Oct 2026· Journal of Global Marketing· 75 references
Environmental Sustainability in Business
Abstract
Generative AI (GenAI) has emerged in global marketing amid intensifying sustainability regulation and scrutiny. Yet the same generative capabilities that can support the detection of greenwashing may also facilitate its production and dissemination. This systematic review examines how GenAI in marketing is governed for sustainability, integrated into marketing operations, and shaped by cultural context. Following PRISMA 2020, we searched five databases for English-language studies published between January 2020 and May 2026, yielding 77 studies for analysis. Three findings emerge. First, GenAI functions simultaneously as verification and persuasion infrastructure. Because both functions draw on the same generative capability, this duality is structural; its sustainability implications depend on the governance conditions surrounding deployment. Second, cultural adaptation remains underdeveloped: only 9% of studies provide strong evidence on this dimension, Sub-Saharan Africa is absent from the corpus, and Latin America and the Caribbean are represented by a single study. Third, although 77% of studies engage themes relevant to the Sustainable Development Goals (SDGs), only 10% explicitly identify specific goals, with the largest gap concerning SDG 12. By integrating governance, operational deployment, and cultural context, this review identifies the conditions under which GenAI may support or undermine sustainable marketing.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
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