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Artificial Intelligence and Consumer Behaviour in Social Media: Systematic Literature Review and Future Research Agenda

Andrea Morales‐Muñoz et al.

International Journal of Consumer Studies2026https://doi.org/10.1111/ijcs.70173article
AJG 2ABDC A
Weight
0.37

Abstract

The rise of artificial intelligence (AI) and, more recently, generative AI (GAI) has transformed digital marketing, particularly within social media. However, academic research on this intersection remains dispersed, requiring a structured synthesis to identify prevailing trends and gaps. Given the increasing integration of AI in digital marketing, understanding its implications for consumer behaviour is crucial for both researchers and practitioners. This study conducts a systematic literature review (SLR) following the SPAR‐4‐SLR protocol to analyse existing research on AI, GAI, social media, and consumer behaviour. In addition, the 5W1H framework is used to organise information and answer questions that arise. Specifically, it examines how AI is portrayed in social media and consumer behaviour literature, whether as an enabler, risk, or neutral factor, the perspective taken by the studies, and the application given to it. Findings show that AI is primarily framed as a driver of personalisation, engagement, and analytics, yet notable concerns about ethical risks like algorithmic bias and privacy persist. Research perspectives vary, spanning consumer, business, and integrative views that reflect the complex AI influence on user experience and organisational strategy. Empirical studies mainly treat AI as a core subject, focusing on applications such as chatbots, recommendation systems, and virtual influencers (VIs). A smaller number employ AI methodologically for social media data analysis through machine learning (ML) and natural language processing (NLP). Despite growth, significant gaps remain in understanding AI's long‐term effects, cross‐cultural nuances, and theoretical integration. Ethical issues highlight the need for responsible AI frameworks balancing innovation and fairness. This review synthesises current knowledge and outlines future research directions, aiming to guide academic inquiry and responsible implementation of AI in digital consumer contexts.

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https://doi.org/https://doi.org/10.1111/ijcs.70173

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@article{andrea2026,
  title        = {{Artificial Intelligence and Consumer Behaviour in Social Media: Systematic Literature Review and Future Research Agenda}},
  author       = {Andrea Morales‐Muñoz et al.},
  journal      = {International Journal of Consumer Studies},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/ijcs.70173},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.