Artificial Intelligence, Governance and Ethics: Global Perspectives

Artificial Intelligence for data-driven decision-making and governance in public affairs

Purpose This study aims to determine and prioritize the critical success factors (CSFs) that drive the procurement process of artificial intelligence (AI) systems in the public sector in the Indian context. It addresses the peculiar challenges and exigencies of procurement processes of AI systems in public sector organizations and develops a hierarchical model for guiding policymakers. Design/methodology/approach This study uses a research methodology that includes: identifying potential CSFs through literature review and expert consultations, developing a structural self-interaction matrix and performing cross-impact matrix multiplication applied to classification analysis for classifying CSFs based on driving and dependence powers. The study also uses interpretive structural modelling to establish relationships among these factors. Findings Fourteen CSFs are found in this study, which shape public procurement of AI. These influential factors cut across technical, organizational, regulatory as well as socio-economic aspects. This model is arranged hierarchically to indicate how these identified CSFs fit together thereby providing a roadmap towards successful procurement of AI systems. All other CSFs depend on or are influenced by stakeholders’ coordination and collaboration, which means that it is the most important one. Practical implications The results present a hierarchical model for navigating the intricacies of public sector AI procurement. Consequently, this model may support public organizations to enhance service delivery, optimize resource allocation and improve decision-making processes. It also addresses the need for an organized approach to the procurement of AI systems in developing countries such as India where extant guidelines are either insufficient or non-existent. Implementing these CSFs can result in more efficient, transparent and accountable procurement practices of AI systems, ultimately impacting positively on public service outcomes. Social implications The hierarchical model and classification of CSFs provide an alternative view regarding what entails successful AI systems’ acquisition stressing out particular requirements and obstacles associated with it within developing countries’ public sector agencies. It is in line with achieving sustainable development goals (SDGs) 9 which is industry, innovation and infrastructure and SDG 12 which is responsible consumption and production. Originality/value This study provides a new perspective by developing a comprehensive structured framework for the procurement of AI systems in the public sector. It fills gaps existing in research by offering a structural model on how to increase organization efficiency through the procurement of AI systems. The hierarchical model and classification of CSFs provide an alternative view regarding what entails successful AI acquisition, stressing particular requirements and obstacles associated with it within developing countries’ public sector agencies.

In the artificial intelligence era, the investment in human resources represents the best way to ensure the public organization's success and bright future. The overall objective of the paper is to capture a comprehensive and genuine image of career management in the public sector and to evaluate the impact of using artificial intelligence (AI) at the central and local government levels. The research questions are: How is Romania improving the management of civil servants’ careers? How is Romania’s performance in applying artificial intelligence in the public sector? Is Romania prepared to face the challenges of exponential artificial intelligence development? The paper explores the landscape of career management in the European and national public sectors, emphasizing the key issues for its improvement. It also analyses the use of artificial intelligence in the European and national public sectors, highlighting the main realities and trends. The conclusion of this research highlights that in the era of artificial intelligence, the leaders in public organizations should have a holistic approach, meaning to create a positive, empowering culture, enable AI innovation, support the changes brought by emerging technologies, identify the competence set specific for AI projects and support training programs in view to endow the public employees with the AI-related competences, as well as to evaluate AI impact. The methodology comprises bibliographic syntheses, socio-innovative empirical research, correlation, and regression analyses. The contribution brought by this research consists in presenting the realities and roadmap for effective management of civil servants’ careers and the use and impact of artificial intelligence in central and local government in view to be successful in times of outstanding challenges and opportunities, as well as in analyzing the statistical connection between government artificial intelligence and digital competitiveness.

The technological and digital evolution of the public sector reinforces the idea of implementing new technologies to improve public management and the government decision-making process. Some governments, such as the United States, China, and the United Kingdom, are investing resources in the development and research of AI-based technologies. However, it is necessary to recognize the scientific and academic advances that analyze the development of AI in the public sector. Based on the above, the objective is to describe and analyze the development of AI in the public sector from the academic literature. This objective is based on the following research question: How has academic literature on artificial intelligence in the public sector evolved in its methodological, conceptual, and contextual dimensions between 2018 and 2022? To answer the question and meet the objective, an analytical strategy is used based on the systematic review of the literature and the establishment of dimensions, categories, variables, and indicators that allow classifying and analyzing the information of the 207 articles that were published between 2018 and 2022 in the academic journals that most publish works related to AI in the public sector. The results show that there is an interest by the academic community in analyzing the development of AI in the public sector worldwide. Derived from the gradual growth of research work in this area. Another aspect to highlight is the number of countries that are analyzing the phenomenon of AI in the public sector.

