Applications of Artificial Intelligence in Engineering: Current Status, Challenges, and Future Perspectives

Abstract

The rapid development of artificial intelligence (AI) has profoundly transformed the paradigm of modern engineering. This paper systematically reviews the current applications of AI in core engineering fields, including civil, mechanical, electrical, and chemical engineering, and analyzes the implementation paths of key technologies such as machine learning, deep learning, and reinforcement learning. By summarizing typical scenarios including intelligent design optimization, predictive maintenance, quality control, and autonomous decision-making, this study reveals the mechanism by which AI empowers engineering practices. Meanwhile, major challenges are thoroughly discussed, including data acquisition and quality, model interpretability, cross-domain generalization, and engineering ethics. Future prospects are also proposed for the deep integration of AI and engineering disciplines. This review aims to provide comprehensive theoretical references and practical guidance for researchers and engineers engaged in AI-driven engineering applications.