The impact of artificial intelligence on public administration in America

Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17283672 146 ISRG PUBLISHERS Abbreviated Key Title: Isrg J Econ Bus Manag ISSN: 2584-0916 (Online) Journal homepage: https://isrgpublishers.com/isrgjebm/ Volume – III Issue -V (September-October) 2025 Frequency: Bimonthly The impact of artificial intelligence on public administration in America DR. Khaireya Redwan Yahya Al-Istiqlal University, Jericho, Palestine | Received: 23.09.2025 | Accepted: 29.09.2025 | Published: 07.10.2025 *Corresponding author: DR. Khaireya Redwan Yahya Al-Istiqlal University, Jericho, Palestine INTRODUCTION From policy-making to service delivery, artificial intelligence (AI) is today an integral part of the contemporary government, affecting most aspects of public administration. In an attempt to streamline the system, enhance decision-making, and optimize the use of resources, United States government agencies increasingly rely on artificial intelligence technology. On the other hand, its rapid integration has raised genuine questions in terms of ethical issues, transparency, and substitution of human labor (Nader & et al, 2024). Figure 1 shows A Comprehensive Review of Artificial Intelligence’s Impact on Decision-Making according to (Caiza & et al, 2024). Through critical examination of its advantages, disadvantages, and future estimated implications, the objective of this paper is to shed light on the various implications artificial intelligence has introduced into public administration (Wang & et al, 2024). Despite the fact that the application of artificial intelligence in public administration is not a new phenomenon, the acceptance of this technology has accelerated over the course of the previous 10 Abstract The maternal marine supplements sector has garnered significant attention in recent years due to growing awareness of the critical importance of maternal health and nutritional support. This study aims to examine the implementation of Green Supply Chain Management (GSCM) practices within this industry as an approach to achieving sustainable global commerce. The research employs a qualitative approach, conducting comprehensive reviews of current literature and examining case studies to identify effective strategies and obstacles related to GSCM adoption in the maternal marine supplements field. Results demonstrate that implementing GSCM practices yields multiple advantages, including enhanced environmental protection, stronger financial performance, and increased consumer confidence. The study concludes by offering strategic guidance for incorporating GSCM frameworks into the operational processes of supply chain participants. KEYWORDS: Green Supply Chain Management, Maternal Marine Supplements, Sustainable Trade, Environmental Sustainability, International Trade Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17283672 147 years (Yigitcanlar & et al, 2024). Automation of administrative duties is one of the many applications of artificial intelligence. Other applications include policy insight analysis of massive amounts of data (Mohammed & et al, 2024). Initiatives driven by artificial intelligence are receiving significant financing from both the federal government and state governments across the United States (Hermann & et al, 2024). These initiatives include predictive analytics for law enforcement, machine learning algorithms for detecting fraud in welfare programs, and chatbot-based services for public interaction. For all these developments, concerns about algorithmic bias, data privacy, and the absence of human judgment still linger. According to findings in previous studies, there are instances when artificial intelligence systems unintentionally reinforce systematic biases or make mistakes because they are trained on incomplete data sets (Adewusi & et al, 2024). Furthermore, even while artificial intelligence presents the promise of greater efficiency, the use of this technology presents some governance and ethical challenges that will need to be carefully resolved (Fosso Wamba & et al, 2024). Policymakers need to reach an understanding of the complexity of the technologies themselves first, prior to being able to anticipate using artificial intelligence in public administration in an appropriate manner (Schweitzer, 2024). Figure 1: A Comprehensive Review of Artificial Intelligence’s Impact on Decision-Making according to (Caiza & et al, 2024) Although the application of artificial intelligence promises a wealth of opportunities for improving public administration, the deployment of this technology is fraught with challenges that require careful consideration. Throughout the course of this effort, the following research questions are addressed: - In what ways is artificial intelligence (AI) currently being integrated into various public administration areas across the United States of America? - In what ways could artificial intelligence increase the efficiency of the government, particularly with regard to decision-making and the delivery of services? - When it comes to administrative systems driven by artificial intelligence, what factors influence public confidence, and how do people perceive such systems? Related Works Artificial intelligence has enhanced the management of data in the public sector, the detection of fraud, and predictive analysis. To comprehend such intricacies, an appreciation of the impact artificial intelligence has on the efficiency of administration, implementation of policy, and decision-making is necessary. With regards to methods, results, and areas for