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The definition of AI lacks a universal consensus, with varying perspectives on its capabilities. AI is often conceptualized as machines or computer systems mimicking human thought and behavior, either by performing tasks requiring human-like intelligence, such as decision-making, or by employing rational thinking based on logic and the careful consideration of options (Russell & Norvig, 2021). AI can be classified as “weak AI”, excelling in specific domains but incapable of autonomously solving problems outside those areas (Wamba et al., 2021), while speculation surrounds the potential for AI to achieve singularity, becoming “conscious/self-aware AI” if it surpasses human intelligence (Kaplan & Haenlein, 2019).
Artificial Intelligence systems are revolutionizing workplace practices by injecting unprecedented value into complex processes and decision-making frameworks. This wave of technological advancement is not confined to the private sector; it is also making significant strides within the public sector, as evidenced by the growing body of research (Wirtz et al., 2019). Despite high expectations that AI will enhance the public sector’s operational efficiency, services and decision-making quality, the integration of AI technologies into public organizations has been modest (Selten & Klievink, 2024). Cutting-edge AI technologies, including large language models, computer vision, generative AI, robotics, natural language processing (NLP), and machine learning algorithms, are evolving at a breakneck pace. These advancements enable AI to tackle increasingly sophisticated tasks, paving the way for its potential to significantly improve the efficiency and effectiveness of public sector operations and services (Madan & Ashok, 2023; Margetts & Dorobantu, 2019; Selten & Klievink, 2024). However, many public organizations find themselves at a crossroads, eager to harness these innovative technologies yet hindered by the rapid technological evolution of AI. This challenge is compounded by a range of barriers that impede the adoption and effective utilization of AI within the public sector. Such barriers include, but are not limited to, issues related to data governance, ethical considerations, and a lack of technical expertise for implementing AI solutions (Kempeneer & Heylen, 2023; Madan & Ashok, 2023; Mergel et al., 2023; Wirtz et al., 2019).
Managers hold a critical position within organizations, exerting substantial influence over the adoption of new technologies (Gagnon et al., 2000). Despite their significant impact, the perspectives of managers are often overlooked (Nielsen et al., 2019; Ullah et al., 2021). Research indicates that transformative leadership traits play a crucial role in influencing AI adoption in the public sector (Madan & Ashok, 2023). Chief information officers (CIOs) are also identified as key players in the adoption and dissemination of AI, requiring not just technical expertise but also political savvy to shape the design of enterprise systems within and across government agencies (Madan & Ashok, 2023). However, studies reveal that public managers, including CIOs, often make decisions regarding the use of AI and other technologies based on pre-existing attitudes and cognitive frames (Criado et al., 2021; Guenduez et al., 2020; Kempeneer & Heylen, 2023). This highlights the importance of understanding their attitudes and intentions to effectively address their concerns and potentially facilitate more successful AI implementations in public organizational settings.