Artificial intelligence (AI) in strategic marketing decision-making: a research agenda. Issue 2 (13th April 2020)

• Record Type: Journal Article
• Authors: Stone, Merlin; Aravopoulou, Eleni; Ekinci, Yuksel; Evans, Geraint; Hobbs, Matt; Labib, Ashraf; Laughlin, Paul; Machtynger, Jon; Machtynger, Liz
• Is Part Of: Bottom line. Volume 33:Issue 2(2020)
• Page Start: 183
• Page End: 200
• Publication Date: 2020-04-13
• Subjects: Strategy -- Planning -- Marketing -- Artificial intelligence -- Decision-making -- Operations; Library finance -- Periodicals; Libraries -- Economic aspects -- Periodicals; 025.11
• DOI: 10.1108/BL-03-2020-0022
• Languages: English
• ISSNs: 0888-045X

Abstract

Abstract : Purpose: The purpose of this paper is to review literature about the applications of artificial intelligence (AI) in strategic situations and identify the research that is needed in the area of applying AI to strategic marketing decisions. Design/methodology/approach: The approach was to carry out a literature review and to consult with marketing experts who were invited to contribute to the paper. Findings: There is little research into applying AI to strategic marketing decision-making. This research 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: The application of AI to strategic marketing decision-making is known to be taking place, but as it is commercially sensitive, 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 make decisions about making different services available to different citizens and identify the risks of not providing services to certain citizens; so, this paper is relevant to the public sector. Originality/value: To the best of the authors' knowledge, this is one of the first papers to probe deployment of AI in strategic marketing decision-making.