For modeling the number of visits in Stopi\'{c}a cave (Serbia) we consider the classical Auto-regressive Integrated Moving Average (ARIMA) model, Machine Learning (ML) method Support Vector Regression (SVR), and hybrid NeuralPropeth method which combines classical and ML concepts. The most accurate predictions were obtained with NeuralPropeth which includes the seasonal component and growing trend of time-series. In addition, non-linearity is modeled by shallow Neural Network (NN), and Google Trend is incorporated as an exogenous variable. Modeling tourist demand represents great importance for management structures and decision-makers due to its applicability in establishing sustainable tourism utilization strategies in environmentally vulnerable destinations such as caves. The data provided insights into the tourist demand in Stopi\'{c}a cave and preliminary data for addressing the issues of carrying capacity within the most visited cave in Serbia.

The World Economic Forum (WEF) publishes its report entitled, "Business Life and Gender Differences," every year. The report got a new name for the first time this year; as you can imagine, this title relates to artificial intelligence (AI). The WEF researched the rates of female AI experts in the workforce in 146 countries. Some important points in the report include caring for children at home, robots taking the place of workers at factories and offices being the most significant factors in women losing their jobs. The WEF Center for the New Economy and Society President Saadia Zahidi says that robotic and artificial intelligence technologies take place in fields where women traditionally work, such as management, customer relations and telemarketing.