The COVID-19 pandemic has worked as a catalyst, pushing governments, private companies, and healthcare facilities to design, develop, and adopt innovative solutions to control it, as is often the case when people are driven by necessity. After 18 months since the first case, it is time to think about the pros and cons of such technologies, including artificial intelligence—which is probably the most complex and misunderstood by non-specialists—in order to get the most out of them, and to suggest future improvements and proper adoption. The aim of this narrative review was to select the relevant papers that directly address the adoption of artificial intelligence and new technologies in the management of pandemics and communicable diseases such as SARS-CoV-2: environmental measures; acquisition and sharing of knowledge in the general population and among clinicians; development and management of drugs and vaccines; remote psychological support of patients; remote monitoring, diagnosis, and follow-up; and maximization and rationalization of human and material resources in the hospital environment.

Introduction: The study aims to describe the organization of one accredited school of Anesthesia and Intensive Care of University of Modena and Reggio Emilia, Italy. The analysis of the post-graduation period aims to measure the time-to-first job, the perceived challenges, what postgraduate residents choose as first employ, and the overall satisfaction rating of a cohort of residents completing their training until 2017 with the usual and standard training program. Methods: We collected organization and administrative records of the five-year program of the A-IC School of 4 cohorts of residents who joined from 2009 to 2012 and we performed a survey. We also analyzed the differences among school cohorts during the medical training. In the end, it was investigated as a reason to choose hub hospitals or not. Results: The focus of the training activities revolved around the operating room with a mean of 30.41 ± 6.6 (sd), months followed by Intensive care with 17.29 ± 4.49 (sd) months. Although 7.5% of the respondents were not fully satisfied of the school’s program, 89.7% of residents rated their training as adequate. In fact, 97.2% respondents reported they could overcome the professional challenges they faced after graduation. The multiple variables logistic regression showed a correlation among working in hub hospitals and training performed in university hospitals with a p value of 0.015. Conclusion: This paper describes the postgraduation period. This point should be examined as an integral part of the accreditation procedure. Knowing the satisfaction rate, perception autonomy, and which type of hospitals are preferred can measure the education training capacity of a postgraduation school.