Generative AI and Large Language Models in Engineering and Management: Opportunities and Challenges

The fast pace of Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) has brought unparalleled opportunities in engineering and management fields. Nevertheless, although these technologies are popularly debated, there is no coherent scholarly critique on their real-world applicability, limitations, and future possibilities. This review paper seeks to fill that gap by exploring systematically the potential, applications, and limitations of GenAI and LLMs in engineering and management areas. Based on a systematic literature review, the paper examines applications like AI-based design, predictive maintenance, strategic planning, and smart automation. It also critically analyzes risks like data bias, computational power, ethical issues, and governance challenges. Through comparative evaluation and selected case research, the research suggests implementable frameworks for ethical adoption, deployability with sustainability, and efficient human-AI collaboration. This article contributes to existing scholarly debates through the identification of research directions as well as providing advice for guiding responsible use of GenAI technologies in engineering and managerial applications.