The Role of Generative Artificial Intelligence in Shaping Consumer Behavior toward Sustainable Consumption: A Systematic Literature Review
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Abstract
Generative Artificial Intelligence (GenAI) has emerged as a transformative technology that reshapes consumer decision-making and creates new opportunities to promote sustainable consumption. However, existing studies remain fragmented across marketing, consumer behavior, and sustainability literature, limiting a comprehensive understanding of GenAI’s role in encouraging sustainable consumer behavior. This study aims to systematically synthesize the existing literature on the role of GenAI in shaping consumer behavior toward sustainable consumption. A Systematic Literature Review (SLR) was conducted following the PRISMA 2020 guidelines. Relevant English-language publications indexed in the Scopus database from 2020 to 2026 were identified and analyzed using thematic analysis. The review identifies seven major themes, including the evolution of GenAI in consumer decision-making, AI-driven personalization, psychological mechanisms, sustainable marketing, behavioral determinants, ethical challenges, and future research directions. The findings indicate that GenAI facilitates sustainable consumption by improving personalized recommendations, trust, environmental knowledge, and consumer engagement, while transparency, privacy, and algorithmic bias remain critical challenges. This study contributes by integrating fragmented knowledge into a comprehensive thematic framework and proposing future research directions to advance AI-enabled sustainable consumption research and practice.
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References
Ahmed, A., Fadzilah, A. H. H., & Chan, T. J. (2025). Impact of Green Media on Purchase Intention: The Moderating Role of Artificial Intelligence in Sustainable Marketing. PaperASIA, 41(4b), 344–359.
Al-Sharafi, M.A., Al-Emran, M., Arpaci, I., Iahad, N.A., AlQudah, A.A., Iranmanesh, M. and Al, & Qaysi, N. (2023). “Generation Z use of artificial intelligence products and its impact on environmental sustainability: a cross-cultural comparison.” Computers in Human Behavior, 143. https://doi.org/10.1016/j.chb.2023.107708.
Almeida, S., & Ivanov, S. (2024). Generative AI in hotel marketing: A reality check. Tourism: An International Interdisciplinary Journal, 72(3), 422–455. https://doi.org/https://doi.org/10.37741/t.72.3.7
Alyousuf, A. N. J., Sabeeh, A. O., Alnaemat, N. D. O., Mouloudj, K., & Hussein, S. A. (2026). Understanding Gen Z’s Adoption of AI Technologies in Green Product Purchases: An Extension of the Technology Acceptance In Insights on Consumer Psychology in the Digital Landscape Model. IGI Global Scientific Publishing, 369–392. https://doi.org/https://doi.org/10.4018/979-8-3373-2424-1.ch013
Bharadwaj, S. (2026). AI-based recommendations and sustainable agri-food purchase intentions: Examining the credence goods paradox through emotional-TAM among Generation Z in India. British Food Journal, 1–20. https://doi.org/https://doi.org/10.1108/BFJ-09-2025-1264
Cao, P., & Liu, S. (2023). The impact of artificial intelligence technology stimuli on sustainable consumption behavior: Evidence from Ant Forest users in China. Behavioral Sciences, 13(7), 604. https://doi.org/https://doi.org/10.3390/bs13070604
Foroughi, B., Naghmeh-Abbaspour, B., Wen, J., Ghobakhloo, M., Al-Emran, M., & Al-Sharafi, M. (2025). Determinants of Generative AI in Promoting Green Purchasing Behavior: A Hybrid Partial Least Squares–Artificial Neural Network Approach. Business Strategy and the Environment, 34, 4072–4094. https://doi.org/https://doi.org/10.1002/bse.4186
Foroughi, B., & Al-sharafi, M. A. (2026). How generative AI drives green purchase behavior : a dual-method study. https://doi.org/10.1108/APJML-11-2025-2386
Garg, V., Bohara, S., & Srivastav, A. (2025). AI-driven sustainability marketing transforming consumers’ perception toward eco-friendly brands. Discover Sustainability, 6, 984. https://doi.org/. https://doi.org/10.1007/s43621-025-01934-y
Haws, K. L., Winterich, K. P., & Naylor, R. W. (2014). Seeing the world through green-tinted glasses: Green consumption values and responses to environmentally friendly products. Journal of Consumer Psychology, 24(3), 336-354.
