Implementing Artificial Intelligence in Traditional B2B Marketing Practices: An Activity Theory Perspective
Brendan James Keegan1, Denis Dennehy2, Peter Naudé3
1School of Business, Maynooth University, Maynooth, Ireland.
Information Systems Frontiers : a Journal of Research and Innovation
|May 31, 2022
Summary
Artificial intelligence (AI) transforms business-to-business (B2B) marketing by introducing new contradictions. This study reveals these challenges and their intended/unintended consequences for marketing practices.
Area of Science:
- Business and Marketing
- Information Systems
- Sociology of Technology
Background:
- Growing anecdotal evidence supports AI's effectiveness in digital and B2B marketing.
- Empirical research on AI-powered B2B marketing, especially socio-technical aspects, remains limited.
Purpose of the Study:
- Examine AI-powered B2B marketing through the lens of Activity Theory (AT).
- Illuminate contradictions arising from AI adoption in traditional B2B marketing.
- Understand AI's role as a catalyst for transformational change in marketing.
Main Methods:
- Utilized Activity Theory (AT) as a theoretical framework.
- Conducted eighteen in-depth interviews with industry and academic experts.
- Analyzed the socio-technical system of AI-powered B2B marketing.
Main Results:
- Identified key contradictions in the adoption and implementation of AI in B2B marketing.
- Highlighted cultural and political challenges associated with confronting these contradictions.
- Observed both intended and unintended consequences following the resolution of contradictions.
Conclusions:
- Contradictions, viewed through AT, drive transformational change in AI-driven B2B marketing.
- Marketing practitioners and researchers must navigate complex socio-technical challenges.
- Resolved contradictions yield multifaceted outcomes, necessitating strategic management.
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