Exploring the Applications of Artificial Intelligence in Marketing: A Topic Modelling Analysis

Authors

DOI:

https://doi.org/10.18089/tms.20250103

Keywords:

Artificial Intelligence (AI), Marketing, Literature Analysis, Text Mining, Topic Modelling

Abstract

Integrating Artificial Intelligence (AI) into marketing has revolutionised this field, offering new avenues of innovation and efficacy. This study aims to unveil the prevailing trends and patterns within the current academic literature about AI applications in Marketing and propose future research directions. The study conducted a comprehensive review by analysing 2,255 articles from the Scopus database from 1980 to 2022, employing a Text Mining approach and Latent Dirichlet Allocation (LDA) topic modelling. The findings suggest trends in research topics of Learning Models, Expert Systems, Natural Language Processing, Social Media, and Consumer Centricity. Outlier topics related to Health, Market Forecast, and Technology Impact on Youth have caught the researchers’ attention. The associated challenges and risks, ethical considerations, and practical implications were presented for each topic. This study develops literature on AI-driven marketing by unearthing the trend topics and suggesting a research agenda. At the same time, it offers actionable insights for businesses to enhance consumer engagement and ethical AI adoption in marketing practices.

Author Biographies

  • Paulo Rita, NOVA Information Management School (NOVA IMS), Lisbon, Portugal

    Paulo Rita is Foundation Chair / Full Professor of Marketing and Director of the Master´s Program in Data-driven Marketing at NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, Portugal. He was a Post-Doc in Digital Marketing (University of Nevada Las Vegas, USA), holds a PhD in Marketing (Cardiff University, UK) and has a Postgraduate diploma in Quantitative Methods in Management (University of Glasgow, UK). His research interests include digital/social media marketing, artificial intelligence in marketing, consumer behavior/neuromarketing, and tourism marketing. Professor Rita has more than 13,900 citations in Google Scholar, and he is among the world´s top 2% scientists.

  • Wajdy Omran, University of Minho, Faculty of Economics and Management, Portugal

    Wajdy Omran is currently a doctoral candidate pursuing a Ph.D. in Management, specializing in Marketing and Strategy, at the University of Minho. He is affiliated with the Centre for Research in Economics and Management (NIPE). Wajdy holds a Master’s degree in Marketing Management from the Polytechnic Institute of Coimbra (ESTGOH). His research focuses on tourism marketing, tourist engagement, and the application of immersive technologies in these fields.

  • Ricardo F. Ramos , Instituto Politécnico de Coimbra, ESTGOH, Portugal

    Ricardo F. Ramos holds a Ph.D. in Management with a specialization in Marketing. He is an Assistant Professor at Polytechnic Institute of Coimbra (ESTGOH-IPC). His research pursuits span a diverse spectrum in the marketing field, encompassing areas such as Consumer Behavior applied in the Tourism and Hospitality, and Sport Marketing. Ricardo enjoys taking advantage of online reviews and working with text mining techniques. His work has been published in esteemed journals such as the International Journal of Hospitality Management, International Journal of Consumer Studies, Journal of Air Transport Management, and Journal of Hospitality and Tourism Technology.

  • Tânia Costa, NOVA Information Management School (NOVA IMS), Lisbon, Portugal

    Tânia Costa holds a master´s degree in Data-driven Marketing with a major in Marketing Intelligence, and a postgraduation in Digital Marketing and Analytics from NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, Portugal. She is a Data Engineer at NTT DATA Europe & Latam.

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02.01.2025

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Business/Management: Research Papers

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Rita, P., Omran, W. ., Ramos , R. F. ., & Costa, T. . (2025). Exploring the Applications of Artificial Intelligence in Marketing: A Topic Modelling Analysis. Tourism & Management Studies, 21(1), 39-55. https://doi.org/10.18089/tms.20250103

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