Generative Artificial Intelligence (AIGC)-based Platform Economy Content Production Model and Marketing Strategy Innovation

As the platform economy enters the deep-water zone of intelligent transformation, generative artificial intelligence (AIGC) technology is reshaping the core logic of content production and marketing strategy. In this paper, we construct the ‘AIGC-DRIVE’ dynamic closed-loop model to explain the role of AIGC in the innovation of platform economy content production and marketing strategy, and carry out efficiency comparison, AB test of AIGC advertisement strategy, and research on users' privacy concerns, as well as combining with the typical case studies of Jitterbug and SHEIN. It is found that AIGC can greatly improve the production efficiency and support the real-time optimisation of dynamic marketing strategies through data-driven multimodal content generation; however, the application of the technology faces the risks of content homogenisation, algorithmic black-boxing and user privacy leakage. This paper proposes a synergistic mechanism of ‘technology embedding - institutional constraints - user feedback’ to achieve sustainable development, which provides a theoretical basis and a practical path for the design of the governance framework of AIGC in the platform economy.