Artificial intelligence in public administration: a comprehensive literature review on opportunities, challenges and strategic implementation

Artificial intelligence (AI) has emerged as a pivotal force reshaping administrative practices across various sectors. This research consolidates insights from a comprehensive literature review on AI's applications in public administration, education, healthcare, agriculture, and management theories. Employing the PRIMSA method and utilizing the Web of Science database with keywords “artificial intelligence” and “administrative sciences,” the study aims to provide a nuanced understanding of how AI is transforming administrative landscapes. The chapter explores recent trends, challenges, and opportunities by analyzing a spectrum of studies, offering valuable implications for future research and practical implementations. The chapter systematically examines multifaceted applications of AI in different administrative domains, integrating findings from prominent studies.

Artificial Intelligence (AI) has become one of the most prominent topics in public policy and administration studies over the last years. Despite the attention to AI in this field isn’t entirely new, the universality of these group of technologies has radically increased the attention of scholars around the globe. This expansion of AI in the public sector entails the exploration of renovated foundations of analysis, not only to understand the novelty of these technologies, but also to connect these processes of adoption and implementation with other debates in public policy and administration. To do so, in this article we debate the need of an analytical framework of AI in the public sector based on the three levels of public administration: macro , meso , and micro . Also, we review the state-of-the-art in the field using the articles presented in the special issue on Artificial Intelligence and Public Administration: Actors, Governance, and Policy . Form here, we propose studying AI using a combination of macro , meso , and micro levels of public administration. We assume this will help to broadly apprehend how and why people, policies, and institutions interrelate with AI in public sector settings, and which effects can be expected from these processes in public administration.

Hepatocellular carcinoma (HCC) diagnosis mainly relies on its pathognomonic radiological profile, obviating the need for biopsy. The project of incorporating artificial intelligence (AI) techniques in HCC aims to improve the performance of image recognition. Herein, we thoroughly analyze and evaluate proposed AI models in the field of HCC diagnosis. A comprehensive review of the literature was performed utilizing MEDLINE/PubMed and Web of Science databases with the end of search date being the 30th of September 2023. The MESH terms "Artificial Intelligence," "Liver Cancer," "Hepatocellular Carcinoma," "Machine Learning," and "Deep Learning" were searched in the title and/or abstract. All references of the obtained articles were also evaluated for any additional information. Our search resulted in 183 studies meeting our inclusion criteria. Across all diagnostic modalities, reported area under the curve (AUC) of most developed models surpassed 0.900. A B-mode US and a contrast-enhanced US model achieved AUCs of 0.947 and 0.957, respectively. Regarding the more challenging task of HCC diagnosis, a 2021 deep learning model, trained with CT scans, classified hepatic malignant lesions with an AUC of 0.986. Finally, a MRI machine learning model developed in 2021 displayed an AUC of 0.975 when differentiating small HCCs from benign lesions, while another MRI-based model achieved HCC diagnosis with an AUC of 0.970. AI tools may lead to significant improvement in diagnostic management of HCC. Many models fared better or comparable to experienced radiologists while proving capable of elevating radiologists' accuracy, demonstrating promising results for AI implementation in HCC-related diagnostic tasks.

