The integration of Artificial Intelligence (AI) in engineering education presents a transformative potential to enhance teaching methodologies, personalize learning experiences, and improve student engagement. However, its adoption is fraught with significant challenges. This paper explores the main problematic aspects of applying AI in engineering education, including issues related to data privacy, ethical concerns, the digital divide, faculty readiness, and the reliability of AI-driven assessments. The lack of standardized AI frameworks for curriculum development and the need for interdisciplinary collaboration further complicate implementation. Additionally, AI-based educational tools require robust infrastructure and continuous updates to remain effective. While AI can provide adaptive learning and automation of administrative tasks, its limitations in fostering critical thinking and hands-on problem-solving raise concerns about over-reliance on technology. This paper highlights these challenges and a case of application generative Ai in education.