The Future of Government Management: How AI will Transform the Form and Functions of Government Agencies



This article explores the growing influence of artificial intelligence (AI) in public administration, focusing on its impact in European countries. As AI gains popularity in various sectors, it is also making inroads into the public sector, transforming traditional bureaucratic processes into technology-driven systems. The research delves into how AI is reshaping the structure and functions of government agencies, posing new challenges.

The paper begins by providing an overview of AI technologies and their current perspectives. It then examines case studies of AI integration in government agencies and the resulting implications. The study concludes with an in-depth discussion of the challenges and transformations brought about by AI adoption, emphasizing the potential benefits for developing nations striving to enhance their public sector services. The paper also underscores the significance of a well-crafted national AI strategy in optimizing public sector operations and fostering innovation in government administration. While AI is still in its early stages of application, it is evident that this technology offers substantial advantages for both organizations and society as a whole.

Introduction

The fact of growing popularity of the use of artificial intelligence (AI) can hardly be questioned nowadays. More and more often there are news that some company has implemented an AI-solution that has allowed it to significantly improve its efficiency, attract new customers or enter a new market. According to Grand View Research, the volume of the AI market is already estimated at more than $ 136 billion, and the projected average annual growth rate until 2030 is set to be 37.3 % [1]. It is noteworthy that AI is most often seen as an innovative approach in the business environment, but what if we look at it as a tool of effective public administration, as a way to modernize the traditional bureaucratic format of the work of state bodies into progressive technology-driven processes.

Nowadays, there are already cases of the introduction of AI tools in the work of government agencies in different countries. The fields of application of this approach are diverse. The scale and goals of the use of AI in the public sector may differ. For example, the development and implementation of a decision–making system for providing protection to refugees is a much more complex and complex task than expanding the use of digital public services through predictive analytics [2]. However, regardless of the approach, the state faces a number of barriers and restrictions, leveling which it adapts modern AI technologies to state specifics, inevitably changing the forms and functions of state bodies at the same time. This article will examine the experience of using AI in public administration in European countries and how this practice has affected the structure of the public sector.

Problem Statement: The widespread integration of artificial intelligence into government management raises a multitude of specific questions, such as concerns about data privacy, cybersecurity, and ethical decision-making, alongside practical challenges related to training staff and development of AI applications. One of the central issues involves deciphering how AI will reshape the organizational structure and functions of government agencies in the future.

Purpose of the article: The purpose of this article is to study the impact of artificial intelligence on the form and functions of public institutions today and in the future and the challenges they may face, based on the experience of implementing this approach in European countries.

This paper is structured as follows: the subsequent section furnishes an exposition on AI technologies, encompassing contemporary perspectives. Section 2 delves into recent exemplars of artificial intelligence integration within governmental agencies and their associated repercussions. The concluding section entails a comprehensive discussion concerning the challenges and transformations linked to the adoption of AI, culminating in final conclusions.

AI technologies: modern perception

Despite the fact that the term «artificial intelligence» appeared in the middle of the 20th century, today there are still disputes about the definition of this concept. However, the vast majority of researchers associate artificial intelligence with the ability of machines to simulate human intelligence and skills. So, back in 1966, Marvin Minsky defined artificial intelligence as «[...] the science of how to make machines do things that would require intelligence if performed by humans» [4]. Stephen Finley understands artificial intelligence as «reproduction of human analytical abilities and/or decision-making capabilities» [5]. Speaking about artificial intelligence systems, it would be reasonable to refer to the definition fixed in the European Law on Artificial Intelligence: «artificial intelligence system means a system that is designed to operate with elements of autonomy and that, based on machine and/or human-provided data and inputs, infers how to achieve a given set of objectives using machine learning and/or logic- and knowledge based approaches, and produces system-generated outputs such as content (generative AI systems), predictions, recommendations or decisions, influencing the environments with which the AI system interacts».

Artificial intelligence technologies are quite diversified. For the convenience of distinguishing them, it is common to divide them into three categories: Artificial Superintelligence, General AI and Narrow AI. Artificial superintelligence pertains to technological progress that surpasses the limitations of human intelligence, a concept that currently remains highly futuristic. General AI refers to systems that have forms of intelligence similar to humans. Finally, a narrow AI is about creating and using a system that performs a specific task or group of tasks more efficiently than a person — for example, analyzes large data sets in a short time (which would be impossible for humans due to limited brain resources) [2]. The article will focus on narrow AI used in public administration, since the first two categories are not matured and not suitable for full-scale use.

