AI in Multidisciplinary Engineering: A Holistic Review of Technologies and Trends

Abstract

Artificial Intelligence (AI) has evolved from a computational tool into a transformative force reshaping every branch of engineering. This review paper explores the depth and breadth of AI integration across major engineering disciplines—including Mechanical, Electrical, Electronics, Computer Science, Civil, Chemical, Aerospace, Biomedical, and Industrial Engineering. By analysing recent advances in machine learning, deep learning, computer vision, natural language processing, and intelligent automation, the paper highlights how AI enhances design optimization, predictive maintenance, smart manufacturing, structural health monitoring, energy management, autonomous systems, process control, and human–machine collaboration. The study also examines domain-specific applications such as digital twins, Industry 4.0, AI-driven materials discovery, intelligent transportation, personalized healthcare systems, and sustainable infrastructure development. Furthermore, the paper discusses emerging challenges involving data quality, interoperability, ethics, and the need for interdisciplinary skill development. This comprehensive review demonstrates that AI is not merely an add-on technology but a foundational enabler driving innovation, efficiency, and intelligent decision-making across all engineering fields, shaping the future of global technological advancement.