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Stone, Merlin, Aravopoulou, Eleni, Ekinci, Yuksel, Evans, Geraint, Hobbs, Matt, Labib, Ashraf, Laughlin, Paul, Machtynger, Jon and Machtynger, Liz (2020) Artificial Intelligence (AI) in Strategic Marketing Decision-Making: A research agenda. The Bottom Line, 33 (2). ISSN 0888-045X

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Abstract

Abstract

Purpose The purpose of this article is to review literature and thinking about the application of AI in strategic situations and to identify the research that is needed in the area of applying AI to strategic marketing decisions. Design/methodology/approach Review of literature and consultation with marketing experts who were invited to contribute to the article. Findings There is little research into applying AI to strategic marketing decision-making. This is needed as the frontier of AI application to decision-making is moving in many management areas from operational to strategic. Given the competitive nature of such decisions and the insights from applying AI to defence and similar areas, it is time to focus on applying AI to strategic marketing decisions. Research limitations/implications Applying AI to strategic marketing decision-making is known to be taking place, but the it is commercially sensitive, so data is not available to the authors. Practical implications There are strong implications for all businesses, particularly large businesses in competitive industries, where failure to deploy AI in the face of competition from firms who have deployed AI to improve their decision-making could be dangerous. Social implications The public sector is a very important marketing decision-maker. Although in most cases it does not operate competitively, it must still make decisions about making different services available to different citizens and identify the risks of not providing services to certain citizens, so this article is relevant to the public sector. Originality/value This is one of the first articles to probe deployment of AI in strategic marketing decision-making. Keywords Artificial intelligence, marketing, decision-making, strategy, planning, operations.

Item Type: Article
Depositing User: Leah Maughan
URI: https://sure.sunderland.ac.uk/id/eprint/13902

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Item ID
13902
ISSN
0888-045X

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Date Deposited
17 Sep 2021 11:18
Last Modified
03 Jun 2025 14:55

Contributors

Author
Merlin Stone
Author
Eleni Aravopoulou
Author
Yuksel Ekinci
Author
Geraint Evans
Author
Matt Hobbs
Author
Ashraf Labib
Author
Paul Laughlin
Author
Jon Machtynger
Author
Liz Machtynger

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