. This finding highlights a significant gap in how these advanced systems perceive and predict human behavior, particularly in strategic scenarios. When tasked with understanding and forecasting human actions, these AI models often assume a higher level of rationality than what is typically observed in real-life situations. Humans, as complex and unpredictable beings, frequently make decisions influenced by emotions, biases, and various cognitive factors, which might not always align with purely rational choices. In strategic games or decision-making processes, where rationality is often key to success, AI models' overestimation of human intelligence can lead to inaccurate predictions. For instance, in a game of poker, an AI might expect human players to consistently make optimal moves, whereas, in reality, players might bluff, make impulsive decisions, or employ strategies that aren't strictly rational. This discrepancy between AI expectations and actual human behavior has important implications for the development and application of AI technology. As AI continues to integrate into various aspects of our lives, from customer service to healthcare, understanding and addressing this overestimation of human rationality will be crucial. It underscores the need for more nuanced AI models that can better account for the intricacies of human decision-making, ensuring more accurate and effective interactions between humans and machines. The study's findings also open up new avenues for research, encouraging the exploration of ways to enhance AI's understanding of human behavior, potentially leading to more sophisticated and adaptable AI systems in the future. As AI technology evolves, bridging the gap between AI perception and human reality will be essential for creating more harmonious and productive human-AI collaborations.