Abstract
Artificial intelligence is a transformational general purpose technology that is impacting marketing as a function and marketing managers' activities, capabilities, and performance. The job of a marketing manager will be evolving into understanding which kind of artificial intelligence can and should be applied to which kind of marketing actions for better performance. Marketing managers will have to go through a learning curve and acquire new skills. The aim of this chapter is to present the tertiary literature on AI and to discuss the future of AI's impact in the field of marketing. The literature on AI for marketing is growing steadily. This article starts by describing some key concepts of the AI literature. It then illustrates a few important consequences of AI on businesses in general. Finally, it unfolds some of the important ways on how AI is already impacting, and will continue to impact, marketing managers' activities, capabilities, and performance. The article ends by discussing the future implication for marketing managers.
TopBackground
According to the latest study of International Data Corporation (IDC) (accessed on 01/09/2021, source: https://www.idc.com/getdoc.jsp?containerId=US48125621):
The AI software market grew rapidly during 2020, and with accelerated digital disruption, we expect this market to continue to grow over the forecast period [i.e. 2021–2025]. IDC forecasts the overall AI software market will approach $596 billion in revenue in 2025 at a Compound Annual Growth Rate (CAGR) of 17.7%, with the AI-centric part to approach $123.3 billions at a CAGR of 27.8% over the forecast period,” says Ritu Jyoti, group vice president of Artificial Intelligence and Automation Research with IDC's software market research and advisory practice. “Today, AI expertise is focused more on developing commercial applications that optimize efficiencies in existing industries. Acceleration of AI adoption and proliferation of smart, intuitive Machine Learning (ML)/Data Learning (DL) algorithms will spawn the creation of new industries and business segments and overall will trigger new opportunities for business monetization.
Key Terms in this Chapter
Robotics: Robotics can be defined as an interdisciplinary branch of computer science and engineering that involves designing and constructing machines to assist humans.
Automation: Automation can be defined as the technique of making an apparatus, a process, or a system operate automatically.
Big Data: Big data can be defined as larger, more complex data sets arising from new data sources, and the techniques to analyze and extract meaning from it.
Artificial Intelligence: Artificial intelligence can be defined as the ability of a system to autonomously learn and interpret from external data and use that knowledge to do specific tasks and achieve goals through rational and flexible adaptation.
Deep Learning: Deep learning can be defined as a type of machine learning technique that teaches technological software to imitate the way humans learn.
Augmented Reality: Augmented reality can be defined as an interactive experience of the real-world environment that is enhanced using a technological device and multiple sensory modalities.
Machine Learning: Machine learning can be defined as making technological software think and act without human intervention.