Semantic Scholar Open Access 2021 289 sitasi

Artificial intelligence in marketing: A systematic literature review

Srikrishna Chintalapati S. Pandey

Abstrak

The digital transformation fostered by the increasing leverage of artificial intelligence (AI) has been a critical influencing factor unleashing the next wave of enterprise business disruption. Marketing is one of the business streams witnessing this transformation on a very intense scale. Contemporary marketing has begun to experiment with modern, cutting-edge technologies, such as AI, deploying them in mainstream operations to ensure accelerated success. This article explores the use of AI in marketing as an emergent stream of research. Based on inferences from earlier studies, the study categorizes marketing into five distinct functional themes—integrated digital marketing, content marketing, experiential marketing, marketing operations, and market research—and 19 sub-functional themes (activity levers). Across the chosen themes and sub-themes, the study further dovetails into and identifies 170 featured use cases of the extant literature, where AI is leveraged by marketing in delivering superior quality outcomes and experiences. By way of a systematic literature review (SLR), the article evaluates 57 qualifying publications in the context of AI-powered marketing and qualitatively and quantitatively ranks them based on their coverage, impact, relevance, and contributed guidance, and elucidates the findings across various sectors, research contexts, and scenarios. The study discusses the practitioner and academic research implications and proposes a future research agenda to study the continuous transformation fostered by accelerated adoption of AI across the marketing landscape.

Topik & Kata Kunci

Penulis (2)

S

Srikrishna Chintalapati

S

S. Pandey

Format Sitasi

Chintalapati, S., Pandey, S. (2021). Artificial intelligence in marketing: A systematic literature review. https://doi.org/10.1177/14707853211018428

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Informasi Jurnal
Tahun Terbit
2021
Bahasa
en
Total Sitasi
289×
Sumber Database
Semantic Scholar
DOI
10.1177/14707853211018428
Akses
Open Access ✓