Despite the fact that most of the AI techniques still demonstrate relatively high level of inaccuracies and mistakes across the developed predictions and solutions, many companies and government agencies show a significant interest towards implementation of these technologies in their work. However, the use of AI in public administration is associated with a number of risks and limitations, the key of which is the regulatory framework. Government institutions tend to be much less flexible and experimental if comparing with private companies. This fact is explained by the regulatory framework that defines numerous restrictions and limitation on the procedures and technical tools that can be used. Previously, the use of modern technologies such as artificial intelligence in the public sector was limited and experimental, but today we can already talk about full automation of processes and the use of complex artificial intelligence technologies, as governments understand the importance of this initiative and improve the current legal regulation. For instance, in 2017, German government introduced a new legal regulation regarding the automation of processes that enabled full automation of all administrative procedures with the exception of individual cases [3]. Through the illustration of Germany and several other European countries, this paper will delve into instances where government agencies employ AI solutions and assess the consequential effects of such innovations.

Recent instances of artificial intelligence integration in government agencies and their concomitant effects

Europe is certainly one of the leaders in the application of modern technologies, including artificial intelligence. An important sign of this leadership can be seen in the adoption of a state-level plan for the development and use of artificial intelligence. Many European countries have implemented National AI strategies, as shown in Table 1.

Table 1

Overview of national AI strategies in Europe

№	Country	Published Date
1	Bulgaria	December 2020
2	Czech Republic	May 2019
3	Denmark	March 2019
4	Estonia	May 2019
5	Finland	June 2019
6	France	March 2018
7	Germany	November 2018
8	Latvia	February 2020
9	Lithuania	April 2019
10	Luxembourg	May 2019
11	Malta	October 2019
12	Norway	January 2020
13	The Netherlands	October 2019
14	Poland	December 2020
15	Portugal	April 2019
16	Russia	October 2019
17	Slovenia	May 2021
18	Spain	December 2020
19	Sweden	May 2018
20	United Kingdom	April 2018

Source: JRC — European Commission, own analysis

These strategies define the vector of each country’s development and the expected role of AI technologies in it. Such documents usually contain plans, standards, requirements and restrictions related to the AI development process in the country. These strategies play an important role because they allow countries to set a vector for the development of the implementation of AI solutions in both the private and public sectors as well as contribute to informing citizens about the importance of this area of public policy.

In the subsequent discussion, illustrations of artificial intelligence applications within the public sector will be elucidated, focusing on European nations that have embraced a national AI strategy while exhibiting divergent technological foundations.

Denmark

The Danish government is committed to orienting public administration towards the use of artificial intelligence and ensuring that world-class services are provided to citizens. The country's strategy highlights three key development vectors — using AI to improve services, maintaining responsible use of AI, and ensuring that government agencies use AI for data-driven decision-making.

Federal, regional and local government agencies in Denmark are already using artificial intelligence. For example, this technology is used to fill out application forms, customer support calls, billing, etc. This saves time for both civil servants and recipients of services [7].

In addition, data-driven traffic management is also practiced in Copenhagen. In conditions of large city traffic jams, it allows the Danish traffic control center to respond promptly to the changing road situation, optimize traffic flows, as well as reduce travel time, thereby reducing emissions into the atmosphere [8].

Another illustrative example of using an AI approach is predictive policing, in which historical data on criminal acts is used to predict future crimes [9].

The Netherlands

The Dutch government is aware of the enormous potential of AI development and use in both the private and public sectors, as described in its national strategy on artificial intelligence, including the statement that AI is a technology that will «transform the world» [11, 13]. As for the potential of the AI usage in public sector, there is a whole section in the strategy devoted to the use of AI by government agencies. It says that using this approach will solve many social problems and optimize processes in government agencies.

Effective communication, openness and unity can be considered as key factors for the development and use of AI in public administration in the Netherlands. For example, it is common to establish public-private partnerships to develop and expand internal expertise in AI. In addition, meetings are held with regional authorities in order to exchange experience and useful practices of using AI in their activities, hackathons and training courses are organized, special research laboratories are created, etc.

