A Systematic Literature Review on AI- Driven Sustainable Marketing Optimization

Authors

  • Sharan Anna Titus Research Scholar, School of Business, Galgotias University, Greater Noida, India Author
  • Dr. Vivek Agarwal Professor, School of Business, Galgotias University, Greater Noida, India Author
  • Dr. Divya Mahajan Professor, Department of Mathematics, Satyawati College, University of Delhi, Delhi, India Author

DOI:

https://doi.org/10.5281/zenodo.20150956

Keywords:

Marketing, Artificial Intelligence, Sustainability, Triple Bottom Line, Big Data, Predictive Analytics, Machine Learning.

Abstract

A transitional shift from Industry 4.0, inclusive of rapid growth in Big Data Analytics lead to development of Internet of Things and Artificial Intelligence to Industry 5.0 whose main theme is human centrism and sustainable wellbeing, has created a major shift in both marketing practices and consumer behaviour. The development in AI over the passage of time has not onlydriven innovation inmarketing segment but has made people think in which directions these advancements are shaping both consumer behaviour and influencing society at large. While Sustainability has become a pressing concern in the current global landscape, marketers have promptly shifted from what was called as basic marketing strategies to a more modern approach which aims to achieve a balance between profits and social and environmental responsibilities. This study analysis the marketer's viewpoint in relation to their evolving marketing strategies to be in coordination with increased emphasis on sustainability by analyzing peer-reviewed papers from Scopus and Google Scholar between the years 2000 and 2024, using keywords like “AI in marketing”, “marketing optimization,” and “sustainable marketing,”. The research gap identified reflects the lack of a unified perspective on how AI is operationalized to drive sustainable marketing outcomes. A ballpark view of the current literature available highlights AI – Driven tools such as chatbots, predictive analytics, and conversational marketing are improving personalization and efficiency, they also support the Triple Bottom Line (TBL) approach- balancing profit, social responsibility, and environmental care. As the study progresses further critical concerns like data biases, ethical concerns, uncertain long-term impacts of technology, and privacy issues undermining the efforts toward sustainable marketing are also analyzed to come to a holistic view on AI-led sustainable marketing aspects. 

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Published

26-05-2026

How to Cite

A Systematic Literature Review on AI- Driven Sustainable Marketing Optimization. (2026). Canadian Journal of Marketing Research, 16(2), 443-452. https://doi.org/10.5281/zenodo.20150956

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