Special education can be defined as specially designed instruction and other related services to meet special needs, which ensures the students with disabilities succeed both academically and personally. Briefly, special education challenges entail proper identification of students, effective and practical development of the Individualized Education Programs, provision of inclusive practices, management of behavior problems, and transition planning. Progress in technology, more so in Artificial Intelligence, is changing special education through bettering individual learning, participation, and accessibility. It involves AI technologies in machine learning and natural language processing, and equally provides assistive tools of speech recognition and synthesis. The system of adaptive learning offers customized education experiences, speech technologies support communication, and comprehension through visual recognition tools. Some of these examples include visual recognition tools to help students with a visual processing problem, predictive analytics that identifies students at risk, and hence gives a way or path towards the individualization of learning intervention. AI-driven software has shown clear benefits in academic performance and behavioral development through real-time feedback, increased engagement, and data-driven decision-making. However, problems that beset integrating AI into special education include the variability of student needs, data privacy, educator training, and striking a balance between AI and human expertise. Tackling these challenges will demand continuous research efforts, professional learning, and attention to ethical practices that maximize AI's potential benefits in facilitating diverse learners.