Abstract

Graphical abstract

Keywords

۱٫ Introduction

۲٫ Conceptual underpinnings

۳٫ Methodology

۴٫ Descriptive details of extant publications

۵٫ Topic modeling

۶٫ Scientometric analysis

۷٫ Conclusion

Acknowledgement

References

Vitae

Abstract

The rapid advancement of artificial intelligence (AI) offers exciting opportunities for marketing practice and academic research. In this study, through the application of natural language processing, machine learning, and statistical algorithms, we examine extant literature in terms of its dominant topics, diversity, evolution over time, and dynamics to map the existing knowledge base. Ten salient research themes emerge: (1) understanding consumer sentiments, (2) industrial opportunities of AI, (3) analyzing customer satisfaction, (4) electronic word-of-mouth–based insights, (5) improving market performance, (6) using AI for brand management, (7) measuring and enhancing customer loyalty and trust, (8) AI and novel services, (9) using AI to improve customer relationships, and (10) AI and strategic marketing. The scientometric analyses reveal key concepts, keyword co-occurrences, authorship networks, top research themes, landmark publications, and the evolution of the research field over time. With the insights as a foundation, this article closes with a proposed agenda for further research.

۱٫ Introduction

What if artificial intelligence (AI) itself were used to investigate the current literature on AI in marketing? That is what we do in this study!

Having received more than US$5 billion in venture capital investments in just the past two years, artificial intelligence (AI) is poised to exert transformative effects on markets and marketing around the world (PricewaterhouseCoopers, 2017; Rangaswamy et al., 2020; Insights, 2018). Marketing increasingly relies on its algorithms, which mimic human cognitive functions and exhibit aspects of human intelligence (Huang & Rust, 2018; Rangaswamy et al., 2020; Russell & Norvig, 2016; Sterne, 2017), such that 72% of marketers cite AI as a business advantage. Consumers benefit from these applications, in the form of decreased costs, more diverse service channels, innovative breakthroughs, and opportunities for expanded human creativity and ingenuity when tedious, repetitive tasks are performed by AI (Haenlein & Kaplan, 2019; PricewaterhouseCoopers, 2017; Smart Insights, 2018). This revolution of AI usage in marketing, and its potential for producing superior value outcomes, has sparked substantial research attention (Davenport, Guha, Grewal, & Bressgott, 2020; Haenlein & Kaplan, 2019; Huang & Rust, 2018), prompting, for example, applications of intelligent technology (Marinova, de Ruyter, Huang, Meuter, & Challagalla, 2017); descriptions of services enabled, facilitated, and delivered by various technologies (Rust & Huang, 2012); investigations of AIpowered robotics (Lu et al., 2020; Wirtz et al., 2018); explorations of AI-led marketing and sales strategies (Davenport et al., 2020); considerations of how AI-enabled delivery can lead to cost-effective service excellence (Wirtz & Zeithaml, 2018; Wirtz, 2020); proposals of AIenabled platform business models (Wirtz, So, Mody, Liu, & Chun, 2019); investigations of the impact of AI chatbot disclosures on customer purchases (Luo, Tong, Fang, & Qu, 2019); considerations of effects on workforces (Davenport & Kirby, 2015) and redefinitions of AIenabled workplaces (Chui, Manyika, & Miremadi, 2015); and discussions of digital technologies as driving forces of work and life (McAfee & Brynjolfsson, 2016).