Human-AI collaboration in chemical engineering

This chapter examines the revolutionary influence of artificial intelligence (AI) on chemical engineering, emphasizing the synergistic interplay between human knowledge and AI technology. It analyzes the progression of AI applications from basic rule-based systems to advanced machine learning models adept at managing intricate data sets and enhancing chemical processes. The chapter explores many AI approaches, including deep learning, natural language processing, and automated decision-making, in relation to essential activities such as process design, response optimization, and safety evaluations. The chapter also emphasizes the creation of transparent AI-assisted frameworks that enable the smooth incorporation of AI technologies into conventional chemical engineering processes. AI has been incorporated into operations by 35% of companies. AI is being used in one form or another by 25% of small businesses. 42% of firms are thinking about integrating AI into their operations in the future. More than half of big industries with more than 5,000 workers use AI. This chapter illustrates the effectiveness of fine-tuned big language models in chemical text mining, highlighting their capacity to extract pertinent information from extensive chemical literature, thus considerably reducing the time and effort needed for research endeavors. The chapter also discusses human aspects in AI interfaces, highlighting the significance of user experience in promoting productive cooperation. Examining parameters associated with cognitive load and situational awareness encourages constructing AI systems that enhance human skills. This chapter clarifies the prospective role of human-AI collaboration in fostering innovation and sustainability in chemical engineering. © 2026 Elsevier Inc. All rights reserved.