This paper examines the development, evolution, and application of Artificial Intelligence Generated Content (AIGC) technology, with a particular focus on its opportunities within the field of industrial design. Using the design of household furniture seating as a case study, the study verifies the feasibility of AIGC in industrial design through a four-stage process: Requirement Input, Concept Generation, Solution Screening, and Parameter Transformation (RGST). The Stable Diffusion tool was employed for implementation. In contrast to traditional workflows, the core value of AIGC lies in transcending conventional “human-AI collaboration” to establish a new paradigm where designers act as decision-makers rather than executors, focusing on requirement analysis, engineering adaptation, and ethical review. Experiments confirmed AIGC boosted efficiency, cut costs, and democratized design. Results offer a replicable RGST workflow for design practitioners and indicate that AIGC can shorten the concept-to-prototype cycle significantly.