Abstract

The emergence of generative artificial intelligence (AI) models has captured the attention of businesses and researchers alike. In this article, we aim to evaluate the efficacy of generative AI in creating marketing content and propose an integration method of generative AI with an information system that processes, profiles, and generates marketing content. We examine the potential of generative AI in four domains: content generation, content variety, content quality, and personalized content. While generative AI has shown significant proficiency in generating varied and aesthetic visual and textual content, challenges remain in achieving high-quality, personalized content. We conducted two studies to evaluate the ability of generative AI to create marketing content. In the first study, we show that AI can create high-quality images that are just as impactful as human-created images. We then test an implementation of automated AI advertising personalization and find that such a method is successful at personalizing advertisements to consumers and increasing customer engagement. The article concludes by suggesting steps necessary for completely automated advertisement personalization.

Recommended Citation

Smolinski, P. R., Januszewicz, J., & Winiarski, J. (2023). Towards Completely Automated Advertisement Personalization: An Integration of Generative AI and Information Systems. In A. R. da Silva, M. M. da Silva, J. Estima, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development, Organizational Aspects and Societal Trends (ISD2023 Proceedings). Lisbon, Protugal: Instituto Superior Técnico. ISBN: 978-989-33-5509-1. https://doi.org/10.62036/ISD.2023.60

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Towards Completely Automated Advertisement Personalization: An Integration of Generative AI and Information Systems

The emergence of generative artificial intelligence (AI) models has captured the attention of businesses and researchers alike. In this article, we aim to evaluate the efficacy of generative AI in creating marketing content and propose an integration method of generative AI with an information system that processes, profiles, and generates marketing content. We examine the potential of generative AI in four domains: content generation, content variety, content quality, and personalized content. While generative AI has shown significant proficiency in generating varied and aesthetic visual and textual content, challenges remain in achieving high-quality, personalized content. We conducted two studies to evaluate the ability of generative AI to create marketing content. In the first study, we show that AI can create high-quality images that are just as impactful as human-created images. We then test an implementation of automated AI advertising personalization and find that such a method is successful at personalizing advertisements to consumers and increasing customer engagement. The article concludes by suggesting steps necessary for completely automated advertisement personalization.