This paper looks into how artificial intelligence influences openness in the public sector and examines the laws in Europe and the United States relating to this issue. The European regulations focus on safeguarding individual rights and privacy, while the laws in the United States prioritize creating anti-corruption measures that hold the government accountable. Various artificial intelligence tools, such as large-scale data analysis and blockchain technology, have significant promise for enhancing transparency and supporting efficient detection and decision-making. However, these technological advancements introduce several legal challenges, making it difficult to achieve clarity regarding algorithms and to identify legal responsibilities, which complicates effective judicial oversight. The AI Act of 2024, introduced by the European Union, is among the main EU regulations as it requires transparency standards for high-risk AI systems. The United States employs various sector-specific regulations instead of a single comprehensive framework for oversight. The study concludes that artificial intelligence requires tailored legal frameworks to ensure transparency while maintaining accountability and protecting essential human rights, along with facilitating judicial oversight.

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.

Is it possible to think strategically about succession in the public sector? The author reviews the private-sector succession literature for insight and analyzes the barriers in the public sector to taking succession seriously. With a case study based on her own experience managing succession at the New York City Department of Juvenile Justice, she offers four strategies that the public sector leader who is committed to a strategic approach to succession might usefully employ. In the public and private sectors alike, demand for change is the one constant. There is a loud call for leaders who can accommodate change personally and who can initiate and drive broad changes in their organizations. These demands make sense but raise a troubling issue. By relentlessly insisting on change, are we risking the loss of innovations recently realized? This is a particularly salient question for public-sector agencies, which are currently under attack from all sides. In this article, I assert that while change must be on the agenda of any public agency for its very survival as well as for the public good, it is just as important to ensure that gains achieved in one administration be given a fair assessment and not be jettisoned, without review, to the god of change. Indeed, the importance of -- essentially keeping change alive -- is an increasing challenge for public agencies.(1) Will innovative programs created as a response to social problems be allowed to live out their natural lives, or will they be killed off before their time, independent of performance and outcomes? This issue is particularly acute in the transition between elected or appointed government officials -- especially in a highly politicized environment that limits government's capacity to continue efforts across administrations. Moreover, one critical tool available to the private sector, succession planning, is rarely used by public agencies because the executives fortunes are generally tied to a particular administration. Many public-sector leaders have devised strategies for continuing efforts across administrations. Some establish support beyond the government, for example, from the business community or other local elites; some obtain early bipartisan political support. Still others avoid program demise by identifying a champion linked to the incoming administration so as to have a voice inside, or by creating wide support within the agency (and other agencies) so that the new governor or mayor hears a consistent message. Finally, some administrators have succeeded in winning national recognition for their innovations so that discontinuing them is a perceived political risk. As important as these approaches are, innovations also can be sustained by cabinet secretaries or agency heads engaging in succession planning, even though these people are as vulnerable to shifting political winds as their superiors. In fact, this level, where so much actual and potential innovation resides, represents a real opportunity for both preserving innovations and transferring them to subsequent regimes -- provided the agency heads can, and will, extend their strategic vision beyond their own tenure. It is no longer sufficient to achieve change, difficult as it may be. The public-sector leader must learn to consider not only what can be but what will be, how what is achieved can be sustained. This requires future-oriented strategic thinking, which I argue must include attention to succession planning. Succession planning done well involves preparing the agency for a change in leadership, but it also includes assessing what has been valuable and how that can be preserved and transferred to the subsequent regime. It is this strategic, sustaining innovation aspect of succession planning that I focus on in this article. First, I shall look at how research on succession in the private sector is both helpful and hindering for public-sector succession planning, especially in the realm of sustaining innovation. …

Purpose The purpose of this paper is to explore how artificial intelligence (AI) impacts both internal communication and employee engagement from a more global perspective by interviewing professionals who live in the United Arab Emirates (UAE) and work for multinational companies. Design/methodology/approach Semi-structured interviews were conducted to capture the experiences of communication professionals who live and work in the UAE, which is an epicenter of multinational corporations and international public relations agencies. Participants oversee internal communication and employee engagement for large, multinational companies. Findings The shared narratives demonstrate that AI can be an enhancer in the workplace as long as humans are involved in the process. Internal communication requires an attention to detail and nuance that cannot always be generated by AI. The professionals expressed concern from their own personal experiences with AI, suggesting that an overreliance on such platforms threatens their professional identity and impedes their creative edge. Last, when AI is used for employee engagement purposes, it lacks the human touch and dialogic components that are necessary and essential for employee engagement. Originality/value AI is only successful when it is seen as a human enhancer, not a replacer. Also, caution needs to be exercised with using and implementing AI in the workplace to aid in the management of employee engagement. By design, AI platforms lack human communication and limit connection, both of which are essential for employee engagement.

