An overview of artificial intelligence and its application in marketing with focus on large language models

Reza Amini 1, * and Ali Amini 2

1 Raj Soin College of Business, Wright State University, Dayton, Ohio, USA.
2 Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran.
 
Review
International Journal of Science and Research Archive, 2024, 12(02), 455–465.
Article DOI: 10.30574/ijsra.2024.12.2.1223
Publication history: 
Received on 25 May 2024; revised on 05 July 2024; accepted on 08 July 2024
 
Abstract: 
Emerging technologies like the Internet of Things, big data analytics, blockchain, and artificial intelligence (AI) have significantly transformed business operations. Among these, AI stands out as the most recent and impactful, revolutionizing marketing practices. Professionals globally are actively seeking AI solutions tailored to their marketing needs. A systematic review of existing literature can highlight AI's significance in marketing and reveal future research pathways. Integrating big data sources and AI tools into marketing practices represents a departure from traditional methods, ushering in a new era of marketing education. This paper explores recent advancements in AI within the marketing sector, highlighting how these developments enable practitioners to effectively navigate and utilize extensive and complex datasets for predictive analytics. By integrating big data and AI, marketing strategies can now be directly aligned with execution, enhancing both strategic planning and the forecasting of marketing outcomes. However, the adoption of these technologies necessitates a shift towards adaptive learning approaches, moving beyond traditional assessment methods to better accommodate the dynamic nature of today's marketing environment. The transition to big data and AI-driven approaches equips experts for the evolving demands of the modern marketing landscape. This shift transcends traditional analytics by leveraging cutting-edge AI technologies, such as Large Language Models, and enhances the utilization of big data through innovative learning experiences, such as role-playing simulations. This integration not only broadens the analytical capabilities of marketers but also fosters a more immersive and experiential understanding of data-driven decision-making.
 
Keywords: 
Artificial Intelligence; Big Data Analysis; Large Language Models; Marketing; Generative AI; Prompt Engineering
 
Full text article in PDF: 
 
Copyright information: 

Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0