The integration of Artificial Intelligence (AI) into Information Systems (IS) design is significantly reshaping traditional development processes, introducing automation, intelligent decision-making, and advanced data analysis capabilities. This systematic review explores the current landscape of AI-driven IS design, focusing on key AI techniques—such as machine learning, natural language processing, and generative models—that are increasingly applied across various stages of system development. The paper examines how these AI technologies are enhancing requirement engineering, system modeling, and process optimization. It also evaluates the benefits of AI in improving system efficiency, decision-making, and user experiences, while addressing challenges such as data quality, technical expertise, and ethical concerns. Finally, the review looks toward the future of AI in IS design, highlighting emerging trends such as low-code platforms and explainable AI. The findings emphasize the need for interdisciplinary collaboration and the development of transparent, responsible AI frameworks to fully realize the potential of intelligent, adaptive, and user-centric information systems.