additional research, this section examines some of the most significant AI research to public administration. The purpose of this review is to put the application of AI in government into perspective by comparing previous and more recent empirical findings in the hopes of determining areas of lacking research. Maybe more than ever before, everyday life, society, and state systems are impacted by AI environments and algorithms. Governments have largely been responsible for making sure that today's public administration systems are in place and facilitating smooth transitioning into new technologies, as presented by Uzun (2022). In order to integrate, govern, and regulate AI technology, public administration and policy have important roles to play. There are several opportunities when AI is included into public administration and the policy-making process. In this sense, the big questions debate began in 1995 when Robert Behn highlighted the importance of the big questions as the main motivator for a research program in public administration. As a result, while AI can assist in solving knotty global challenges, it generates severe privacy, accountability, and regulatory issues. This study demonstrates the political, legal, and public administration aspects of transdisciplinary AI regulation. Policymakers need to address AI relentlessly to maximize its advantages while minimizing its disadvantages (Uzun & et al, 2022). Although the use of artificial intelligence (AI) chatbots in public organizations has increased in recent years, three crucial gaps remain unresolved. First, little empirical evidence has been produced to examine the deployment of chatbots in government contexts. Second, existing research does not distinguish clearly between the drivers of adoption and the determinants of success and, therefore, between the stages of adoption and implementation. Third, most current research does not use a multidimensional perspective to understand the adoption and implementation of AI in government organizations. for this regard, Chen 2024 addressed these gaps by exploring the following question: what determinants facilitate or impede the adoption and implementation of chatbots in the public sector? this question by analyzing 22 state agencies were answered across the U.S.A. that use chatbots. It showed that different types of determinants (such as knowledge-based creation and maintenance, technology skills and system crashes, human and financial resources, cross-agency interaction and communication, confidentiality and safety rules and regulations, and citizens’ expectations, and the COVID-19 crisis) impact differently the adoption and implementation processes and, therefore, determine the success of chatbots in a different manner. Table 1 shows the Determinants of AI Chatbot Implementation Success as presented (Chen & et al, 2024). Table 1: Determinants of AI Chatbot Implementation Success according to (Chen & et al, 2024) Factor Second-order Code Challenge (First-order Code) Enabler (First-order Code) Data & Knowledge-based Limited website analytics use (10) Collaborate with service staff (3) Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17283672 148 Information creation Content enhancement Users phrase questions differently (4) Monitor chatbot performance (3, 2) Technology Technology skills Lack of chatbot development skills (12) Partner with IT vendors (12) System Lack of chatbot management skills (4) Provide training (2) System crashes (2) Use a soft launch approach (2) Organizational Human resources Increased workload (9) Reallocate staff (3) Financial resources Long-term funding sustainability (2) Use free trials, contracts, or special funding (12) Interorganizational Staff expectations Deployment seen as complex & burdensome (2) Improve cross-agency communication (2) Executive expectations Unrealistic expectations about chatbots (2) Clarify project scope (2) Institutional Confidentiality & safety No PII required for chatbot use (11) Contextual End-user expectations Users expect specific details (2) Communication & clarification (2) Examining how AI interacts with public governance and management in both developed and emerging market economies was the goal of another study. Therefore, the paper made the case that artificial intelligence (AI) has enormous potential and has been used to improve government performance in the following areas: politics, intergovernmental relations, policymaking, social service delivery, public security management, public financial management, information processing, and data management. The study came to the conclusion that because AI offers attractive returns on investment, there are still a lot of untapped potentials in the interaction between AI and public administration. As a result, more research should be done and professionals who are interested in integrating AI into more functional areas of public management and governance should receive more support (Agba & et al, 2023). Using a dataset of 3,149 documents from the Scopus database, another study identified the top 200 most cited articles based on annual citations. In addition, selected AI use cases from the European Commission database were classified, focusing on their contributions to public value. The analysis focused on three dimensions of governance: internal processes, service delivery, and policy making. The results provided a categorized understanding of AI concepts, types, and applications in the Palestinian Authority, along with a discussion of best practices and challenges (Babšek & et al, 2025). The connection between discretion, bureaucratic form, and