Artificial Intelligence (AI) is fundamentally transforming higher education systems worldwide, particularly in university admissions processes. Traditional admissions systems rely heavily on manual evaluation of applications, academic transcripts, and supporting documentation, resulting in inefficiencies, scalability limitations, and potential human bias. AI technologies, including machine learning, natural language processing, computer vision, and intelligent automation, offer scalable and efficient solutions for automating application processing, enhancing decision-making accuracy, improving fraud detection, and optimizing applicant experience. This paper provides a comprehensive analysis of the role of AI in university application processes, examining technological architectures, operational benefits, ethical considerations, implementation challenges, and future developments. The study also evaluates global case studies and emerging trends in AI-driven admissions systems. The findings demonstrate that AI significantly improves admissions efficiency, scalability, and fairness when implemented with proper governance, transparency, and human oversight.