Abstract
This chapter examines the drivers for the adoption of artificial intelligence (AI) in digital marketing and the challenges that organizations face while implementing AI-based marketing strategies. The chapter begins with an overview of the potential applications connected with using AI in digital marketing, including automation. It then explores the key drivers for the adoption of AI in digital marketing. This chapter also provides a framework for greater adoption of AI in digital marketing. The framework has many well-known components relative to other known AI frameworks but is focused upon digital marketing. The chapter discusses the challenges that organizations face when implementing AI-based marketing strategies. The chapter also explores the potential risks associated with using AI in digital marketing, including algorithmic bias and the risk of over-reliance on AI. Overall, this chapter provides insights into the drivers and challenges of using AI in digital marketing and offers recommendations for organizations looking to implement AI-based marketing strategies.
TopBackground
As most business processes, digital marketing tends to benefit in various ways from the use of information systems in general. With the growing development and adoption in AI since some years, marketing professionals have quickly found out that they can be supported in different ways by AI systems (Malviya et al., 2022). However, in order to understand this wide topic, it would be worthwhile for the readers to understand some of the main drivers which lead to the current state of use of AI for digital marketing. The following list down some of the main factors:
Key Terms in this Chapter
Digital Footprint: Traces of all transactions left after use of any digital technology.
Personalization: The action of providing tailor made products and services based on individual customer tastes and needs.
Precision Farming: The use of techniques in agriculture which minimizes the use of intrants as no wide-scale method is applied.
Cloud Computing: The application of pay as you use services over computer networks.
Big Data: The capacity to use technologies which can work with huge volume of different types of data and in real time basis.
Predictive Analysis: The use of analytical techniques in order to be able to guess with a high level of confidence a future occurrence.
Internet of Things (IoT): The interconnection and interdependence of different devices via the internet.