The rapid advancement of artificial intelligence (AI) technologies has profoundly transformed virtually all areas of human activity, and public administration is no exception. The integration of AI into public management systems opens up unprecedented opportunities to increase efficiency, transparency, and responsiveness in the provision of public services. This article examines the potential, challenges, and prospects of using artificial intelligence in public administration, focusing on ethical, legal, and organizational aspects. It emphasizes that AI tools—from data analytics and machine learning to natural language processing and automated decision-making systems—can significantly contribute to improving the quality of political planning, resource allocation, and citizen participation. Through predictive modeling, intelligent data processing, and real-time monitoring, AI enables evidence-based decision-making and strengthens the adaptability of public institutions to a dynamic socioeconomic environment. At the same time, the implementation of AI in public administration presents several complex challenges. Key issues include algorithmic bias, data protection violations, a lack of transparency regarding automated decisions, and insufficient digital literacy among public sector employees. The article emphasizes that without a clear ethical framework and appropriate regulatory mechanisms, the use of AI could exacerbate social inequalities and undermine citizens’ trust in government institutions. Therefore, the development of clear governance standards for the use of AI in the public sector is essential to ensure accountability, fairness, and human oversight in all decision-making processes. The study also analyzes international experiences in AI governance, particularly in the European Union, the United States, and leading Asian countries, and identifies best practices that can be transferred to national contexts. It argues that the strategic implementation of AI should be based on the principles of open government, inclusivity, and human-centered digital transformation. The article also emphasizes the need for continuous training and development measures for public sector employees to ensure competent use of AI-based tools and the interpretation of algorithmic results. In conclusion, it is concluded that artificial intelligence represents both a challenge and an opportunity for modern public administration. It can optimize administrative processes and strengthen democratic governance, but at the same time requires new legal safeguards, ethical standards, and institutional competencies. The success of integrating AI into public administration depends crucially on the balance between technological innovation and the protection of human rights, transparency, and accountability. The future of AI in the public sector therefore lies not solely in technological progress, but in the development of responsible and sustainable political strategies that align innovation with the public interest and democratic values.

Introduction: In recent years, the emphasis on leveraging technological innovations within educational frameworks has grown significantly. Among these innovations, the metaverse—an emerging digital environment—presents vast potential for revolutionizing medical education. This qualitative study set out to explore and delineate the specific ways in which the metaverse can be utilized within this context.Methods: A comprehensive literature review was conducted across several major English-language databases, including MEDLINE, CINAHL, Web of Science, Cochrane Library, Science Direct, Springer, ERIC, Emerald, Sage Journals, Wiley Online Library, Scopus, PubMed, and Google Scholar. The search encompassed records from their inception through September 2000 to March 2025. Data synthesis followed the meta-aggregation methodology outlined by the Joanna Briggs Institute (JBI), centering on qualitative studies focused on the role of metaverse in medical education.Results: Of the 194 studies reviewed, only 27 met the inclusion criteria and were included in the final analysis. The qualitative synthesis of these studies led to the identification and categorization of seven main themes: the use of emerging technologies in medical education, virtual learning environments, intelligent teaching methods, personalized learning, expansion of interactive spaces in medical education, intelligent student assessment mechanisms, and the development of medical strategies and foresight.Conclusion: Integrating emerging technologies such as the metaverse and artificial intelligence is fundamentally reshaping the landscape of medical education, offering immersive, personalized, and competency-based learning experiences. These innovations enhance engagement, collaboration, and decision-making and promote meaningful assessment and continuous professional development. Strategic implementation and evidence-based evaluation will be essential as the field advances to fully realizes its transformative potential in preparing future-ready healthcare professionals.

It is predicted that artificial intelligence may have serious impacts on the governance of the future. For this reason, all countries have started to make changes and transformations in public administrations in order to use artificial intelligence applications in the management of the future. In this context, it is known that countries have made significant investments in integrating artificial intelligence into public institutions. Research and theoretical studies show that the use of artificial intelligence and the competition for access to artificial intelligence will reach a better point than its current state. The versatility of AI also points to its various applications and use cases around the world. These include face recognition, automatic text correction, mapping and wayfinding, call centers, robotic systems, chatbots, financial markets, autonomous vehicles, recommendation algorithms, and digital voice assistants. In addition to these, pattern recognition for data prediction, pattern recognition for anomaly detection, classification of headlines and data according to similarities and differences, and text and image processing can be given as examples of artificial intelligence uses. In this framework, it is very important for countries to integrate into artificial intelligence applications by managing data at the national level. Because this situation will directly affect the future artificial intelligence management of countries positively or negatively; countries will be able to control the production-distribution-processing and data consumption of resources and this process with the use of artificial intelligence in the future. For this reason, the issue of integrating artificial intelligence into public administration and using its applications is very important and this constitutes the original value of this study. The aim of this study is to evaluate the use and impact of artificial intelligence applications in public administration. In the study, qualitative research method will be used, and a literature review will be conducted on the use of artificial intelligence in public administration. With the findings obtained, it is seen that the power of artificial intelligence has a power that can change the world and is a matter that should be taken into consideration. Therefore, it is important for countries to pay more attention to this issue in their future management policies. In this context, the areas of use of artificial intelligence in countries include issues such as red tape, efficiency, facilitating innovation in the field of artificial intelligence, artificial intelligence training for entrepreneurship, the development of new business areas, and expanding the use of artificial intelligence in government companies and compliance with. In this study, these issues are addressed; successful country practices are examined, and the opportunities and challenges created by the use of artificial intelligence applications in public administration are discussed. As a result, it is evaluated how the use of artificial intelligence has affected the public administration of countries and how it has improved their capacity areas.

