As AI techniques such as machine learning, neural networks, and natural language processing continue to improve at a very fast rate, they will be increasingly used in education. This will lead to more flexible and fair learning experiences that are tailored to each student’s strengths and needs. This paper looks at the main AI features that power some of the most important education technology innovations, such as smart tutoring systems, personalized virtual tutors, automated content creation, and smart assessment analytics. After looking at results and examples from a number of important areas, such as simulated environments, data-driven ideas, and conversation-based tutoring agents, the main pros and cons of these new sociotechnical systems are discussed. AI has the ability to improve teaching and learning in ways that people cannot. However, as the field grows, it is important to think about ethics, responsibility, and including everyone. A study of adding teachers versus replacing them is also performed, and framework principles for fair learning progress are proposed. The summary is easy to understand and discusses past successes, current skills, current trends, and possible future developments. It tells many people about both good and bad outcomes and stresses how important it is to have freedom, choice, and design that is based on results for systems that are moral and help students learn.