## 1 Introduction  
The technological advancements of the past decade have positioned artificial intelligence (AI) as a transformative force across various sectors, with particularly significant impacts in the realm of healthcare management. The integration of AI promises to revolutionize healthcare processes, improve patient care, and optimize emergency responses by leveraging complex data to inform rapid, evidence-based decisions. However, despite growing enthusiasm, the adoption of AI in healthcare also presents unique challenges, necessitating a careful examination of its operational, strategic, and emergency implications. In addition to AI, other emerging technologies, such as augmented reality (AR), have shown potential in optimizing processes and improving outcomes in various sectors, including healthcare and training. For instance, recent studies on AR for corporate training demonstrate its ability to enhance learning outcomes and reduce errors through real-time, immersive experiences [1]. ([PERSON] et al., 2018). In the face of widespread health challenges that have put global healthcare systems under intense pressure, AI has offered innovative solutions for managing unprecedented health crises, highlighting the urgency of scientifically assessing its impact. Thus, this study contributes by providing a comprehensive evaluation of AI's impact on healthcare management, focusing on its potential to enhance operational efficiency, strategic decision making, and emergency preparedness. Additionally, this work explores variations in AI's impact based on temporal and geographical contexts, offering valuable insights into how AI can be optimally integrated into diverse healthcare systems. The integration of artificial intelligence (AI) in the healthcare sector represents one of the most significant technological advancements in recent years, promising to transform healthcare management through process optimization, improvement in patient care, and effectiveness in emergency responses. The integration of AI in healthcare improves the quality of medical education and scientific publications, while also enhancing the resilience of healthcare facilities during emergencies [2]. The implementation of AI technologies has been shown to support the reproducibility of scientific findings, a cornerstone for advancing medical knowledge and practices [3]. Furthermore, the development and testing of tools to assess the flexibility and resilience of healthcare infrastructure highlight AI's potential to prepare and adapt healthcare systems for emergency situations [4]. It is crucial to emphasize the importance of ethical and regulatory oversight in the use of artificial intelligence in the healthcare sector, to ensure that AI applications are safe and that the privacy of patient data is respected [5]. Additionally, the need to develop specific guidelines for reporting and evaluating AI in healthcare has been identified, to support systematic reviews and meta-analyses that ensure transparency and reproducibility of results [6]. In the United States and Europe, regulatory frameworks are evolving to keep pace with advancements in artificial intelligence in healthcare. Regulators, such as the FDA in the United States, are working to balance technological innovation with patient safety and privacy [7]. In Europe, the 2021 European Union Health Technology Assessment (HTA) regulation represents a significant step towards harmonizing evaluation procedures for technologies, including AI-based tools, across member states. This regulation aims to ensure that AI adoption in healthcare meets standards of safety, efficacy, and transparency, contributing to the overall improvement of healthcare quality [8]. Similarly, in Asia, countries like China and Japan are heavily investing in AI integration within their healthcare systems. In China, privacy protection is a central concern in AI regulation in healthcare, with specific regulations and accountability mechanisms needed to safeguard personal data.