Artificial Intelligence (AI) technologies in public administration are gaining increasing attention due to the potential benefits they can provide in improving governmental operations. However, translating technological opportunities into concrete public value for public administrations is still limited. One of the factors hindering this progress is the lack of AI capability within public organisations. The research found that various components of AI capability are essential for successfully developing and using AI technologies, including tangible, intangible, and human-related factors. There is a distinction between the AI capability to develop and the AI capability to implement AI technologies, with more administrations capable of the former but finding difficulties in the latter. A lack of in-house technical expertise to maintain and update the AI systems, legal challenges in deploying developed AI systems, and the capability to introduce changes in the organisation to ensure the system remains operational and used by relevant end-users are among the most critical limiting factors for long-term use of AI by public administrations. The research underlines the strong complementarity between historical eGovernment developments and the capability to deploy AI technologies. The study suggests that funding alone may not be enough to acquire AI capability, and public administrations need to focus on both the capability to develop and implement AI technologies. The research emphasizes that human skillsets, both technical and non-technical, are essential for the successful implementation of AI in public administration.

Artificial intelligence in public administration is critical for the modernization of the public sector and adaptation to the challenges of modern society. The paper analyzes studies dedicated to the impact of artificial intelligence on the efficiency, innovation, and transparency of management processes in the public sector using meta- and bibliometric analysis. The goal is to identify the main areas and keywords that highlight theoretical and practical aspects of artificial intelligence in public administration. In total, 879 scientific articles were analyzed, of which 598 works are devoted to artificial intelligence. Dynamic time analysis revealed a significant surge in scientific interest in artificial intelligence in public administration: from 2010 to 2019, 135 publications were devoted to this issue, and from 2020 to 2024, 421. Bibliographic maps of keywords and publication maps showed the main thematic areas of research on artificial intelligence: the application of AI in public administration and the public sector, decision-making in public administration, data management and digital technologies in public administration, and the strategic use of AI to forecast socio-economic trends.The obtained data became the basis for expanding the scientific and practical potential of using artificial intelligence in public administration. The main areas of future research will concern the regulation of ethical issues to ensure the trust of citizens, the development of a regulatory framework and standards, increasing the efficiency of public services, the integration of artificial intelligence into strategic planning, and the use of artificial intelligence to achieve sustainable development goals. AcknowledgmentThe analysis was carried out within the framework of the implementation of the perspective plan for the development of the scientific area “Social Sciences” of Sumy State University, number d/r 0121U112685.

