekstu upravljanja UI; ter (d) raziskati povezave med nacionalno strategijo za UI posamezne države in njenimi širšimi mehanizmi upravljanja. Načrt/metodologija/pristop: raziskava združuje kvantitativne in kvalitativne metode ter uporablja podatke AI Watch, Evropske komisije, Eurostata, Oxford Insights in Organizacije za gospodarsko sodelovanje in razvoj (OECD). Ugotovitve: rezultati razkrivajo pomembne razlike med izbranimi državami članicami EU in opredeljujejo ključne dejavnike, ki bodisi omogočajo bodisi omejujejo vključevanje UI v javno upravo, pri čemer ponujajo nove vpoglede v razvijajočo se vlogo modela trojne vijačnice v dobi algoritmičnega upravljanja. Praktične implikacije: rezultati so posebej relevantni za odločevalce v javnem sektorju, raziskovalce s področja upravljanja in inovacijskih študij ter za oblikovalce politik, ki iščejo trajnostne modele za digitalno preobrazbo in sodelovalne inovacije. Izvirnost/vrednost: gre za prvo čeznacionalno empirično študijo, ki povezuje dinamiko trojne vijačnice z inovacijami, ki jih poganja UI, v javnem sektorju ob upoštevanju niza kazalnikov. Izvirnost raziskave je v konceptualni integraciji okvira trojne vijačnice s preoblikovalnimi zmožnostmi umetne inteligence pri preoblikovanju javnega upravljanja in inovacijskih dinamik v nekaterih državah EU.

• Keywords: model trojne vijačnice, umetna inteligenca, javna uprava, inovacijski ekosistemi, Evropska unija, primerjalna analiza, digitalna preobrazba, digitalno upravljanje

Projects

• Funder: Other - Other funder or multiple funders
• Name: The impact of artificial intelligence in public administration and algorithmic governance of human resources in the digital age: opportunities and challenges