In the future, it is planned to actively implement various AI solutions in such areas of state activity as security and justice, defense, healthcare, agriculture [11]. Moreover, to date, many pilot projects on the use of AI technology have already been launched. For example, some government organizations use intelligent text analysis in order to simplify work in archives and document management in general, a number of government agencies are experimenting with the use of blockchain and artificial intelligence in procurement, and such structures as the police and the Netherlands Agency for Entrepreneurship are developing special chatbots designed to optimize their activities [13].

Germany

Since the introduction of the national AI strategy, many projects have been implemented in Germany with the use of this technology. In addition, great importance is given to AI research — Germany is one of the world leaders in the number of scientific publications on AI [12] It is noteworthy that the strategy has a separate section dedicated to the use of AI for solving government tasks, including describing the risks and limitations, as well as the issues of optimizing the regulatory framework connected with AI implementation.

Considering this, the German Federal Government is creating new structures and systems to monitor the impact of AI on work and society. These will be used to ensure sustainable and responsible development and the use of AI for the benefit of citizens. This involves, among other things, the increased implementation and establishment of a number of AI projects, both by the government and private organizations [10].

For example, German governmental agencies are strategically embracing AI to significantly advance their data infrastructure and drive AI systems development. Notable initiatives such as mCloud, Mobility Data Marketplace (MDM), Smart Data Innovation Lab (SDIL), and the Research Data Centre (FDZ) play pivotal roles in facilitating data access, sharing, and fostering research with AI applications. These initiatives collectively contribute to Germany's commitment to harnessing the power of AI for diverse purposes within the public sector [11].

Italy

One of the Italian government’s objectives in public sector is development of AI-based services [15]. In this context, the national AI strategy notes the great potential of the Italian AI ecosystem and at the same time the lack of its full realization.

In order to realize all the possibilities of the AI ecosystem, the Italian government sets goals for investing in key areas of AI development, one of which is the implementation of AI and its applications both in public administration and in the Italian economy as a whole [11, 15]. This includes:

— development of integrated datasets in order to create national data lake, supporting AI startups to find innovative solutions for the development of public administration;

— creation of a structured base of digital datasets of Italian documents for the development of AI solutions;

— building a structured data base in Italian for developing effective AI solutions;

— using big data and AI-based analytics to process citizen feedback and improve public services;

— Development of datasets based on satellite information and digitization of land cadaster;

— Implementation of technologies based on artificial intelligence for cross-authority interaction.

These initiatives will make a big step towards the efficient use of data collected by the government, as well as provide citizens with high quality services.

Ireland

One of the key directions of AI development in Ireland in accordance with the AI development strategy is to improve the quality of public services through the introduction of AI solutions. In Ireland, some services are already leveraging artificial intelligence, but the current goal is to scale the implementation of this approach in the field of public administration. Much attention is paid to the creation and development of an «open» environment aimed at accelerating the development of new AI solutions for the public sector, including through the organization of hackathons and special seminars. A considerable role is assigned to the development of talents and the building up of expertise in the public service [11, 14].

At the same time, there is already the use of AI in various areas of the public sector. For example, Department of Agriculture, Food and the Marine of Ireland in collaboration with IBM, harnessed artificial intelligence and machine learning to develop a predictive model that made it possible to detect bovine tuberculosis infection risk at the individual animal level. By analyzing extensive datasets from the Irish Animal Health Computer System, the model accurately identified the infection status of over 10,940 test-positive cattle and 2,114,368 test-negative cattle, offering a valuable tool for veterinarians to manage and mitigate the disease's impact, potentially saving cattle lives, safeguarding farmers' livelihoods, and reducing the national bovine tuberculosis infection eradication program's substantial costs [14].

Another example is The Health Service of Ireland, using artificial intelligence and natural language processing to automatically extract structured information from unstructured clinical notes in the Kidney Disease Clinical Patient Management System. This streamlines clinical audits, increases quality of research and reduces operational costs and time. The project aims to improve healthcare outcomes for kidney failure patients and support the development of a national renal registry [14].

Discussion of challenges and changes associated with AI adoption

The experience of European countries shows that AI-based solutions can be developed and successfully applied in the public sector and government agencies, bringing benefits both in terms of optimizing and automating internal processes and improving the quality of work with clients — citizens and organizations using public services.

However, implementing AI solutions in the public sector is not the same as doing it in private organizations, because, as noted earlier, they are not as flexible. In addition, the State is entrusted with such functions as the safety of citizens and ensuring respect for fundamental rights. In this context, the introduction of any «artificial» systems should be carried out with special attention.