The article is devoted to the study of the phenomenon of rapid transformation of the world, which is artificial intelligence (AI). It is noted that the aforementioned is due to the ability of AI to accelerate innovation, change economic processes, influence the ways in which people interact with technology, and open up new prospects for the development of humanity. It is noted that in recent years, unprecedented rates of AI implementation have been observed in key areas of life, which allows for significant changes in the labor market, scientific research, social communications, global security and the economy. Attention is focused on the successful implementation of AI in the military sphere, which in the current conditions of an undeclared war against the Russian Federation is extremely important, since this helps to properly ensure national security. Examples of the use of AI in various spheres of life in Ukraine are given, including public management, administration, and control, which helps to perform complex tasks and make decisions based on data analysis, and such use of AI will become increasingly widespread and significant. The integration of AI into public administration, in particular, will help to analyze regulatory and legal acts and translate European legislation. It is very important that digital expertise of regulatory and legal acts will be carried out thanks to AI tools. And in the future, of course, all these solutions can be scaled for the work of the government as a whole. Digital technologies, especially AI, are the future of digital governments. Ukraine has already established itself as a powerful player in the field of technology, and is now taking other important steps in the development of artificial intelligence. At the same time, attention is drawn to the fact that, along with the above-mentioned positive aspects of AI, concerns have been expressed in the world about the existence of a danger of the introduction of AI, the emergence of a potentially catastrophic risk for humanity. This is confirmed by the signing of the Bletchley declaration (November 1–2, 2023, Great Britain) on the first day of the Artificial Intelligence Security Summit organized by the British government, according to which countries agreed to work together on AI security research. It was emphasized that the summit participants focused on the need for appropriate international efforts to study and address the potential impact of AI systems, as well as recognizing that the protection of human rights, transparency and clarity, fairness, accountability, regulation, safety, appropriate public oversight, ethics, bias mitigation, privacy and data protection require urgent attention. It is noted that the above requires appropriate knowledge and consideration of advanced European experience in this area and an appropriate vision of AI. For this purpose, we will analyze the content of the scientific article by Oriol Mir Puigpel “The Impact of the AI Law on Public Authorities and Administrative Procedures”. The said Law (Regulation) will have an impact on automated decision-making by public authorities throughout Europe. In addition, Member States may supplement its provisions with their national acts on administrative procedure, which will positively affect the creation of a regulatory framework and the use of artificial intelligence systems by European public authorities. It is noted that the Law aims to guarantee the free movement of artificial intelligence systems with equal application to entities of different forms of ownership. In this case, public authorities are usually considered “users”. At the same time, they will also be “suppliers” if they develop their own AI systems themselves or purchase an individual AI system. The Law prohibits certain AI systems and imposes numerous obligations on suppliers and, to a lesser extent, on users of high-risk systems, and defines four levels of risk for AI systems. The Law’s impact on EU and Member State public authorities when using or developing AI systems is disclosed, and their respective responsibilities are also defined.

Artificial Intelligence (AI) implementation in public administration is gaining momentum heralded by the hope of smart public services that are personalised, lean, and efficient. However, the use of AI in public administration is riddled with ethical tensions of fairness, transparency, privacy, and human rights. We call these AI tensions. The current literature lacks a contextual and processual understanding of AI adoption and diffusion in public administration to be able to explore such tensions. Previous studies have outlined risks, benefits, and challenges with the use of AI in public administration. However, a large gap remains in understanding AI tensions as they relate to public value creation. Through a systematic literature review grounded in public value management and the resource-based view of the firms, we identify technology-organisational-environmental (TOE) contextual variables and absorptive capacity as factors influencing AI adoption as discussed in the literature. To our knowledge, this is the first paper that outlines distinct AI tensions from an AI implementation and diffusion perspective within public administration. We develop a future research agenda for the full AI innovation lifecycle of adoption, implementation, and diffusion.

