Maintenance schedules are scheduled ahead of time and automatically based on the continuous monitoring of the equipment by statistical methods, thanks to artificial intelligence-enabled digital transformation and the best fit model based on Machine Management Index in a pedagogical system. One of the most important aspects of universities is the widespread use of machine learning methods to evaluate students' progress. Machine learning approaches are designed to speed up the learning process without sacrificing accuracy. The dynamics of teaching and learning have shifted since the introduction of modern technological tools. The educational system as a whole has changed and developed over time. These days, people can get an education outside of the classroom as well, thanks to the proliferation of online courses and resources. Everyone's professional life begins with their education. By analyzing past data, artificial intelligence methods can resolve existing problems. When applied properly, artificial intelligence can be a highly efficient method for solving problems with a predictable and repeatable solution space. The learner's personality can be predicted based on a number of factors using machine learning approaches. This article examines how AI may improve digital learning in education management systems to sustain the education ecosystem. AI in education improves student results, learning experiences, and administrative processes. This study discusses AI applications in education management systems and associated problems and opportunities. We also explore ethical issues and the roadmap for using AI to improve education. Educational institutions can provide individualized curriculum for students based on their unique personalities and areas of interest. Institutions of higher learning can benefit greatly from this instrument for personality prediction by recommending a course of study that will better prepare students to enter the field of their choice and achieve professional success.