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

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NOVA Information Management School (NOVA IMS), Lisbon, Portugal, Rita, Paulo, Omran, Wajdy, University of Minho, Faculty of Economics and Management, Portugal, Ramos, Ricardo F., Instituto Politécnico de Coimbra, ESTGOH, Portugal, Costa, Tânia, NOVA Information Management School (NOVA IMS), Lisbon, Portugal·2025·Tourism & Management Studies
DOI 10.18089/tms.20250103
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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.

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  • Recent literature reports an accelerated growth of research on AI in marketing since 2021, driven by generative language models and low-cost predictive analytics.

    “La literatura reciente coincide en señalar una expansión acelerada de la investigación sobre IA aplicada al marketing a partir de 2021, impulsada por la disponibilidad de modelos de lenguaje generativo y de analítica predictiva de bajo costo (Rita et al., 2025).”

    From El Reto del Marketing Social ante la Inteligencia Artificial: un análisis comparado en distintos contextos geográficos y sistemas políticos (2026) · cites this paper as Rita et al., 2025

    Section 2.1 (page unavailable) reports a sharp rise in AI-and-marketing publications: 1,493 articles appeared in 2019–2022, compared with 2,255 since 1980. It does not locate the start of that growth specifically in 2021. Section 3.1 discusses generative models and predictive applications, but does not say that their availability, or low-cost predictive analytics, drove the growth in research. (LLM, conf=0.87)

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Cited by

Sorted by citations

Authors
NOVA Information Management School (NOVA IMS), L., Rita, P., Omran, W., University of Minho, F. O. E. A. M., Ramos, R. F., Instituto Politécnico de Coimbra, E., Costa, T., & NOVA Information Management School (NOVA IMS), L.
Affiliations
  • Universidade Nova de Lisboa (PT)
  • University of Minho (PT)
  • Universidade Politécnica de Coimbra (PT)
ORCID
Venue
Tourism & Management Studies
Publisher
School of Management, Hospitality and Tourism, University of the Algarve
Published
2025-01-01
Volume
21
Issue
1
Pages
39-55
ISSN
  • 2182-8458 (ISSN-L)
  • 2182-8466
DOI
10.18089/tms.20250103
OpenAlex
W4406013305
Cited by
7
References
8
Citations by year
2026: 7
FWCI
2.81
Type
journal article
Language
en
Open access
Licence
cc-by-nd
Locations
  • Tourism & Management Studies (publishedVersion, cc-by-nd)
  • Dialnet (Universidad de la Rioja) (submittedVersion)
  • Repositório do ISCTE-IUL (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by-nc-nd)
Funders
Fundação para a Ciência e a Tecnologia (UIDB/04152, 10.54499, UIDB/04152/2020)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
  • Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
artificial intelligence in marketing, AI-driven marketing, research trends, learning models, expert systems, natural language processing, social media marketing, health marketing, market forecast, ethical AI, customer engagement

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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