No matter what machine the software engineers build, the requirements are located in the environment" [Jackson’97]. This environment is part of the real world in which the machine is installed and the machine’s effect is observed and evaluated. The re-emergence of AI (especially the black-box deep learning solutions) and the unstoppable penetration of AI-based systems across industries, public sectors, and all walks of life make it important and timely for the requirements engineering (RE) community to discuss the role of environment in driving various activities: elicitation, modeling, implementation, testing, deployment, and evolution. With the machine becoming more intelligent and embedded, the environment is more open and dynamic. This year’s workshop objectives are to bring the interested researchers and practitioners together, exchange ideas, discuss ongoing work, and work together as a community to explore the capabilities and limitations of ChatGPT as a requirements modeling helper. In particular, the workshop participants will work in small groups on an agreed set of RE problems (scenarios), and interact with ChatGPT to build a requirements model in problem frames, goal models, UMLs, etc. Throughout this working session, we will share our experience as a community in the kinds of good and bad questions that ChatGPT responses, the resulting model’s quality or the lack thereof, etc.