EXPERT CONSENSUS ON FUTURE MARKET DEVELOPMENT OF THE “AI + CHEMICAL ENGINEERING INDUSTRY”: A DELPHI SURVEY

With the rapid development of the global artificial intelligence (AI) industry, large-scale general AI models are demonstrating diverse potential and distinct development characteristics across the chemical engineering industry chain. Traditional chemical manufacturing relies heavily on physical experiments and validation tests, which are time-consuming, costly, and often involve high safety risks. In contrast, “AI + chemical engineering industry” (i.e., AI-enabled chemical engineering technologies) integrates physical and digital spaces, enabling design, simulation, and verification processes to be efficiently conducted in virtual environments. This approach offers advantages such as near-zero marginal cost, flexible system architecture, and significantly reduced reliance on physical testing. As a result, technological innovation in chemical engineering is shifting from experience-based trial and error toward a data-driven paradigm, substantially improving efficiency and accuracy. This research explores the market potential of the “AI + chemical engineering industry” using the Delphi method, drawing on insights from 20 experts in Henan Province, China. Through case analyses of three representative sectors (AI-driven coal, non-ferrous metals, and new energy industries), the research forecasts emerging market opportunities and future development directions for AI integration within the chemical engineering industry chain. The findings reflect a consensus on the future trajectory of these AI-integrated sectors, suggesting that AI adoption will revitalize the chemical engineering industry, enhance safety and quality management systems, stimulate innovative integration models, and promote the development of industrial clusters.