Exploring The Barriers of Artificial Intelligence Adoption in Digital Marketing Landscape
Main Article Content
Abstract
The growing capacity of artificial intelligence (AI) has been compared to how electricity transformed our world and industries a hundred years ago. AI is changing the rules, roles and tools of marketing, as marketing is one of the most prosperous areas to implement AI in. The purpose of this paper is uncover the reasons behind the adoption of AL within the field of digital advertising. It seeks to understand the motives that drive the AL adoption and identify the potential benefits and challenges that this process may entail. The authors strive to identify the key incentives for AL adoption and observe the benefits and challenges arising from this process with the help of qualitative analysis. An analysis of interviews with 20 experts from different industries related to Marketing and AI shows that AI have impact in Marketing processes and the impact will be bigger in the future. The research questions are how to use AL in digital marketing, secondly what are the future predictions in the field of digital marketing and AI and finally what are the potential AI enabled solutions in digital marketing. The conclusions of this study indicated that companies which leverage technology in their business strategies can gain an advantage over their competitors who remain to work in traditional ways. AI can predict, analyze and personalize one to one marketing messages to consumers at scale and with precision that humans are incapable of. Companies should not fear technology but embrace it throughout the core functions of the business bearing in mind the issues around ethics and data privacy. The best time to begin gathering business data is today.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Alvesson, M., & Deetz, S. (2000). Kritisk samhällsvetenskaplig metod. Lund: Studentlitteratur.
AIMA (2019, 30 January). Artificial Intelligence: A Modern Approach. AIMA. http://aima.cs.berkeley.edu/. [Retrieved 2019-04-22]
Bughin, J., Seong, J., Manyika, J., Chui, M. and Joshi, R. (2018). Notes from the AI frontier: Modeling the impact of AI on the world economy. McKinsey. https://www.mckinsey.com/featured-insights/artificial-intelligence/notes-from-the-aifrontier-modeling-the-impact-of-ai-on-the-world-economy. [Retrieved 2019-06-11]
Bus, H., Ti, L. & Rt, S. (n.d.) Driving Digital Transformation: New Skills for Leaders, New Role for the CIO. Harvard Business Review.
Alpaydin, E. (2014). Introduction to Machine Learning. MIT Press, 2014. ProQuest Ebook Central.http://ebookcentral.proquest.com/lib/umeaubebooks/detail.action?docID=3339851.
Ayoub, K., & Payne, K. (2016). Strategy in the Age of Artificial Intelligence. Journal of Strategic Studies. 793–819.
Attaran, M., & Deb, P. (2018). Machine Learning: The New “Big Thing” for Competitive Advantage. International Journal of Knowledge Engineering and Data Mining. 5(1), p. 1. :BBC (2017, 25 May). Google AI defeats human Go champion. BBC. https://www.bbc.com/news/technology-40042581. [Retrieved 2019-04-24]
Beck, M., & Libert, B. (2017, 15 February). The Rise of AI Makes Emotional Intelligence More Important. MIT Sloan Management Review. https://hbr.org/2017/02/the-rise-of-ai-makes-emotional-intelligence-moreimportant.[Retrieved 2019-04-24]
Bishop, P. (2000). Synchronicity and intellectual intuition. In: Kant, Swedenborg, and Jung: The Edwin Mellen Press.
Bolton, R.N., Gustafsson, A., McColl-Kennedy, J.R., Sirianni, N.J., & Tse, D.K. (2014). Small details that make big differences: A radical approach to consumption experience as a firm’s differentiating strategy. Journal of Service Management. 253-274.
Brightedge (2018). 2018 Future of Marketing and AI Survey. Brightedge. https://videos.brightedge.com/research-report/brightedge-2018-future-of-marketingand-ai-survey.pdf. [Retrieved 2019-04-24]
Bogner, A., Littig, B., & Menz, W. (2018). Generating Qualitative Data with Experts and Elites.
Flick, U. 2018. The SAGE handbook of qualitative data collection. 1st ed. Los Angeles: SAGE, 652-668.