The emerging global governance of artificial intelligence (AI) is shaped by numerous political actors. Inviting non-state actors into such processes is typically assumed to address a perceived democratic deficit, by promoting increased representation, transparency, and openness. In the AI sphere, however, non-state actors include the same multinational companies that develop the technology to be regulated. Surprisingly, the task of normatively theorizing the democratic role of non-state actors in global AI governance has nevertheless been largely ignored. This paper addresses this by specifying, first, under what conditions non-state actors contribute to the actual democratization of global AI governance, as ‘democratic agents’, and second, under what conditions they instead contribute to the strengthening of the prerequisites for future democratization, as ‘agents of democracy’. We conclude that, although few non-state actors are authorized to act as ‘democratic agents’, their exercise of ‘moral’, ‘epistemic’, and ‘market authority’ could make them legitimate ‘agents of democracy’.

Public sector agencies are rapidly deploying AI systems to augment or automate critical decisions in real-world contexts like child welfare, criminal justice, and public health. A growing body of work documents how these AI systems often fail to improve services in practice. These failures can often be traced to decisions made during the early stages of AI ideation and design, such as problem formulation. However, today, we lack systematic processes to support effective, early-stage decision-making about whether and under what conditions to move forward with a proposed AI project. To understand how to scaffold such processes in real-world settings, we worked with public sector agency leaders, AI developers, frontline workers, and community advocates across four public sector agencies and three community advocacy groups in the United States. Through an iterative co-design process, we created the Situate AI Guidebook: a structured process centered around a set of deliberation questions to scaffold conversations around (1) goals and intended use for a proposed AI system, (2) societal and legal considerations, (3) data and modeling constraints, and (4) organizational governance factors. We discuss how the guidebook’s design is informed by participants’ challenges, needs, and desires for improved deliberation processes. We further elaborate on implications for designing responsible AI toolkits in collaboration with public sector agency stakeholders and opportunities for future work to expand upon the guidebook. This design approach can be more broadly adopted to support the co-creation of responsible AI toolkits that scaffold key decision-making processes surrounding the use of AI in the public sector and beyond.

Disruptive technologies are widely used in semi-periphery and core countries such as the United States of America, Australia, Croatia, and China to manage and preserve records. However, the same cannot be said about periphery countries, especially on the African continent. These countries, including South Africa, are struggling with the digitalisation of records, let alone the management of paper-based records. This study, conducted in the public sector in South Africa, explores literature review to critically analyse challenges to archival functions that can be mitigated through the application of artificial intelligence technologies. Findings reveal problems relating to governance in a digital environment, a lack of accountability, the high level of litigation rates, bad audit results, and a lack of or poor service delivery emanating from a breakdown in records systems in South Africa. Both paper-based and digital records management systems in the public sector in South Africa are in a state of disarray. As a result, the preservation of digital records is slowly taking place, which leads to the loss of memory for the entire public sector. It is concluded that the market is ripe for disruptive technologies such as artificial intelligence, cloud computing and blockchain in the management and preservation of records in the South African public sector. The study recommends that governmental bodies cautiously consider exploring the possibility of storing their records in a trusted digital repository cloud as an interim solution while observing legal obligations. Other technologies such as blockchain technology can also be adopted to ensure the security of records.

Artificial intelligence (AI) has emerged as a disruptive technology in healthcare, with applications ranging from imaging diagnostics to clinical data management. This articlepresents a systematic literature review on the use of AI in clinical practice, focusing on global experiences and perspectives for Angola, particularly the Malanje region. The methodology included the analysis of scientific articles published between 2023 and 2025, obtained from platforms such as ScienceDirect, PubMed, SciELO, and Google Scholar, as well as technical reports from international organizations. The overall objective was to synthesize the available evidence on AI applications in healthcare, identifying lessons learned in countries such as the United States, Brazil, and South Africa, and proposing recommendations for its implementation in low-income settings. The results highlight that AI can improve diagnostic accuracy, optimize resource management, and expand access to healthcare services, especially in regions with shortages of professionals and infrastruct. However, its implementation requires investments in technological infrastructure, professional training, and ethical considerations, such as the protection of patient data. The conclusion is that AI can revolutionize clinical practice in Angola, provided it is implemented strategically, with investments in infrastructure, professional training, and ethical considerations. This study contributes to the advancement of scientific knowledge and the formulation of evidence-based public policies, aiming to promote equity and efficiency in the Angolan healthcare system.

