Empowering Sustainability in Marketing Through Artificial Intelligence

<p>In recent years, the business landscape has been significantly transformed by the emergence of advanced technologies, many of which have contributed to the sustainability of various business sectors. Among these technologies, Artificial Intelligence (AI) has been recognized as a fundamental force reshaping how organizations operate across multiple domains, including marketing. Notable changes in marketing practices have been observed with the adoption of AI technologies. The article explores the intersection of sustainability, AI, and marketing by examining how AI contributes to the sustainability of marketing practices. To achieve this objective, a systematic literature review (SLR) was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The review process was carried out in four stages. First, relevant studies were identified using major academic databases, including Scopus, Web of Science, ScienceDirect, and JSTOR. Second, the retrieved literature was screened to determine its relevance. Third, selection criteria (e.g., document type, language, and publication year) were applied to refine the dataset. Finally, the selected articles were analyzed in depth. The findings reveal that AI plays a dual role. Its contribution is not inherent but largely depends on how it is implemented within organizations. In other words, the impact of AI on marketing sustainability is directly linked to the organization’s sustainability orientation.</p>

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Publication Details

Journal
Change Management An International Journal
Published
2026-05-18
DOI
https://doi.org/10.18848/2327-798x/cgp/a126
Primary Topic
AI in Service Interactions
Type
article
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article

Empowering Sustainability in Marketing Through Artificial Intelligence

Fatima Zahra El Arbaoui, Taoufiq Yahyaoui, Firdaws Hayoun, Samira Rhizlane
Change Management An International Journal
AI in Service Interactions
article

Empowering Sustainability in Marketing Through Artificial Intelligence

Fatima Zahra El Arbaoui, Taoufiq Yahyaoui, Firdaws Hayoun, Samira Rhizlane
article en

Abstract

<p>In recent years, the business landscape has been significantly transformed by the emergence of advanced technologies, many of which have contributed to the sustainability of various business sectors. Among these technologies, Artificial Intelligence (AI) has been recognized as a fundamental force reshaping how organizations operate across multiple domains, including marketing. Notable changes in marketing practices have been observed with the adoption of AI technologies. The article explores the intersection of sustainability, AI, and marketing by examining how AI contributes to the sustainability of marketing practices. To achieve this objective, a systematic literature review (SLR) was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The review process was carried out in four stages. First, relevant studies were identified using major academic databases, including Scopus, Web of Science, ScienceDirect, and JSTOR. Second, the retrieved literature was screened to determine its relevance. Third, selection criteria (e.g., document type, language, and publication year) were applied to refine the dataset. Finally, the selected articles were analyzed in depth. The findings reveal that AI plays a dual role. Its contribution is not inherent but largely depends on how it is implemented within organizations. In other words, the impact of AI on marketing sustainability is directly linked to the organization’s sustainability orientation.</p>

Change Management An International Journal
School of Business and Management (FR), Université Sultan Moulay Slimane (MA)
Openalex Percentile: Top 4%
AI in Service Interactions
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Empowering Sustainability in Marketing Through Artificial Intelligence — Fatima Zahra El Arbaoui, Taoufiq Yahyaoui, et al. · Change Management An International Journal (2026) | TGRS Research Map | TGRS