Artificial Intelligence (AI) has revolutionized assistive communication technologies with increased accessibility for individuals with speech, hearing, and cognitive impairments. This study discusses AI technologies such as speech-to-text transduction, NLP, predictive text input, and adaptive interfaces, highlighting the importance of such technologies in the communication process. A quantitative analysis of AI applications evaluates the effects of these applications on adaptive systems and real-time speech recognition. Results indicate that AI-based devices enhance efficiency in communication as well as enable participation and independence of individuals with disabilities in society. Continuous adaptation of system algorithms through machine learning enables repeated enhancement in accuracy, enhancing usability. Issues are in areas of ethical considerations regarding data privacy, algorithmic bias, and inclusive design demands to enable accessibility to all. Improvements in AI models should be pursued by future research to further personalize technologies. Accessibility challenges should be targeted at underserved populations. Future progress depends on integrative studies and collaborations among researchers in AI, clinicians, and policymakers in developing equitable access to AI-based assistive technologies. As AI continues to progress, its application in assistive communication is equally of great value in eliminating communication barriers as well as enabling people with impairment in numerous contexts.