Artificial intelligence encompasses a wide range of approaches, methodologies, and techniques aimed at mimicking human intelligence in machines. In recent times, the concepts of Generative Artificial Intelligence (AI), Super AI, and Narrow AI have attracted considerable attention. Undoubtedly, the success of ChatGPT in capturing all attention has played a significant role in this. Artificial intelligence technology has a profound impact on all sectors, and sector representatives are striving to adapt to this technology more quickly. It is projected that artificial intelligence could generate an economic size of 13 trillion American dollars by 2030. Developments in artificial intelligence technologies undoubtedly lead to significant improvements in the functioning of public institutions and access for citizens. Artificial intelligence has the potential to be used in many public services, including security and defense, healthcare services, education, transportation and infrastructure, environmental and natural resource management, law and justice systems, among others. Therefore, evaluating the types of artificial intelligence, Narrow AI applications, and chatbots for public use is seen as highly beneficial from the perspective of public administration and the public sector. In our study, the topics of super artificial intelligence, generative artificial intelligence, narrow artificial intelligence, and chatbots have been extensively evaluated within the context of the public sector and public administration. Utilizing findings from both Turkish and English literature reviews, the importance and potential impacts of artificial intelligence within the public sector, along with current trends, have been comprehensively assessed. This research delves into the concepts of artificial intelligence and its subsets—super AI, generative AI, narrow AI, and chatbots—within the general framework of the public sector. China and the United States are pioneering and leading countries in terms of investment. Although the U.S. stands out in many areas regarding investment, China's integration of artificial intelligence with national strategies and its policies indicate that it may play a more dominant role in the future. There are four main implementation areas of artificial intelligence in the public sector: efficiency and automation, service delivery, data-driven governance, and ethical and regulatory challenges. A review of the literature reveals that the ethical, legal, and social implications of implementing artificial intelligence in the public sector require more careful consideration. The study makes a significant contribution to the field of artificial intelligence discussions in public administration and the public sector, providing a comprehensive assessment of current discussions on artificial intelligence in the literature.

Artificial Intelligence (AI) implementation in public administration is gaining momentum, heralded by the hope of smart public services that are personalized, lean, and efficient. However, the use of AI in public administration is riddled with ethical tensions concerning fairness, transparency, privacy, and human rights. We refer to these as AI tensions. The current literature lacks a contextual and processual understanding of AI adoption and diffusion in public administration to explore such tensions. Previous studies have outlined risks, benefits, and challenges with the use of AI in public administration. However, a significant gap remains in understanding AI tensions as they relate to public value creation. Through a systematic literature review grounded in public value management and the resource-based view of the firm, we identify technology-organisational-environmental (TOE) contextual variables and absorptive capacity as factors influencing AI adoption. This paper outlines distinct AI tensions from an AI implementation and diffusion perspective within public administration. We develop a future research agenda for the full AI innovation lifecycle of adoption, implementation, and diffusion.

The study explores the use of automation and artificial intelligence (AI) in public administration and its potential benefits and constraints for government organizations. It discusses how automation and AI can revolutionize public administration by improving productivity, effectiveness, and service quality. The study provides an overview of automation and AI technologies, highlighting their strengths and weaknesses. It identifies key areas where automation and AI can be integrated into public administration, including policymaking, service delivery, decision-making, and citizen engagement. The advantages of using automation and AI in public administration are examined, such as data-driven policy decisions, streamlined administrative procedures, and enhanced service delivery through AI-powered chatbots and virtual assistants. Ethical considerations, privacy concerns, and job displacement are also addressed, proposing methods for ensuring ethical and equitable application of automation and AI. The study includes case studies from different countries that demonstrate successful applications of automation and AI, showcasing increased citizen involvement, transparency, and improved government services. It concludes by emphasizing the importance of strong leadership, collaboration between governmental organizations and technical experts, and ongoing research and development to maximize benefits and minimize risks. The study aims to provide insights and recommendations for policymakers, administrators, and researchers, contributing to the knowledge base on AI and automation in public administration.

