Human–Artificial Intelligence (Human–AI) interaction has become a significant area of research in contemporary higher education, as students increasingly rely on AI-based systems for learning, problem-solving, and academic decision-making. The integration of generative AI tools, intelligent tutoring systems, recommendation engines, and decision-support technologies has transformed the cognitive and behavioral patterns of students. These technologies assist learners in processing information, evaluating alternatives, and making academic decisions more efficiently, thereby reshaping traditional decision-making behaviors. The present study investigates the relationship between human–AI interaction and decision-making behaviors among students in higher education institutions. A quantitative cross-sectional research design was employed involving 250 undergraduate and postgraduate students. Human–AI interaction was assessed through AI usage frequency, trust in AI systems, and dependency on AI tools, while decision-making behavior was evaluated through analytical thinking, problem-solving ability, critical thinking, and academic decision confidence. Descriptive statistics and Pearson correlation analysis were used for data analysis. The findings reveal a moderate to high level of human–AI interaction among students and a significant positive relationship between AI interaction and decision-making behaviors. Students with higher engagement in AI systems demonstrated improved decision-making confidence, analytical reasoning, and problem-solving abilities. The study concludes that human–AI interaction plays a crucial role in shaping student decision-making behaviors and recommends the development of AI literacy, ethical awareness, and critical thinking skills for responsible AI usage in higher education.