Digitalization has become an important part of human lives that occurs in many fields, ranging from education to labor. Artificial intelligence is one of the most important disruptive technologies, which has produced massive changes in current medical practices, such as MRI, X-ray, and surgeries. AI-based surgeries present lower risks to patients and support medical specialists when it comes to burnout and more challenging operations, which can be more easily performed with the help of robots. The COVID-19 pandemic had a huge impact on healthcare systems due to the large number of patients that overburdened medical healthcare professionals and the medical capacities of hospitals. In this paper, we approach AI-based tools, which have a significant impact on various specializations in medicine under the form of robots, based on an extensive literature review. The research methods consist of a quantitative study conducted on a sample of 50 nurses with the purpose of assessing the awareness of nurses regarding digital technologies used in the medical field, focusing mainly on their capacity to classify digital technological risks that may occur in a public healthcare system. The results show that most of the respondents (62%) are aware of digital applications used in hospitals and are able to classify and manage the risks that may occur. After conducting our research, we found that nurses have a certain degree of reluctance when it comes to the introduction of digital technologies in the medical field.

Recent financial crises, heightened geopolitical instability, sustained financial volatility, and broader global uncertainty have increased the exposure of private sector organizations to emerging and interconnected economic risks. In this context, systematic and sustainable approaches to organizational risk management are becoming increasingly important for maintaining organizational resilience and economic security. Given the persistent instability of markets and the prospect of structural economic changes toward 2030, this study examines how key organizational and risk-related factors influence perceived economic security under crisis conditions. The empirical investigation was conducted on a sample of 205 employees from private sector organizations. Exploratory factor analysis (EFA) was used to validate the structure of the constructs, while structural equation modeling (SEM) was applied to test the relationships among the variables and provide a model-driven assessment of the determinants of perceived economic security. The findings show that all factors included in the proposed model have a significant influence on perceived economic security during periods of crisis. The results highlight the importance of systematic risk identification, assessment, monitoring, and management, as well as organizational learning from previous crises, in responding to a changing and uncertain economic environment. Under conditions of continued global uncertainty, volatility, and structural transformation, the development and continuous improvement of organizational risk management systems can strengthen organizational resilience and support economic security over time.