Implementing Artificial Intelligence in Traditional B2B Marketing Practices: An Activity Theory Perspective
Brendan James Keegan (),
Denis Dennehy and
Peter Naudé
Additional contact information
Brendan James Keegan: Maynooth University
Denis Dennehy: Swansea University
Peter Naudé: Manchester Metropolitan University
Information Systems Frontiers, 2024, vol. 26, issue 3, No 10, 1025-1039
Abstract:
Abstract Anecdotal evidence suggests that artificial intelligence (AI) technologies are highly effective in digital marketing and rapidly growing in popularity in the context of business-to-business (B2B) marketing. Yet empirical research on AI-powered B2B marketing, and particularly on the socio-technical aspects of its use, is sparse. This study uses Activity Theory (AT) as a theoretical lens to examine AI-powered B2B marketing as a collective activity system, and to illuminate the contradictions that emerge when adopting and implementing AI into traditional B2B marketing practices. AT is appropriate in the context of this study, as it shows how contradictions act as a motor for change and lead to transformational changes, rather than viewing tensions as a threat to prematurely abandon the adoption and implementation of AI in B2B marketing. Based on eighteen interviews with industry and academic experts, the study identifies contradictions with which marketing researchers and practitioners must contend. We show that these contradictions can be culturally or politically challenging to confront, and even when resolved, can have both intended and unintended consequences.
Keywords: Artificial Intelligence; Activity Theory; B2B Marketing (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s10796-022-10294-1 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:infosf:v:26:y:2024:i:3:d:10.1007_s10796-022-10294-1
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10796
DOI: 10.1007/s10796-022-10294-1
Access Statistics for this article
Information Systems Frontiers is currently edited by Ram Ramesh and Raghav Rao
More articles in Information Systems Frontiers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().