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While early initiatives focused primarily on digitizing administrative procedures and
expanding online services, the concept of digital government has gradually evolved
beyond service digitization. Digital government emphasizes the use of integrated digital
platforms and data-driven decision-making to improve governance processes and policy
outcomes (Mergel et al., 2019). According to Mergel et al. (2019), digital transformation
in the public sector involves not only technological adoption but also significant changes
in organizational structures, administrative processes, and service delivery models.
Recent technological developments, particularly in artificial intelligence (AI), have
further accelerated this transformation. AI technologies enable governments to analyze
large datasets, automate administrative procedures, and improve public service delivery.
A systematic review by Zuiderwijk, Chen, and Salem (2021) highlights that AI can support
evidence-based policymaking and enhance administrative efficiency, although its
implementation also raises challenges related to data governance, organizational capacity,
and algorithmic accountability.
International organizations similarly recognize the growing role of AI in public
governance. The OECD (2025) argues that AI technologies are becoming a key driver of
the transition from digital government toward AI-enabled governance, where advanced
analytics support policy design and improve the efficiency of public services. At the same
time, the OECD emphasizes that successful AI adoption requires coordinated
development of digital infrastructure, data systems, and regulatory frameworks in order
to ensure transparency and accountability.
2.2. Artificial intelligence in the public sector: institutional and organizational
perspectives
Artificial intelligence has recently become an important topic in the study of digital
government and public sector transformation. In the context of digital governance, AI is
widely viewed as a technology capable of improving administrative efficiency, policy
analysis, and public service delivery (Wirtz et al., 2019). By processing large volumes of
data and identifying complex patterns, AI systems can assist governments in forecasting
socio-economic trends, detecting irregularities, and optimizing resource allocation.
Research also highlights the potential benefits of AI in improving government
performance. Zuiderwijk, Chen, and Salem (2021) show that AI applications in the public
sector can enhance data analytics capabilities and support evidence-based decision-
making. At the same time, the authors emphasize that implementing AI involves not only
technological innovation but also broader organizational and institutional challenges.
International organizations have likewise emphasized the importance of governance
frameworks in AI adoption. The OECD (2025) notes that the successful deployment of AI
in public administration requires appropriate regulatory frameworks, data governance
mechanisms, and institutional safeguards to ensure accountability and responsible use of
algorithms. Countries with higher levels of AI readiness typically possess stronger digital
infrastructures, well-developed innovation ecosystems, and policy environments that
support technological experimentation.
From an institutional perspective, the adoption of AI within government systems
depends on a combination of technological capacity, organizational capability, and
broader socio-economic conditions. Empirical studies provide evidence that these
institutional factors significantly influence governments’ ability to deploy advanced
technologies. For example, Iuga and Socol (2024) find that AI readiness among European

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