Generative Artificial Intelligence in Marketing : An Exploration of the Sustainability Dimensions

Sammanfattning

The development of generative artificial intelligence has increased rapidly since GPT-3 was introduced by OpenAI in the autumn of 2020. As a result, the implementation of generative artificial intelligence in various industries has increased drastically, where the marketing domain is one of the most affected. Moreover, the research regarding generative artificial intelligence is slower than its development, giving rise to new advantages and challenges that needs to be studied. Simultaneously, sustainability is becoming increasingly more important for business, as stakeholders such as customers, investors and governments expectations for sustainable practices are rising. The purpose of this study has hence been to develop sustainable recommendations regarding the utilization of generative artificial intelligence, to practitioners in marketing and communication. Consequently, the research question has been as follows: “How is generative artificial intelligence utilized in marketing sustainably?” Sustainability in this study has been defined by four interconnected dimensions, consisting of the economic-, environmental-, social & ethical- and technological dimension, where Gen AI have been classified as the technological dimension. Moreover, the research method in this qualitative, holistic multiple-case study, consisted of semistructured interviews with both marketers/communicators and practitioners in tech. A total of 13 respondents were interviewed, identified by convenience- and snowball sampling. The data were then analysed in a thematic analysis, resulting in the sub-themes “Value vs. Cost”, “Gen AI Utilization”, “Energy Usage”, and “Responsibility” under the themes “Economic”, “Technological”, “Environmental” and ”Social & Ethical” respectively. Furthermore, the main practical contribution of this study is the collection of recommendations regarding how Gen AI can be utilized sustainably in marketing, which can support marketers and communicators when utilizing Gen AI. The findings can also inspire policymakers regarding regulations of Gen AI and highlights the importance of Gen AI knowledge in the workforce to top managers. Moreover, the main theoretical contribution has been to increase the research in the interdisciplinary area of Gen AI utilization in Sustainable Marketing. This study has also proposed directions for future studies, such as focusing on sustainable Gen AI utilization in marketing across various industries, and to further explore how the geopolitical ownership influences the adoption and utilization of Gen AI tools.