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The use of Artificial Intelligence (AI) in digital marketing is presenting a unique opportunity to achieve personalization and efficiency in the business strategy more than ever before, but organizational and human obstacles are frequently preventing its implementation. This paper will examine the last 15 years to explore the role of training in the use of AI technologies in digital marketing and advertising. Based on the qualitative approach, this paper summarizes the evidence provided by peer-reviewed articles (such as empirical and systematic reviews) and primary data (e.g., expert interviews) in North India and determines the main themes. The results emphasize that digital marketing people do not possess AI skills and confidence often, so the formal training is a vital facilitator of adoption and continued performance. Research consistently demonstrates that special training and educational workshops raise the perception of ease of use and utility of AI tools, which will measure faster acceptance. On the other hand, those organizations which do not focus on training experience resistance and skill gaps (a skills paradox) to slow down AI adoption. The present study recaps the existing theoretical frameworks (e.g., TAM and TOE) within the framework of AI marketing, pointing to the lack of training as one of the relevant perceived barriers. Practical recommendations are provided on the basis of thematic analysis to both managers (e.g., invest in customised AI training, enable an AI-literate culture) and research in the future (e.g., quantitatively measure training impacts). This paper highlights that training and learning can be regarded as the key drivers in closing the gap between AI potential and the actual application in the sphere of digital advertising, which will eventually lead to sustainable business performance. The significance of the research under consideration is the fact that it offers an evidence of the importance of training as a mediating variable between the Technology Acceptance Model and the Technology-Organization-Environment model as the means of explaining the adoption of AI in the digital marketing in the circumstances of an emerging economy.
Saini et al. (Sat,) studied this question.