Artificial empathy in marketing: conceptual mapping, antecedents and consequences

Purpose As digital interactions increasingly replace traditional face-to-face exchanges, the ability to embed empathy into technological systems has become a critical frontier. This study aims to examine the growing role of artificial empathy (AE) in human–AI interactions, focusing on its transformative impact within the marketing domain, where empathy-driven technologies are increasingly vital for fostering long-term consumer relationships. Design/methodology/approach This study uses a systematic literature review of AE research published over the past two decades. Relevant articles were identified through structured keyword searches in selected academic databases, applying predefined inclusion and exclusion criteria (e.g. peer-reviewed journal articles, relevance to marketing and consumer behavior and English language publications). The final sample (n = 85) was analyzed using bibliometric mapping and qualitative content analysis to trace the conceptual development of AE, identify its key antecedents and consequences and propose future research trajectories. Findings The analysis reveals five dominant research streams: emotion recognition technologies, AI-driven emotional engagement, AE in marketing analytics, sentiment analysis in social media and emotion detection in wearable and immersive environments. Antecedents of AE include technological infrastructure, consumer emotional dynamics, human-centered design and relational marketing practices. AE is linked to both positive outcomes, such as increased trust, personalization and customer experience, and critical challenges. Research limitations/implications While this review synthesizes key trends and gaps in the literature, future empirical studies are needed to validate proposed frameworks and assess the real-world implications of AE adoption across diverse marketing contexts. Originality/value This study develops a theoretical framework of the antecedents and consequences of AE in marketing while providing a comprehensive and integrative overview of the field. It further identifies four emerging research frontiers that offer a strategic foundation for advancing theory and designing emotionally intelligent marketing systems.

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Publication Details

Journal
International Journal of Innovation Science
Published
2026-04-13
DOI
https://doi.org/10.1108/ijis-08-2025-0411
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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article

Artificial empathy in marketing: conceptual mapping, antecedents and consequences

Ronny H. Walean, Benny Lule, Nikolas Fajar Wuryaningrat, Deske W. Mandagi
International Journal of Innovation Science
AI in Service Interactions
article

Artificial empathy in marketing: conceptual mapping, antecedents and consequences

Ronny H. Walean, Benny Lule, Nikolas Fajar Wuryaningrat, Deske W. Mandagi
article en

Abstract

Purpose As digital interactions increasingly replace traditional face-to-face exchanges, the ability to embed empathy into technological systems has become a critical frontier. This study aims to examine the growing role of artificial empathy (AE) in human–AI interactions, focusing on its transformative impact within the marketing domain, where empathy-driven technologies are increasingly vital for fostering long-term consumer relationships. Design/methodology/approach This study uses a systematic literature review of AE research published over the past two decades. Relevant articles were identified through structured keyword searches in selected academic databases, applying predefined inclusion and exclusion criteria (e.g. peer-reviewed journal articles, relevance to marketing and consumer behavior and English language publications). The final sample (n = 85) was analyzed using bibliometric mapping and qualitative content analysis to trace the conceptual development of AE, identify its key antecedents and consequences and propose future research trajectories. Findings The analysis reveals five dominant research streams: emotion recognition technologies, AI-driven emotional engagement, AE in marketing analytics, sentiment analysis in social media and emotion detection in wearable and immersive environments. Antecedents of AE include technological infrastructure, consumer emotional dynamics, human-centered design and relational marketing practices. AE is linked to both positive outcomes, such as increased trust, personalization and customer experience, and critical challenges. Research limitations/implications While this review synthesizes key trends and gaps in the literature, future empirical studies are needed to validate proposed frameworks and assess the real-world implications of AE adoption across diverse marketing contexts. Originality/value This study develops a theoretical framework of the antecedents and consequences of AE in marketing while providing a comprehensive and integrative overview of the field. It further identifies four emerging research frontiers that offer a strategic foundation for advancing theory and designing emotionally intelligent marketing systems.

International Journal of Innovation Science
Klabat University (ID), Manado State University (ID)
Reduced inequalities
Openalex Percentile: Top 5%
AI in Service Interactions
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