The rapid integration of intelligent systems into educational environments has transformed teaching, learning, assessment, and academic decision-making. Technologies such as intelligent tutoring systems, adaptive learning platforms, learning analytics, artificial intelligence-based assessment tools, and virtual learning assistants have created personalized learning environments that continuously respond to learners\' needs and performance. As educational institutions increasingly adopt these intelligent technologies, understanding how learners adapt to AI-supported educational systems has become an important area of interdisciplinary research. The present study examines the relationship between intelligent systems and human adaptation in educational settings using a quantitative cross-sectional research design. Data were collected from 250 respondents through a structured five-point Likert scale questionnaire and analyzed using descriptive statistics, Pearson correlation analysis, and multiple regression analysis. The findings indicate that intelligent systems significantly enhance adaptive learning behavior, learning engagement, digital competence, self-directed learning, and technology acceptance. The study concludes that successful implementation of intelligent educational systems depends not only on technological capabilities but also on learners\' adaptability, digital readiness, and positive behavioral responses. The findings provide practical implications for educators, institutional leaders, policymakers, and educational technology developers seeking to establish learner-centered and sustainable AI-supported educational environments.