ChatGPT, AI Advertising, and Advertising Research and Education

Abstract

Since ChatGPT was released on November 30, 2022, followed by Microsoft’s announcement of its artificial intelligence (AI)–powered new Bing search engine on February 7, 2023, and Google’s Bard release on March 21, 2023, it seems AI generally has taken over conversations across all sectors of society. In a very short time span, consumers and a wide range of organizations have adopted generative AI technologies with astonishing capabilities (Bove 2023). These new technological developments have accelerated the integration of AI into many tools, apps, and areas of our daily life, but the transformative AI technology is perhaps most deeply impacting the world of advertising. AI-enabled advertising spending worldwide in 2022 was estimated to be $370 billion, with predictions of $1.3 trillion in the next ten years (Statista 2023). While the viral sensation and enormous popularity of ChatGPT are generating unprecedented attention and interest in AI right now, AI, as both a theoretical concept and version of its technological implementations and applications, has a long history with its origin going back to the 1950s. In the advertising field, the first research article on the topic of AI in connection to advertising was published in 1988 (Cook and Schleede 1988). The authors described “decision support systems” (i.e., expert systems) as probably the “most widely implemented and well-known applications of AI” (48). As described, these systems used databases and models to solve problems, such as help with direct-mail systems and newspaper advertising placement. Since then, AI has changed the business of media and advertising and attracted attention from both advertising practitioners and scholars. Although there is no standard definition, Rodgers (2021) defined AI advertising as “brand communication that uses a range of machine functions that learn to carry out tasks with intent to persuade with input by humans, machines, or both” (2) and positioned AI advertising as a subdiscipline of advertising “situated at the intersection of cognitive science, computer science, and advertising” (2). Advertisers are using AI technologies in automated market segmentation and targeting, ad creative development and personalization, improving ad buying and placement, and optimizing advertising investment (Kietzmann, Paschen, and Treen 2018). Following the trend of increasing AI adoption in advertising, advertising scholars have organized sessions at the American Academy of Advertising (AAA) conference, such as the 2014 preconference, “Big Data for Advertising Research and Education,” and the joint AAA-ANA Educational Foundation luncheon panel with the provocative title, “The Future of Advertising—Will We Be Replaced by Robots?” in 2018. The Journal of Advertising (JA) has published multiple themed collections on AI-related topics, starting with a Special Section on Artificial Intelligence and Advertising, guest-edited by Hairong Li (2019). This collection of articles explored the potential and actual application of AI technologies to enhance advertising efficiency, effects, and effectiveness across the entire spectrum of the advertising campaign process, from situation analysis and consumer insight generation to advertising message creation, to media planning and buying, and to advertising effect assessment (see the Journal of Advertising, vol. 48, no. 4). Another Special Section on Advances in Computational Advertising in 2020, guest edited by Jisu Huh and Ed Malthouse (2020), addressed broad implications of evolving computer science technologies for data-driven, AI-powered computational advertising, and proposed a future research agenda in the areas of macro and exogenous factors, consumers’ roles in computational advertising, AI-powered ad content generation, computational advertising media planning strategy shifts from purchasing exposure to focusing on meaningful consumer engagement, and computational advertising measurement systems (see the Journal of Advertising, vol. 49, no. 4). A year later, JA published an up-to-date comprehensive Themed Issue on Promises and Perils of Artificial Intelligence and Advertising (2021, vol. 50, no. 1). In her editorial, the previous editor, Shelly Rodgers (2021) proposed an AI classification schema to systematically understand and develop subdomains