This paper investigates behavioral patterns in online gambling through the application of artificial intelligence (AI), machine learning, and the Internet of Behavior (IoB) concept. The digital revolution has significantly increased the accessibility of online gambling, leading to complex behavioral patterns among players. Although many see gambling as a form of recreation, the increased availability also poses a risk of addiction. This study highlights the crucial role of artificial intelligence and machine learning in identifying problematic behaviors, such as excessive spending and prolonged gambling sessions. By analyzing data with the help of clinical practice and training MLP (Multi-Layer Perceptron) neural network from a sample of 200 players in the Republika Srpska and testing a neural network-based trained model on a broader sample of 5000 players, we identified risky patterns associated with online slot playing. This paper suggests implementing AI tools for early detection of problematic player behavior, with an emphasis on public health protection.