artificial intelligence (AI) in public organizations was the subject of another essay. The study came to the conclusion that while the usage of AI has grown recently, little is known about how this unique kind of ICT, discretion, and bureaucratic form relate to one another along the street-level to system-level continuum. As a function of bureaucratic form, the study discovered that the impact of AI on discretion is nonlinear and nonmonotonic. However, even if these organizations have previously opposed such changes, the deployment of AI may accelerate their shift from street-level and screen-level bureaucrats to system-level bureaucracies (Bullock & et al, 2020). The goal of Schiff, 2020, was to evaluate the core public values that could be jeopardized by the adoption of automated decisionmaking systems (ADS) by governments. In order to quantify and compare the significance of three of these values—fairness, transparency, and human responsiveness—a public value failure framework and empirical approach were used. The results of a survey experiment conducted among fields of criminal justice and child welfare demonstrated unequivocally that some public value failures related to AI have a substantial detrimental impact on citizens' assessments of their government. They discovered that when fairness and openness are not met in the application of ADS, there are notable unfavorable reactions from the public. Even in cases where respondents were not directly impacted, these results held true regardless of political background or ideology (Schiff & et al, 2022). In spite of the extensive research on artificial intelligence in public administration and governance, there are still gaps in research such as the lack of research on transparency, ethics, and reducing bias in AI applications and a lack of comparative studies that reflect the challenges of implementing AI in developing economies. In addition, short are longitudinal measures gauging the long-term effects of artificial intelligence on government trust and the public sector. Also lacking is much investigation of the intersection of artificial intelligence, decision-making, and accountability in public policy. Furthermore, public administration generative AI solutions (like chatbots) need improved understanding of implementation problems as well as the participation of individuals, and hence additional applied and experiment studies are required to ensure efficient governance and clear ethics for AI deployment in the public sector. For this regard, the objectives of this research study: to assess the level and grade of artificial intelligence (AI) uptake in public administration in the United States; to explore the ways in which AI impacts governmental efficiency, policymaking, and the dynamics of labor; to identify the prime ethical, juridical, and technological questions regarding AI rollout; and to provide policy recommendations for how one can advance the governance of AI. By means of a critical evaluation of the current artificial intelligence deployment in governmental institutions, this study attempts to examine the benefits and drawbacks of artificial intelligence governance. Moreover, it looks at how artificial intelligence technologies affect administrative decision-making, resource allocation, and service delivery performance. This paper intends to highlight important legal and governance questions resulting from algorithmic bias, data privacy difficulties, and human labour displacement. The project seeks to offer evidence-based policy recommendations to guarantee responsible and ethical uses of artificial intelligence in public administration, so combining public confidence with technical development. Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17283672 149 Methodology By examining its effects on institutional efficiency, decisionmaking, transparency, and government investment, this study seeks to investigate how artificial intelligence (AI) is affecting public administration in the United States. In an effort to understand the advantages and difficulties of implementing AI in the public sector, the study uses a mixed-methods approach, integrating quantitative and qualitative data (See Figure 2). The study examines, using the descriptive-analytical approach, the influence of artificial intelligence (AI) on American public administration. The study uses qualitative and quantitative data to examine the influence of artificial intelligence on the performance of institutions, decisionmaking, transparency, and government expenditures. The study employs three main sources of data usage in an attempt to provide accuracy and comprehensiveness: - Official Statistical Data including DARPA's and the U.S. Bureau of Statistics reports on artificial intelligence investments and use (National Academy of Public Administration , 2019), (Centers for Medicare & Medicaid Services, 2019), and (Institute, 2019). - Academic journals ensure theoretical underpinnings through Public Administration Review articles, Information Polity, and the Journal of Public Administration (Bullock & et al, 2020), (Schiff & et al, 2022). - Case studies of artificial intelligence application in court systems, the healthcare sector, police, and other administrative functions to evaluate success rates and gaps. Mathematical models are used in an effort to gather statistical information, clean and analyze it in this secondary data analysis method. One of the most important models used and presented as presented in Equation (1): Y_t =α+β_t+ϵ_t …………………………….