This report presents a general overview of the economics literature on technological change and focuses particularly on the interface between the public and private sectors in promoting the transfer and diffusion of new technologies. Our ability to transfer and diffuse new technologies is generally recognized as a key to increased productivity in the United States and this country's ability to compete internationally. A great deal of research has been done on technology transfer and diffusion by various disciplines and from numerous perspectives. Unfortunately, the policy implications of those different works are not always consistent. Further, the different disciplines have difficulty in communicating even when addressing the same issues and drawing the same general conclusions. The primary objective of this report is to lessen the chasm among the disciplines with respect to technology transfer and diffusion by summarizing the perspectives presented in the economics literature. The document is intended primarily for an interdisciplinary audience. The discussion begins with an overview of the economics literature on technological change and focuses on what economists commonly refer to as the Schumpeter trilogy--i.e., invention, innovation, and diffusion. Economists typically view technological change to occur in these three distinct steps and have formulated conceptual frameworks that suggest how and why each step in the process of technological change takes place. After defining these three steps, the report presents brief overviews of the seminal conceptual and empirical works in the three areas. Of key concern is an overview of the types of questions historically posed by economists and the degree to which economists have reached a consensus on these questions. The report then abstracts from this larger picture of technological change and focuses specifically on the interface between the public and private sectors. Within this second thrust, the report poses and attempts to answer two general questions: (1) Why have economists argued for government involvement to promote technological change? This issue leads to a brief discussion of market failures that inhibit the invention, innovation, and diffusion of new technologies. (2) Where and how can the public sector interface with the private sector to correct the market failures or, alternatively, take actions to counteract the effects of market failures? The role of the federal government in the innovative process remains the subject of significant debate by economists. Although most economists would agree that some role must be played by the public sector, our current conceptual and empirical knowledge is lacking. Little consensus has thus been reached about how the government should respond to the problem in general, and even less consensus exists about how particular technologies in particular markets should be dealt with. The report suggests that the public sector can encourage the process of innovation by either directly participating in the process of technical change or by indirectly stimulating the private sector's innovative activities. Although both methods have been shown to promote technical change, economists have not yet developed a generally agreed upon formula that dictates what method is most appropriate in any given case. It is likely that the arguments by economists with respect to the government's role in technological change will become more definitive as more detailed conceptual and empirical studies are completed. It is unlikely, however, due to the number of dynamic factors that are known to influence the innovative process, that the economics profession will develop a formula or set of formulae for promoting technical change or the involvement of the public sector in that change. A movement toward interdisciplinary research, which is currently underway, is the most promising avenue for studying the role of public policy in promoting technical change.

Public sector agricultural R&D has been an important source of new technologies and ideas for new technologies since the beginning of the Twentieth Century. The traditional model of the relationship between the public and private sector in the United States has discipline-based university departments doing the basic research, state agricultural experiment stations and the US Department of Agriculture institutions doing strategic or generic research, state experiment stations and private companies doing the applied work of developing technologies for farmers and then the extension system popularizing the new technology. In recent years stagnant levels of public research funding, changes in the laws governing public research (particularly the Bayh-Dole Act), and major investments by private companies in basic and strategic biotechnology have led to new institutional relationships between the public and private sector. Collaborative research by the public and private sector has grown. New institutions for transferring technology from the public to the private sector have evolved-offices of technology transfer and companies based on public sector technology with partial university ownership. Many of the same forces that led to institutional changes in the United States have also been putting pressure on less developed country (LDC) research institutions-declining public budgets, ideological and legal changes, and opportunities to collaborate with the private sector. The objectives of this article are to answer the following questions:

This chapter explores the intersection of Artificial Intelligence (AI) and governance, emphasizing the public sector's dual role as an innovator and a regulator. It begins with a theoretical foundation on innovation, defining its dimensions and triggers, as articulated by thinkers such as Schumpeter and Christensen. The discussion highlights how innovation extends beyond economic motives, with the public sector playing a significant role in fostering societal advancement. The chapter addresses the perception of the public sector as resistant to innovation, showcasing examples of ICT advancements in Southeast Asia, including e-government initiatives in the Philippines. Despite bureaucratic and institutional challenges, these cases demonstrate how the public sector has successfully utilized technology to improve transparency, efficiency, and citizen engagement. The transformative potential of AI is categorized into three areas: streamlining bureaucracy, enhancing democratic accountability, and improving public service delivery. Applications include automated tax compliance, corruptionresistant procurement processes, citizen engagement platforms, and efficient resource allocation in sectors like healthcare and transportation. Challenges such as data bias, ethical concerns, and environmental impact are discussed alongside the need for a robust regulatory framework. The chapter advocates for ecological safeguards, human accountability in the use of AI, and equitable access to AI innovations. International cooperation is critical for establishing global norms and inclusive AI governance. Ultimately, the chapter affirms that the public sector, by balancing innovation with oversight, can harness AI to foster accountability, inclusiveness, and sustainable development.