PRNewswire, Despite the Buzz, Consumers Lack Awareness of the Broad Capabilities of AI(2018). https://www.prnewswire.com/news-releases/despite-the-buzz-consumers-lackawareness-of-the-broad-capabilities-of-ai-300458237.html. Accessed 12 Apr 2019
Makridakis, S.: The forthcoming Artificial Intelligence (AI) revolution: its impact on society and firms. Futures 90, 46–60 (2017). https://doi.org/10.1016/j.futures.2017.03.006 :Kietzmann, J., Paschen, J., Treen, E.: Artificial intelligence in advertising: how marketers can leverage artificial intelligence along the consumer journey. J. Advertising Res. 58(3),263–267 (2018). https://doi.org/10.2501/JAR-2018-035
Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach. Pearson Education Limited, London (2016). https://doi.org/10.1016/j.artint.2011.01.005
Siau, K.L., Yang, Y.: Impact of artificial intelligence, robotics, and machine learning on sales and marketing. In: Twelve Annual Midwest Association for Information Systems Conference, pp. 18–19 (2017)
Eden, A., Steinhart, E., Pearce, D., Moor, J.: Singularity Hypotheses: An Overview.Springer, Heidelberg (2012). http://dx.doi.org/10.1007/978-3-642-32560-1_1
Rosenberg, D.: How marketers can start integrating AI in their work. Harvard Bus. Rev.(2018)
Chui, M., Manyika, J., Miremadi, M., Henke, N., Chung, R., Nel, P., Malhotra, S.: Notes from the AI Frontier: Insights from Hundred Uses of Cases. McKinsey & Company (2018)
Ramaswamy, S.: How companies are already using AI. Harvard Bus. Rev. 14, 2017 (2017) Ransbotham, S., Gerbert, P., Reeves, M., Kiron, D., Spira, M.: Artificial intelligence in business gets real. MIT Sloan Manag. Rev. 60280 (2018)
Domingos, P.: The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. Penguin Books LDA, London (2015)
Beaudin, L., Downey, S., Hartsoe, A., Renaud, C., Voorhees, J.: Breaking the marketing mold with machine learning. MIT Technol. Rev. Insights (2018)
Gallo, A.: The value of keeping the right customers. Harvard Bus. Rev. 29 (2014)
Severino, A.J.: Metodologia do trabalho científico. Cortez Editora (2007)
Rumelt, R.: Good Strategy, Bad Strategy. Profile Books, London (2011)
Ertuğrul, İ., & Deniz, G. (2018). 4.0 Dünyası: Pazarlama 4.0 ve endüstri 4.0. Bitlis Eren Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 7(1), 143-170.
Khanna, A., Akshay, A. G., & Bhalla, A. (2017). Designing natural language processing systems with quickscript as a platform. Paper presented at the ICACIE 2016.
Kose, U., & Sert, S. (2017). Improving content marketing processes with the approaches by artificial intelligence. ECOFORUM, 6(1), 1-8.
Kotler, P., Kartajaya, H., & Setiawan, I. (2010). Marketing 3.0: From products to customers to the human spirit. John Wiley & Sons.
Kotler, P., Ang, S. H., Leong, S. M., & Tan, C. T. (2003). Marketing management: An Asian perspective (3th ed.). Singapore: Prentice-Hall.
Kumar, V., Rajan, B., Venkatesan, R., & Lecinski, J. (2019). Understanding the roleof artificial intelligence in personalized engagement marketing. California Management Review, 61(4), 135-155.
Kurt, R. (2019). Industry 4.0 in terms of industrial relations and its impacts on labour life. Procedia Computer Science, 158, 590-601.
Liao,T.(2015).Augmented or admented reality?The influence ofmarketing on augmented reality technologies. Information, Communication & Society, 18(3), 310-326.
Luce, L. (2018). Artificial intelligence for fashion. New York: Apress - Springer Nature
Marinchak, C. L. M., Forrest, E., & Hoanca, B. (2018). The impact of artificial intelligence and virtual personal assistants on marketing. In Encyclopedia of Information Science and Technology, Fourth Edition (pp. 5748-5756). IGI global.
McCorduck, P., & Cfe, C. (2004). Machines who think: A personal inquiry into the history and prospects of artificial intelligence. CRC Press.
McGregor, K. A., & Whicker, M. E. (2018). Natural language processing approaches to understand HPV vaccination sentiment. Journal of Adolescent Health, 62(2),S27-S28. Miikkulainen, R., Iscoe, N., Shagrin, A., Rapp, R., Nazari, S., McGrath, P.,& Epstein,
J. (2018, April). Sentient ascend: AI-based massively multivariate conversion rate optimization. Proceedings of The Thirtieth AAAI Conference on Innovative Applications of Artificial Intelligence, (7696-7703).
Milgrom, P. R., & Tadelis, S. (2018). How artificial intelligence and machine learning can impact market design. NBER WORKING PAPER SERIES: National Bureau of Economic Research, Cambridge: MA.