…… (1) represent the AI adoption rate at time, the trend coefficient, the error term, and the intercept. It can identify whether AI adoption in public administration follows an increasing, decreasing, or stagnant trend over time. Several quantitative techniques are used to examine trends in AI adoption: - Statistical Analysis: The analysis quantifies the impact of AI on government performance using descriptive statistics like mean (μ), standard deviation (σ), and interquartile range (IQR). Investment in AI growth is investigated using Equation (2), which represents AI investment at time t: ………………. (2) - Trend Analysis: This analysis can be used in this study to understand how the adoption of artificial intelligence is evolving. The compound annual growth rate (CAGR) can be calculated as in Equation (3), where the final, initial AI adoption value and number of years are , respectively: …. (3) - Comparative analysis: This method helps evaluate the adoption of AI across different administrative sectors such as law enforcement, taxation, and public healthcare. The efficiency ratio (ER) for each of these sectors can be evaluated using Equation (4): …… (4) Figure 2: Flowchart representing the methodology of the study. Results This section seeks to provide a critical assessment of evidence on the impact of AI on public administration based on quantitative measures. This section synthesizes the results of this study across four areas of importance: the use of AI by government agencies, investment trends, public trust and transparency, and employment impact. The findings show that 63% of government agencies already use AI, and another 59% will implement AI soon. This reveals the increasing acceptance of the role of AI in improving administrative effectiveness. The implementation rate of AI-based decision-making is only 48%, suggesting that although AI is being embraced, its integration into decision-making processes is still in the making, as illustrated in Table 2. Table 2: AI Adoption in Government Agencies Metric Value Unit Percentage of government agencies using AI 63% % Percentage of agencies planning to adopt AI 59% % AI-driven decision-making implementation rate 48% % An adoption rate of over 60% indicates that AI has become a key tool in public administration. However, the 48% decision-making implementation rate means that while AI is widely available, agencies may be hesitant to rely on AI to make critical governance decisions, perhaps due to ethical concerns, regulatory barriers, or technical limitations. There exists a gap between adoption and effective use, signifying the need for policies supporting the easy embedding of AI into decision-making. While the US government spend on AI stood at $6 billion in 2023, it is anticipated to be $9 billion by 2025, growing at a CAGR of Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17283672 150 12%. This type of investment by the government indicates the strategic importance of the development of AI, which can be seen from Table 3. The 12% CAGR also indicates the increasing significance of AI in government policy and proposal submissions. Further, the estimated cost of $9 billion by 2025 indicates how AI is also being seen as a long-term driver of administrative effectiveness, cost reduction, and service automation. The increased expenditure requires a clearly established AI governance framework to enable responsible expenditure, avoid duplicating efforts, and ensure maximum returns on investments in AI. Table 3: Investment in AI and Budget Allocation Metric Value Unit Government AI investment in 2023 $6B Billion USD Projected AI investment in 2025 $9B Billion USD Annual AI investment growth rate 12% % Public trust in AI decision-making is divided, 48% of whom were trusting, with 38% of the public still suspicious of openness. Furthermore, 27 AI governance breakdowns were reported, which reflect enhanced more open governance arrangements as seen in Table 4. 48% trust overall means restricted AI decision-making acceptance but requires greater openness and accountability. Transparency issues remain a significant concern, as 38% of complaints were process-based AI-driven. Table 4: Public Trust and Transparency Metric Value Unit Public trust in AI-driven decisions 48% % Complaints about AI transparency issues 38% % AI-related administrative failures 27 Cases The 27 reported failures of governance also reflect that the use of AI is not flawless and requires constant adjustment and monitoring to reduce errors and increase reliability. Improving transparency mechanisms, such as explainable AI models and open regulatory policies, can potentially establish more public trust in AI-driven decision-making. While examining the impact of AI on jobs and labor force, AI is significantly changing the government workforce, where 50,000 employees have to be retrained in order to adapt to AI-driven changes. In addition, 30% of white-collar jobs were affected, and 16 AI projects directly contributed to job displacement, as shown in Table 5. It can be concluded that retraining 50,000 employees demonstrates a proactive effort by the government to address workforce disruptions caused by AI. While the 30% of white-collar jobs affected highlight the transformative impact of AI on government employment, with routine and repetitive tasks being automated. The 16 AI-led job displacements suggest that while AI creates efficiency, it also creates social and economic concerns related to job security. Governments must balance AI efficiency gains with job-protection policies, such as retraining programs and AI-human collaboration models. Table 5: AI Impact on Workforce and Employment Metric Value Unit Number of government employees retrained