Artificial Intelligence (AI) is playing an increasingly important role in public administration, offering innovative solutions for efficiency and better public services. The application of AI in public administration aims to modernise and streamline the services offered to citizens. AI contains advanced algorithms, neural networks, and machine learning techniques to improve performance and efficiency over time. Smart algorithms, responsibly implemented, could help governments enhance service delivery and strengthen citizen engagement in local, city, regional, and national administrations around the world. Governments in some states have discreetly launched pilot programs to test developing AI applications, demonstrating an enthusiasm for technology at least as great as that in the private sector. By utilising AI, public administrations can automate repetitive processes, optimize resource usage, and improve interaction with the public. The purpose of the research is to show the extent and scope that AI tools integrated into organisations have in almost all areas of the public and private sectors in general, and state administrations in particular. The research objectives were: to analyse the dynamics of investments in AI tools; to discover the main services in state administrations that can be better performed using AI; to analyse the risks; and to highlight the perspective of development and integration of AI in public administrations of a few European states. The research is based on a comparative analysis of the implementation of AI tools across fields, components, and regions at the European level mainly, but also for Romania. The analysis period is 2021-2030. The results show a continuously increasing trend and an ever-faster rate of assimilation of AI tools in the field of public administration in an increasing number of states from most developed regions worldwide.

International development institutions, United Nations agencies, and non-governmental organizations (NGOs) generate vast quantities of unstructured qualitative data, including narrative reports, field interviews, focus group summaries, and policy documents. Despite the significant financial investments in producing this data—NGOs alone disbursing over US$23 billion annually—its potential remains underutilized due to the lack of scalable analytical methods. Traditional qualitative analysis approaches, such as content analysis, thematic analysis, narrative analysis, discourse analysis, and grounded theory, are resource-intensive, time-consuming, and often unsustainable at the scale required. Artificial Intelligence (AI) offers a promising alternative by enabling automated or semi-automated analysis of large datasets, enhancing efficiency, reliability, and the breadth of insights generated. This literature review examines the application of AI in analyzing unstructured qualitative data, focusing on its use in healthcare, social sciences, and policy research. AI techniques, including natural language processing (NLP), sentiment analysis, clustering, topic modeling, and pattern recognition, have demonstrated potential to replicate human-led content analysis outcomes in significantly reduced timeframes. For instance, in healthcare research, AI has been used to analyze chronic pain narratives and COVID-19-related qualitative datasets, often achieving results comparable to human analysis but with enhanced speed. Similarly, in education and social science contexts, AI tools such as Python’s SpaCy have processed thousands of open-ended survey responses, enabling meaningful interpretation at scale. The review identifies several advantages of AI-enabled analysis. These include substantial time and cost savings, reduced analyst fatigue, improved coding accuracy, and the ability to conduct more comprehensive literature reviews and thematic explorations. AI also supports iterative and reflexive analysis, expanding the possibilities of theory development and data visualization. Such capabilities make AI particularly attractive to institutions with limited analytical resources yet large volumes of qualitative data. Nonetheless, limitations persist. AI struggles with nuanced interpretation, including detecting sarcasm, cultural references, and subtle thematic variations. Ethical concerns—ranging from data privacy to algorithmic bias—remain critical considerations. Reliability issues, “hallucinations” in generative AI outputs, and reduced interpretive depth compared to traditional qualitative methods underscore the need for cautious application. Studies suggest that deductive AI setups may outperform inductive approaches, but human reflexivity, contextual knowledge, and interpretive judgment remain indispensable. A recurring theme across the literature is the advocacy for hybrid analytical models where AI augments rather than replaces human expertise. In such models, AI serves as a rapid pattern-detection and preliminary coding tool, allowing human analysts to focus on higher-order interpretation and critical inquiry. This approach can maximize efficiency while preserving the depth and contextual sensitivity that define rigorous qualitative research. The paper concludes that AI holds transformative potential for the analysis of unstructured qualitative data, particularly for organizations in development, health, and policy sectors. Realizing this potential requires sustained collaboration between institutions, academia, and the private sector to refine methodologies, test across diverse datasets, and address ethical and reliability challenges. Furthermore, generational differences in AI adoption—where younger researchers are more inclined toward AI use—suggest opportunities for targeted capacity-building initiatives. By strategically integrating AI into qualitative workflows, stakeholders can unlock greater value from existing data, inform decision-making, and enhance the inclusivity and scope of research insights.