Twenty years ago, Artificial Intelligence (AI) sounded like science fiction, with robots replacing the functions of humans and taking over the world. Though AI seems to be a brand new and current technology, the concept of AI is rooted in the 1950s with Alan Turing and his infamous Turning Test (Ma and Sun, 2020). Fast forward to today, and the age of AI is here. AI is assisting society in a variety of different ways, from helping provide information in the form of digital assistants such as Alexa, Cortana, and Siri to providing fast-paced decisions that could save lives (Duggal, 2023). In the world of business, AI has started to augment decision-making, which may make a more pleasant customer experience, increase profitability and revenue, and even increase employee productivity (Ljepava, 2022). Marketing is one area of business that is slowly getting the AI treatment.
Marketing is defined by American Marketing Association “as the activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and society at large” (American Marketing Association, 2017). AI is a machine or computer system that simulates human intelligence, with three main types, weak, strong, and super. Weak AI performs routine, mundane pre-programmed tasks, and strong AI attempts to be human-like intelligence (Ljepava, 2022). Super AI, however still conceptual, is AI that will have intelligence that surpasses human intelligence (Duggal, 2023). Nevertheless, AI marketing appears to be a worthy area of research. More research needs to be conducted on this subject. Between 1987 and 2020, only 163 articles were published discussing the topic of the use of AI in marketing, with 95 of those articles being published between 2016 and 2020 (Vlačić et al., 2021). From the research that is out there, AI is influencing marketing by giving the customer a more personalized experience by understanding the customer and making predictions based on the consumer’s behavior (Ljepava, 2022). AI is able to take on marketing tasks such as digital searches, social media interactions, mobile device tracking, online purchases, and in-store purchases to provide targeted advertising and marketing (Ma and Sun, 2020). While this seems like a positive affirmation to use AI in marketing, which could potentially reduce the noise of pointless and unwarranted advertisements, there is a growing concern within the consumer community over privacy and dependency (Mariani et al., 2021).
Nonetheless, organizations are using AI, and there is strong evidence that AI is going to change business processes like marketing (Ma and Sun, 2020). Areas that AI has majorly begun to impact in marketing are in the stages of analysis, such as understanding the customer and marketplace, and tactics, like purchase predictions and campaign automation. It is noted that AI is used less frequently for strategic marketing decisions (Ljepava, 2022). The lack of using AI for strategic marketing decisions was a theme in the late 1990s when organizations used intelligent systems and artificial neural networks (ANNs), the precursors to modern AI, for routine and operational marketing functions but not strategic (Li, 2000).
To conclude, academic research involving AI and marketing has only started to pick up interest in the last ten years, with most of the research focused on machine learning (Ma and Sun, 2020). Areas of future research in the field of AI and marketing would be how AI could be used for strategic decision-making. Organizations having the ability to use AI to help with pricing decisions, predicting emerging markets, and forecasting (Ljepava, 2022) could be beneficial to both consumers and producers. Other areas of research could include public perception as it relates to privacy, which machine learning styles benefit marketing decisions the most, and how to better use AI for customer relations like chatbots (Ma and Sun, 2022).
. Mariana, M. M., Perez-Vega, R., & Wirtz J. (2022). AI in marketing, consumer research and psychology: A systematic literature review and research agenda. Psychology & Marketing, 39, 755-776. https://doi.org/10.1002/mar.21619Links to an external site.
. Vlačić, B., Corbo, L., Costa e Silva, S., & Dabić, M. (2021). The evolving role of artificial intelligence in marketing: A review and research agenda. Journal of Business Research, 128, 187-203 https://doi.org/10.1016/j.jbusres.2021.01.055Links to an external site.
. Ma, L., & Sun, B. (2020). Machine learning and AI in marketing – Connecting computing power to human insights. International Journal of Research in Marketing, 37, 481-504. https://doi.org/10.1016/j.iresmar.2020.04.005Links to an external site.
. Shuliang, L. (2000). The development of a hybrid intelligent system for developing marketing strategy. Decision Support Systems, 27, 395-409
. Ljepava, N. (2022). AI-enabled marketing solutions in marketing decision making: AI application in different stages of marketing process. Technology Education Management Informatics Journal, 11(3), 1308-1315. https://doi.org/10.18421/TEM113-40Links to an external site.
. Duggal, N. (2023, May 05). Advantages and disadvantages of Artificial Intelligence. Simplilearn Solutions. https://www.simplilearn.com/advantages-and-disadvantages-of-artificial-intelligence-articleLinks to an external site.
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