due to AI 50,000 Employees Percentage of administrative jobs 30% % affected by AI AI projects leading to job displacement 16 Projects On the other hand, the benefits of AI innovation include better decision processes but the advancement challenges leadership in adaptation as well as creates jobs losses and ethical quandaries. This research studies possible predictive outcomes of AI effects on public administration and delivers strategic recommendations for handling its intricate issues. The fast pace at which AI systems enter administrative work has sparked worries about how such integration affects workforces and their privacy as well as equal opportunities among citizens. Automation of public sector jobs that complete repetitive operations creates an unemployment problem that affects large numbers of workers. AI-based governance requires additional consideration of ethical issues which affect accountability measures as well as creates doubts about transparency while distorting operational decision systems. When AI surpasses human intelligence, it establishes uncertain social conditions which makes future outcomes unpredictable for society. Public administrative agencies across federal and state levels embrace AI deployments which result in process optimization together with improved service delivery and better decision-centric capabilities. AI-powered chatbots along with predictive analytics and automated document processing systems have substantially raised operational speed. The implementation of algorithmic governance faces ongoing difficulties to prevent biases from appearing while maintaining fairness standards (See Table 6) according to (Yigitcanlar & et al, 2021) (Gillespie & et al, 2023). Table 6: Challenges of AI Application in Government Agency Government Agency AI Application Challenges IRS Fraud detection & tax compliance Risk of false positives DHS Facial recognition for security Privacy concerns DMV Automated licensing & vehicle registration Algorithmic bias risks Government funding for AI research and development continues to increase because AI has become vital for public administration needs. Commissioned federal funding along with tech partnerships and AI-based infrastructure development demonstrates official confirmation of permanent AI implementation. The fair distribution of AI technologies together with funding allocation matters remain subject to ongoing concerns between stakeholders (Yigitcanlar & et al, 2021) (Gillespie & et al, 2023). The public maintains trust in AI decision systems when they are transparent to view. The public has developed doubts regarding how AI participates in governmental operations because they worry about both untraceable processes and violations of ethical guidelines. The development of explainable AI combined with public engagement programs will build trust for AI-driven public services, according to the information presented in Table 7 (Yigitcanlar & et al, 2021) (Gillespie & et al, 2023). Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17283672 151 Table 7: Percentage of Respondents (%) for Public Concern Public Concern Percentage of Respondents (%) AI bias in government decision-making 68% Lack of transparency in AI policies 74% Privacy risks in AI-powered services 81% The introduction of AI automation technologies has modified public sector labor forces which led to personnel layoff in certain positions but introduced positions dedicated to AI management and oversight responsibilities. The main issue rests in delivering proper training programs for employees who lost their jobs to ensure they can maintain relevance in the AI-based economic environment following data in Table 8. Table 8: Jobs Created and Lost Due to AI in Customer Service, Data Entry, and Cybersecurity Sector Jobs Lost Due to AI Jobs Created by AI Customer Service 120,000 40,000 Data Entry 90,000 30,000 Cybersecurity 20,000 60,000 The following three scenarios depict AI's path in public administration together with their effects on human occupation according to (Yigitcanlar & et al, 2021) (Gillespie & et al, 2023):  Scenario 1: Human Control Over AI and Robotics The utilization of AI tools under human oversight in this situation permits public administration to benefit from technological advances without losing human employment positions. Public administrations enact controlled legislation to lead AI development activities by monitoring ethical practices and maintaining human supervision throughout the process. This method allows both human control and AI efficiency to work together so that people maintain their decision-making authority. This scenario shows a major benefit because AI supports human workers instead of taking their positions thus diminishing economic as well as ethical complications.  Scenario 2: Coexistence Between Humans and AI Within this model, AI forms a mutually beneficial partnership with human operators by performing automatic duties and letting humans handle high-importance work to establish policies and perform oversight responsibilities. AI supports data analytical functions while it automates administrative work alongside service improvement programs until human workers maintain their positions. Organizations require ongoing adjustments along with specialized training and human-centered ethical standards to manage AI systems within established human-based principles. The model design delivers operational excellence to public services and preserves jobs within the bureaucracy.  