<p>As functional and technological differences among armchair products continue to diminish, furniture companies are placing increasing emphasis on optimizing product form to enhance users’ emotional experiences. This study proposes a novel integrated artificial intelligence approach that combines Stable Diffusion (SD) with the Multi-Objective Coati Optimization Algorithm (MOCOA) to enable the automatic generation of high-quality, creative furniture designs that precisely align with users’ multi-dimensional requirements. First, a LoRA-enhanced SD model is trained to generate creative images of Ming-style armchairs that are distinct from existing market offerings. The generated armchairs are then deconstructed in terms of form to identify their design characteristics (DCs). Second, the CRITIC method is employed to extract key user requirements (URs). Third, an intelligent mapping model is established between the DCs of the innovative armchairs and the key URs, which serves as the foundation for multi-objective optimization. MOCOA is subsequently used to obtain Pareto-optimal solutions that best satisfy these key URs. Representative solutions are identified through clustering analysis of the Pareto front. These representative candidates are then rapidly transformed from conceptual sketches into high-resolution renderings using SD, followed by detailed engineering modeling. A case study on Ming-style armchairs demonstrates that the generated creative solutions can accurately meet diverse user requirements, thereby validating the feasibility and advanced capabilities of the proposed approach. The method introduced in this study enables design teams to rapidly generate an unlimited range of innovative ideas and automatically produce visual representations that reflect user preferences. This significantly enhances both creativity and efficiency in the design process, addressing key limitations of traditional design paradigms.</p>