The objective of the current study is to explore how certain attributes of chief executive officers (CEOs), such as their innovativeness, knowledge of information systems (IS), and trust in technology and technological factors (Compatibility, relative advantage, and complexity) on the utilization of accounting information systems (AIS) in companies across various industries in Jordan. The research gathered data through a structured questionnaire, which included a 7-point scale. The respondents were CEO/owner of small, medium, and large enterprises (SMEs) in Jordan. A total of 315 valid responses were analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique. The findings indicated a significant and positive correlation between complexity, compatibility, CEOs trust in technologies, CEOs information system (IS) knowledge, and the utilization of AIS. However, CEO innovativeness and relative advantage have an insignificant impact on AIS use. The present study is the first to examine CEO characteristics in the AIS context. The practical and theoretical implications derived from the empirical findings of this study offer valuable insights for managers and practitioners. These insights aim to enhance their understanding of the fundamental factors crucial for the successful implementation of AIS in companies, ultimately contributing to improved firm performance.

This study examines the relationship between the types of Artificial Intelligence (AI) technology employed and monitoring tax payments. A thorough literature review is conducted to examine different AI technologies in the context of tax administration. These include machine learning algorithms (MLA), natural language processing (NLP) technology, robotic process automation (RPA), explainable artificial intelligence (XAI), and advanced data analytics techniques (DAT). A variety of technologies, such as big data analytics, task automation, task automation, unstructured data analysis, and predictive modeling, are available to improve tax payment monitoring procedures. Recommendations for further study to expand our knowledge and use of AI in tax payment monitoring are included, along with the consequences of AI adoption for tax authorities, policymakers, and practitioners.

The aim of this study was to examine how the implications of the Covid-19 pandemic moderate the impact of Artificial Intelligence (AI) on the effective application of Cyber Governance (CG) in Islamic banks. A total of 93 questionnaires from branch heads of Islamic banks were used in this study, and the data were analyzed using the Statistical Package for Social Sciences (SPSS) through descriptive-analytical methods. The findings indicated that AI has a significant influence on the effective application of CG in Islamic banks. The study also revealed that the Covid-19 Pandemic positively moderates the influence of AI on the effective application of CG in Islamic banks. The results of this study have implications for regulators and decision-makers in proposing new legislation to effectively apply CG in the Islamic banking sector, which can help protect public funds and limit cyber-attacks. This study is the first to investigate the moderating effect of the Covid-19 pandemic on the influence of AI on the effective application of CG in Islamic banks.