Scenario 3: AI Surpasses Human Control The most concerning situation occurs when automated systems along with AI surpass human management which triggers an unprecedented level of automation. The implementation of AI algorithms within administration functions leads to mass job losses along with a governing system controlled by artificial intelligence. The power shift would establish AI systems with control that exceeds human capabilities, thereby creating conditions of dependency between humans and these AI systems. The distribution of power among AI-controlled entities while AI makes decisions and violates privacy elevates ethical risks throughout modern society. This scenario creates declining human supervision and exposes communities to relinquish control of their public administrative operations. Discussion These results of this research are discussed with recently researches as (Criado & et al, 2024), (Madan & et al, 2023), and (Kulal & et al, 2024). especially, the researches that offer a detailed analysis of the impact that artificial intelligence has had on public administration. Comparing and contrasting the findings of the various studies that have been conducted on the subject of artificial intelligence and governance is a beneficial way to have a better understanding of the impact that AI has on governance. When considering the existing research, it showed that, (Criado & et al, 2024) suggested a three-tiered framework for studying the effects of AI on public administration in the year 2024. This framework would include macro, meso, and micro levels. This present research is an extension of this approach by integrating factual data on AI adoption trends among U.S. agencies and actual case studies. As pragmatic implementation problems at the agency level, e.g., labour relocation and issues with trust, these findings suggest, Criado et al. focused on governance-level measures. (Madan & et al, 2023) also investigated AI adoption via the prism of absorptive capacity and public value tensions. Our research validates their claim that governance structures and technology readiness shape AI integration. But we also discovered that, given differences between federal, state, and local government entities across the United States, the actual application of artificial intelligence is more dispersed. According to the results of a recent study on the effect of artificial intelligence on the effectiveness of public sector operations by (Kulal & et al, 2024), AI greatly improves the operations of municipal organizations while having a negligible effect on human-centric services. Our findings support the claim that artificial intelligence-driven automation increases operational effectiveness, but they also highlight further questions about how it affects decision-making transparency more broadly. According to the result of our research, citizens' trust in artificially intelligentdriven services is lower than anticipated, which contradicts the research finding of Kulal (Kulal & et al, 2024). It can be seen that there is an urgent need for more robust transparency and accountability mechanisms. When compared to other countries, the United States of America also invests a substantial amount of money on the regulation of artificial intelligence; it is estimated that this cost will reach up to $9 billion by the year 2025. However, our findings demonstrate that there is a significant disparity between readiness and investment. According to the findings of our research, institutions in the United States of America employ a strategy that is not related to any particular approach to AI governance. This is in contrast to the findings of studies that have been undertaken in Europe and India, which highlight coordinated policies for AI governance. Both data governance and algorithmic bias are considered to be contemporary problems in all the studies that have been conducted on the subject. Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17283672 152 As per the results of (Madan & et al, 2023) and (Criado & et al, 2024), all that is needed is responsibility and openness. Moreover, these pieces of evidence are complementary to one another and function together. The evidence that we present, on the other hand, presents an alternative perspective on the debate: although artificial intelligence promotes efficiency, it does not inevitably increase public trust, particularly in matters pertaining to the administration of law enforcement and the distribution of welfare benefits. While the majority of the study that was done in the past concentrated primarily on the use of artificial intelligence within government structures, the current research reveals that significant distinctions are being made with regard to the deployment of AI. Despite the fact that law enforcement agencies are having trouble dealing with problems related to prejudice, the implementation of artificial intelligence in taxation operations and the fight against fraud has been successful to a greater degree. The previous research did not fully investigate this sectoral analysis as it was carried out. Table 5 shows the main differences between this current study and recently researches, Thus, this current study presents a forward-looking perspective on the application of artificial intelligence in American public administration by combining data from other sources and contrasting them with the body of present literature. Issues include employment loss, lack of openness, and governmental fragmentation still exist even if artificial intelligence has enhanced performance and decision-making. Future research has to focus on developing a uniform governance framework for artificial intelligence if we are to close the investment-touse discrepancy. Table 