The paper "Transforming Digital Marketing with Generative AI" by Tasin Islam, Alina Miron, Monomita Nandy, Jyoti Choudrie, Xiaohui Liu, and Yongmin Li introduces MARK-GEN, a conceptual framework that leverages generative artificial intelligence (AI) models to transform marketing content creation. The framework provides a structured approach for businesses to employ generative AI in producing marketing materials, addressing the challenges of content creation and innovation in digital marketing. The authors present two case studies within the fashion industry to demonstrate how MARK-GEN can generate compelling marketing content using generative AI technologies. The paper builds on previous technical developments in virtual try-on models, including image-based, multi-pose, and image-to-video techniques. It aims to provide a clear and understandable framework for businesses to develop generative AI models that can assist them in achieving their marketing goals. The framework outlines seven iterative steps: defining the marketing aim, data collection, data processing, model design, model training, model evaluation, and deployment. The case studies highlight the potential benefits of using generative AI in the fashion industry, such as creating unique and customized content that resonates with the target audience. The paper also discusses the importance of data privacy and ethical considerations in the use of generative AI for marketing.The paper "Transforming Digital Marketing with Generative AI" by Tasin Islam, Alina Miron, Monomita Nandy, Jyoti Choudrie, Xiaohui Liu, and Yongmin Li introduces MARK-GEN, a conceptual framework that leverages generative artificial intelligence (AI) models to transform marketing content creation. The framework provides a structured approach for businesses to employ generative AI in producing marketing materials, addressing the challenges of content creation and innovation in digital marketing. The authors present two case studies within the fashion industry to demonstrate how MARK-GEN can generate compelling marketing content using generative AI technologies. The paper builds on previous technical developments in virtual try-on models, including image-based, multi-pose, and image-to-video techniques. It aims to provide a clear and understandable framework for businesses to develop generative AI models that can assist them in achieving their marketing goals. The framework outlines seven iterative steps: defining the marketing aim, data collection, data processing, model design, model training, model evaluation, and deployment. The case studies highlight the potential benefits of using generative AI in the fashion industry, such as creating unique and customized content that resonates with the target audience. The paper also discusses the importance of data privacy and ethical considerations in the use of generative AI for marketing.