This learning investigates the character of Artificial intelligence compelled applications in changing engineering education and their influence on student happiness with the prompt development of emerging learning machineries, there is a developing need to explore how Artificial intelligence can improve educational consequences although development holistic development, predominantly for engineering students. This study aims to bridge the gap between technological integration and the mental, emotional, and academic well-being of students in the engineering domain. A mixed-methods approach was employed, combining quantitative surveys and qualitative interviews to assess the effectiveness of AI tools in improving educational experiences and well-being. The study involved engineering students across various disciplines, utilizing AI-driven platforms such as intelligent tutoring systems, adaptive learning technologies, and data analytics to evaluate their impact on academic performance and well-being metrics. The findings indicate that AI applications significantly contribute to improved learning outcomes and enhance student well-being by offering personalized learning paths, reducing the cognitive load, and promoting better engagement with educational materials. The use of adaptive technologies also supported emotional resilience and a sense of academic belonging, which were found to be crucial for student success in engineering fields. The study underscores the transformative potential of AI-driven applications in shaping a more adaptive and supportive educational environment for engineering students. AI technologies not only improve academic performance but also play a pivotal role in enhancing student well-being. This research highlights the importance of integrating AI with student-centric pedagogical strategies to achieve sustainable educational transformations.