5: Comparison between this current study and the recently researches Study Focus Area Results Differences from Current Study (Criado & et al, 2024) AI governance strategies Framework for AI governance at macro, meso, and micro levels This current study extends to real-world agency-level implementation (Madan & et al, 2023) AI and public value tensions AI success depends on absorptive capacity and governance frameworks The present study highlights disparities in adoption at different government levels (Kulal & et al, 2024) AI in public service efficiency AI enhances municipal processes but has moderate human-centric impact Our study finds lower public trust than expected Current Study AI in U.S. public administration AI improves efficiency but raises transparency and workforce concerns The current study introduces sector-specific implementation disparities AI implementation within government institutions has simplified administrative processes but citizens remain concerned about system transparency together with accountability and discrimination risks. AI technology adoption trends continue to escalate which calls for strengthened ethical guidelines to manage their distribution in society. Public confidence becomes more significant because citizens want to understand better how AI systems make decisions. The employment sector experiences a fundamental shift because automation performs certain tasks yet develops fresh AI oversight and governance positions. Public administration's AI future hinges mainly on strategic planning together with regulatory approaches. Three future scenarios are emerging from scenario-based analysis that present AI either under human control or alongside humans or dominating independent from human involvement. The fast progress of AI demands regularly updated policies since human oversight represents the best approach. Lack of suitable measures puts human control at risk which might create governance imbalances and ethical issues. To guarantee AI functions as a human capability enhancer versus human substitute policymakers must take proactive steps while developing their workforce. Conclusion Where public administration is concerned, integration of artificial intelligence presents marvelous opportunities and enormous challenges. This research study establishes that government performance in matters such as predictive modeling, automated citizen services, and fraud detection has been enhanced through technologies created through artificial intelligence. Yet there are significant obstacles to overcome in the form of concerns over openness, uneven policy enforcement, and citizens' lack of trust in artificial intelligence making decisions. Maybe the most surprising of this study is the discrepancy between the level of technological readiness different government agencies actually possess and the financial investment in artificial intelligence. Despite federal agencies receiving ample funding for artificial intelligence, state and local governments are typically not given the tools and expertise to effectively execute AI plans. Furthermore, ethical issues surrounding algorithmic bias and data privacy underscore the necessity of crafting robust laws to govern the uptake of artificial intelligence. Subsequent research needs to center mainly on the development of standardized models of governance and longitudinal studies quantifying the effect of artificial intelligence regulation in the real world. Artificial intelligence is on a fast track. The policymakers should ensure that artificial intelligence is an asset to improved public administration and not a cause of inequality and mistrust; thus, they should create maximum priority towards an approach weighing the advantages of AI against its natural risks. Recommendations The following recommendations serve as recommendations to handle the challenges together with the risks that AI technology presents to public administration:  Establish clear policies together with ethical guidelines which maintain AI as a tool helping people not replacing their tasks. Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17283672 153  Public sector organizations need to design training schemes that develop workforce capabilities for working with AI-based systems.  Governments should implement procedures for developing AI which maintains both transparency and accountability for avoiding bias and ensuring fair governance practices.  The coexistence between humans and machines should be sustained through policies which guide AI automation practices while keeping human supervision active.  AI Accountability Systems need development for tracking AI systems that refrain from crucial choices when personnel should be involved. Disclosure Statement Ethical approval and consent to participate: Conducted in accordance with established procedures. Availability of data and materials: Collected in a proper and systematic manner. Author contribution: The author was solely responsible for all stages of the research and manuscript writing. Conflict of interest: The author has no conflicts of interest to disclose. Funding: No funding or financial support was received from any organization. Acknowledgments: The researcher extends heartfelt thanks to all friends and colleagues who contributed to the success of this work, and sincere appreciation to the dear students who participated in the study. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc/4.0/ References 1. Adewusi, & et al. (2024). Artificial intelligence in cybersecurity: Protecting national infrastructure: A USA. 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