AI for marketing: Enabler? Engager? Ersatz?

Sreedhar Madhavaram () and Radha Appan ()
Additional contact information
Sreedhar Madhavaram: Jerry S. Rawls College of Business, Texas Tech University
Radha Appan: Jerry S. Rawls College of Business, Texas Tech University

AMS Review, 2024, vol. 14, issue 3, No 7, 258-277

Abstract: Abstract The prospect of artificial intelligence (AI) matching and surpassing human intelligence continues to intrigue. On the foundations of the exceptional advances in AI technologies in the last decade, the potential for competitive advantages makes AI in general and Generative AI in particular one of the most promising technologies for marketing. However, while there are robust theoretical advances in the domain of AI for marketing, how AI impacts marketing entities is poorly understood. Further, how AI potentially makes marketing entities ineffective and inefficient is rarely addressed in research. Therefore, in this research, we begin with the articulation of a theory toolkit relevant to AI for marketing. Second, we discuss different types of AI and introduce a new perspective on approaching AI for marketing entities and purposes. Specifically, we conceptualize three new types of AI: enabling AI, engaging AI, and ersatzing AI (artificial, but inferior intelligence that make marketing entities less capable). Third, using our typology, we explicate the enormous potential of the three specific types of AI for marketing. Finally, toward actualizing the potential of AI for marketing, we conclude with a discussion of the contributions of our research and a research agenda.

Keywords: AI; Enabling AI; Engaging AI; Ersatzing AI; Ersatz intelligence; Collaborative AI; Critical thinking AI; Customer engagement; AI-enabled sciolism; Employee engagement (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13162-024-00293-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:amsrev:v:14:y:2024:i:3:d:10.1007_s13162-024-00293-7

Ordering information: This journal article can be ordered from
http://www.springer. ... gement/journal/13162

DOI: 10.1007/s13162-024-00293-7

Access Statistics for this article

AMS Review is currently edited by Manjit S. Yadav

More articles in AMS Review from Springer, Academy of Marketing Science
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().