Artificial intelligence in marketing: exploring current and future trends

Abstract

Artificial Intelligence (AI) has revolutionized marketing domain, driving rapid digital transformation by enhancing processes, accelerating growth, and transforming the business landscape. Despite the growing attention towards artificial intelligence review studies, there remains a dearth of comprehensive reviews within the marketing domain. Thus, the current study aims to explore the use of artificial intelligence in marketing as an emerging research topic using a systematic literature review (SLR) method. A corpus of 522 studies between 2015 and July 2023 was gathered and finalised from the Web of Science (WoS) database. Furthermore, the current study expanded the SLR using a bibliometric analysis. Observably, a growing trend of artificial intelligence exists in the marketing domain. The bibliometric analysis findings depicted six emerging clusters of artificial intelligence in marketing research, namely psychosocial dynamic, artificial intelligence-enhanced market dynamic strategies, artificial intelligence for consumer services, artificial intelligence for decision-making, artificial intelligence for value transformation, and artificial intelligence for ethical marketing. The findings highlighted future research avenues in terms of context, methods, and theory. The study also discussed the outcomes for academics and practitioners and proposed a future research agenda to examine the ongoing shift driven by rapid artificial intelligence implementation in marketing.

Keywords:

• Artificial intelligence
• Industry 4.0
• marketing
• SLR
• bibliometric

REVIEWING EDITOR:

• Len Tiu Wright, De Montfort University Faculty of Business and Law, United Kingdom

SUBJECTS:

• Marketing Management
• Marketing
• Internet/Digital Marketing/e-Marketing

Acknowledgements

The author of this manuscript would like to express her appreciation and gratitude to the Arab Open University in Saudi Arabia for supporting this research.

Author contributions

Concept, writing, analysis, and revision are done by Ebtisam Labib.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data will be available on request.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Notes on contributors

Ebtisam Labib

Ebtisam Labib is a dedicated Assistant Professor and Director of the Academic Advising Unit, bringing over 15 years of experience to the realm of higher education. Her academic journey is anchored by a Ph.D. in Marketing with a specialized focus on Consumer Behavior from Universiti Sains Malaysia, complemented by an MBA from King Abdulaziz University. Her academic interest areas are Artificial Intelligence, Digital Marketing, consumer behavior, block chains, social media marketing, blended learning, open and distance learning.