This chapter explores the profound influence of artificial intelligence (AI) on advertising, covering its historical context, current trends, and future implications. Initially, advertising relied on manual data analysis, but AI has shifted the landscape towards more targeted campaigns. AI's role began with predictive analytics for weather forecasting in the 1950s and evolved to include collaborative filtering by companies like Amazon. Current trends include hyper-personalization through predictive analytics, programmatic ad buying, and conversational AI. These AI-driven strategies enhance user experience and improve ad targeting. The future promises even greater personalization, with advancements in voice and visual search. However, ethical considerations regarding privacy and data security have also emerged. This analysis underscores the transformative impact of AI on advertising, from its inception to its current state, highlighting the continuous evolution and future prospects.
Top2. Historical Context
To encapsulate the transformative trajectory of artificial intelligence (AI) within the advertising realm, it is imperative to commence with a pre-AI baseline of the advertising industry. The metamorphosis of AI from a concept of science fiction to an indispensable tool across multiple sectors illustrates a profound evolution. Historically, the advertising domain was markedly manual, with marketers depending on demographic segmentation and rudimentary data analysis for customer targeting (Kietzmann et al., 2018). This era was characterized by a reliance on generalized advertising methods, which, while broad in reach, often resulted in suboptimal conversion rates and return on investment due to their lack of personalization (Elhager, 2023).
The advent of AI heralded a new epoch in advertising, marked by a gradual yet undeniable shift towards data-driven, automated processes. Goldberg L. (2018) provides an insightful examination into the chronological adoption and impact of AI in advertising. A notable early instance of AI's potential impact on consumer behavior can be traced back to the weather prediction software developed in 1950 by Jule Gregory Charney, an American meteorologist. This pioneering application of predictive analytics not only revolutionized weather reporting but also enabled advertisers to tailor product promotions in alignment with weather conditions, thereby enhancing the efficiency and relevance of their campaigns (Huang & Rust 2021).
Further developments in AI technology facilitated the emergence of more sophisticated targeting strategies. For instance, the concept of predictive behavior modeling, introduced by Swedish computational linguist Jussi Karlgren, laid the groundwork for contemporary recommendation systems utilized by leading digital platforms like Amazon, Facebook, Netflix, and Spotify. These systems leverage collaborative filtering and other AI-driven methodologies to offer personalized suggestions, thereby significantly enhancing user engagement and satisfaction.