Research on the Application and Ethical Boundaries of AI-Generated Content in Personalized Marketing Content Generation

Abstract

The rapid advancement of generative artificial intelligence is propelling personalized marketing into a new intelligent phase. This study systematically analyzes the technical mechanisms of AIGC-driven content generation, including semantic parsing based on large language models, visual generation through multimodal fusion, and the paradigm shift from static templates to dynamic interaction. It constructs a collaborative framework encompassing in-depth user profile development, brand semantic field calibration, and content ecosystem architecture, while conducting an in-depth examination of ethical boundaries concerning data privacy, algorithmic transparency, content authenticity, and cognitive autonomy. Through this dual-dimensional analysis of technology and ethics, the research provides theoretical foundation and practical guidance for responsible innovation in the application of AIGC within the marketing domain.