This study examines the drivers and barriers impacting the adoption and diffusion of artificial intelligence (AI) in public administration. Key drivers, categorized by technological, organizational, environmental, and human factors, are explored as facilitators for effective AI integration....

Iterative educational and public administration transformation projects (ETP) are important for the enhancements of their sustainability, performances, and longevity. ETPs are complex, due to the inter-linking AI, lack of the adoption of a polymathic and holistic approaches, and the integration...

This chapter examines how AI might alter public administration by improving efficiency, accessibility, and decision-making. AI automates ordinary jobs, freeing up public servants for high-impact work. Predictive analytics improve government operations by offering data-driven insights for...

Advanced educational and public administration transformation projects (EPTP) are crucial for academic, public sector (PS), and business institutions. Unfortunately, such EPTPs are complex and have high failure rates, because of the various issues like the lack of experienced personal which...

The advent of social networks has undoubtedly changed the way we disseminate information, communicate, and interact with one another. The ways in which AI and social networking are beneficial for higher education have come under much scrutiny. This chapter examines multifaceted roles that AI and...

This study investigates the influence of artificial intelligence (AI) on student enrollment in higher educational institutions in Kerala, with a particular emphasis on the mediating role of customer relationship management (CRM) systems. Employing a descriptive research design, a self-prepared...

Many businesses have to operate within the framework of national and international standards to meet customers' expectations, security requirements, and environmental regulations. Compared to other industries, the aviation industry has high-security requirements. However, the continuous...

As a result of the transition of many systems to the digital age with the developing technology, it has been observed that fraud reports have increased, and this increase requires banks to develop strong systems against these threats. The inadequacy and slowness of the manual method currently...

This study uses machine learning-based causal analysis to analyze the relationship between government health spending and socioeconomic characteristics. The research aims to enhance public health and promote economic stability by allocating significant resources to healthcare. Conventional...

Istanbul, hosting millions of tourists annually, faces significant air pollution challenges, impacting both health and climate. The air quality index (AQI) is vital for assessing pollution and its health effects. This study predicts AQI levels in Istanbul using machine learning models (XGBoost...