The main limitations in the implementation of AI solutions in the field of public administration can be divided into 5 categories: organizational, technological, legal, ethical and personnel (see Table 2).

Table 2

Categories of constraints in the implementation of AI solutions in the public sector

Name of the Constraint	Description of the Constraint
Organizational	The complexity of integrating artificial intelligence into complex hierarchical structures of government agencies and patterns of established interactions
Technological	Constraints in access to modern technologies and the lack of the necessary infrastructure for the effective implementation of artificial intelligence
Legal	Adherence to data processing laws and transparency regulations can pose limitations on the use of AI within government agencies
Ethical	Government bodies must consider ethical issues related to citizen privacy and the potential for bias in AI algorithms
Personnel	The shortage of AI experts and the need to train personnel to work with these technologies can create staffing constraints when implementing AI in government agencies

Source: JRC — European Commission, own analysis

Depending on the country, different restrictions may take different weights. For example, Italy and Ireland place great emphasis on human resources in their AI development strategies, since the human capital in terms of research, development and implementation of AI solutions in them is not as developed as other areas [14, 15]. Other countries such as Denmark and Netherlands are actively raising the issue of ethics of AI-based systems [11]. These factors reflect the complexity of implementing large AI solutions in government structures and explain why sometimes quick wins are prioritized over long-term large-scale [11].

Nevertheless, active implementation of artificial intelligence in government agencies may affect their structure and functionality. This can be explained by the necessity for active and open cooperation between government agencies and other companies, the growing number of scientific and public laboratories, changes in the usual functional tasks of civil servants, etc. The experience of advanced countries reviewed in this article demonstrates the importance of maintaining the principles of unity and openness while developing and implementing artificial intelligence related decisions in their operations. Effective communication and openness, both in terms of sharing experiences and discussing common ideas, and in terms of technological integration with representatives of other authorities, industry experts or researchers is a key factor in the success of the implementation and functioning of an AI.

In addition, such relations between the public and private sector increase citizens' trust in both the government and AI technologies in general. Increasing citizens' trust serves as an important benchmark for many countries. After all, if citizens are not ready for an AI implementation, fearing, for example, data leakage, the effectiveness of its use will be low and its security will be in doubt. Therefore, it is essential to effectively manage the relationship with citizens, educate and immerse them in the new technological way of life, while respecting the principle of unity and openness.

The issue of normative regulation necessarily also arises when we talk about any innovations. Being one of the limitations (legal restrictions), it requires detailed consideration, which is also noted in a number of strategies [7, 10,11, 14, 15]. Public authorities spend significant resources on developing legislation aimed at providing citizens' safety, clarifying the processes of implementing AI-based systems in public administration, etc. As a result, the legal basis for the functioning of an organization is gradually changing, as well as the specifics of its work when interacting with other organizations or citizens.

All these changes have been taking place for a long time, they are strategic in nature, but today we already observe how countries are fulfilling their strategies in the area of artificial intelligence and implementing AI-based technologies in the public sector. More importantly, these innovations are not implemented in vain, but with real impact and value, improving the quality of services and processes and making people's lives better and safer

Conclusion

Every year AI is gaining more and more popularity, appearing in the lives of people in various fields. With less intensity and flexibility, but it also penetrates into the public sector, inevitably changing the specifics of work there, while introducing innovative solutions based on artificial intelligence.

Advanced European countries are fully aware of AI's potential and are making significant efforts to become proficient in its utilization. Among other things, the development of strategies that define the vector of development of this technology, and the documents and projects resulting from them. Practice shows that AI solutions can be successfully integrated into the work of government agencies, but taking into account a number of principles (unity, openness, trust of citizens, effective communication) and limitations (organizational, technological, legal, ethical, personnel).

Based on an analysis of the experiences of European countries, it can be concluded that with a well-devised national AI strategy, significant benefits can be realized within the operations of the public sector. In this context, substantial potential emerges for developing countries, where the quality of government services or internal processes within governmental bodies may not be at the highest level. Artificial intelligence not only facilitates the optimization of specific services or processes but also enhances the overall model of public sector operations by altering approaches to communication and technology management.

At present, the application of AI solutions in public administration is in its early stages of development. This trend has its own specifics and risks and requires detailed research and development. What is clear for sure is that AI is of great benefit and value, being a concrete advantage not only of individual organizations, but also of society and the states as a whole.

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