Huang, M.-H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155–172. https://doi.org/https://doi.org/10.1177/1094670517752459
Khaldy, M. A., Fasha, M., & Barham, H. (2026). Business Intelligence and Green Marketing Effectiveness: A Data-Driven Approach to Sustainable Customer Segmentation. Proceedings of the 8th International Symposium on Computational and Business Intelligence. https://doi.org/https://doi.org/10.1109/ISCBI69404.2026.11496239
Lin, T., Xu, T., Zac, A., Tomkins, S., & Elkind, E. (2023). SUSTAINABLESIGNALS: An AI approach for inferring consumer product sustainability. Proceedings of the International Joint Conference on Artificial Intelligence. https://doi.org/https://doi.org/10.24963/ijcai.2023/675
Ma, J., Wang, Q., Liu, D., Pan, H., & Ran, H. (2025). Do environmental values drive artificial intelligence products green purchasing behavior? A value-attitude-behavior approach. Acta Psychologica, 260, 105467. https://doi.org/https://doi.org/10.1016/j.actpsy.2025.105467
Makani, A. L. S. (2025). Social Relations, Consumption Patterns, And Sustainable Consumption Behaviors Of Students In An Urban Environment: The Last Few Of Basic Education Curriculum (Bec) Before K12 In Iloilo City. Philippine Sociological Review, 73, 135–153. https://www.jstor.org/stable/48857241
Marolla G, Sabbagh P, Rosa A, M. O. (2026). “Leveraging generative artificial intelligence for process innovation: the moderating role of IT culture and organisational flexibility”. European Journal of Innovation Management, 29(11), 427–444. https://doi.org/https://doi.org/10.1108/EJIM-09-2025-1269
Minton, E. A., Tan, S. J., Tambyah, S. K., & Liu, R. L. (2022). Drivers of Sustainability and Consumer Well-Being: An Ethically-Based Examination of Religious and Cultural Values. Journal of Business Ethics, 175(1), 167–190. http://www.jstor.org/stable/45406893
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372(71). https://doi.org/https://doi.org/10.1136/bmj.n71
Page, M. J., Moher, D., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & McKenzie, J. E. (2021). PRISMA 2020 explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews. BMJ, 372(160). https://doi.org/https://doi.org/10.1136/bmj.n160
Panda, M., Singh, K., Raj, A., & Puri, R. (2026). Understanding the interplay between generative artificial intelligence and consumer behaviour through a systematic literature review.
Panwar, N., Shetty, D. K., & Shenoy, S. S. (2025). Can AI-driven nudging promote sustainable product adoption on e-commerce platforms? Revista de Administração Contemporânea, 29(6). https://doi.org/adoption on e-commerce platforms? Revista de Administração Contemporânea, 29(6). https://doi.org/10.1590/1982-7849rac2025250105.en
Phuangsuwan, P., Siripipatthanakul, S., Chaiprakarn, S., Rakpathum, W., Muthmainnha, Pariwongkhuntorn, N., & Wattanakul, P. (2024). Sustainable Development Adopting Artificial Intelligence (AI) in Marketing and Consumer Behaviour Analysis In International Conference on Data Analytics & Management. Singapore: Springer Nature Singapore, 569–587. https://doi.org/https://doi.org/10.1007/978-981-96-3372-2_39
Qadri, U. A., Moustafa, A. M. A., & Waqas, M. (2026). When and how AI personalization drives sustainable purchases: The roles of relevance, privacy, and transparency in eco-friendly advertising. Journal of Retailing and Consumer Services, 89, 104592. https://doi.org/https://doi.org/10.1016/j.jretconser.2026.104592
Riandhi, A. N., Arviansyah, M. R., & Sondari, M. C. (2025). AI and consumer behavior: Trends, technologies, and future directions from a scopus-based systematic review. Cogent Business & Management, 12(1). https://doi.org/10.1080/23311975.2025.2544984
Rodríguez-Ulcuango, O. M., Guerra-Flores, C. O., Sánchez-Chávez, R. F., & Cedeño-Ávila, G. M. (2025). Sensorial marketing within consumer behavior: bibliometric analysis and future trends. Cogent Business & Management, 12(1), 212–239. https://doi.org/10.1080/23311975.2025.2503422
Sadiq, M. W., Akhtar, M. W., Huo, C., & Zulfiqar, S. (2024). ChatGPT-powered chatbot as a green evangelist: An innovative path toward sustainable consumerism in e-commerce. The Service Industries Journal, 44(3–4), 173–217. https://doi.org/https://doi.org/10.1080/02642069.2023.2278463
Sauer, P. C., & Seuring, S. (2023). How to conduct systematic literature reviews in management research: A guide in 6 steps and 14 decisions. Review of Managerial Science, 17(5), 1899–1933. https://doi.org/https://doi.org/10.1007/s11846-023-00668-3
Si, K., Wang, C., Wei, S., & Lan, Y. (2026). Generative AI-enabled precision recommendation for green products: Mechanisms of consumer cognitive fluency and low-carbon purchase decisions. Sustainability, 18(4), 2018. https://doi.org/https://doi.org/10.3390/su18042018
Sidra, S., & Wagan, S. M. (2026). How artificial intelligence enabled marketing activities will change consumer behavior. Discover Artificial Intelligence, 6(17). https://doi.org/https://doi.org/10.1007/s44163-025-00735-6
Silalahi, A. D. K. (2025). Can generative artificial intelligence drive sustainable behavior? A consumer-adoption model for AI-driven sustainability recommendations. Technology in Society, 83, 102995. https://doi.org/https://doi.org/10.1016/j.techsoc.2025.102995
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/https://doi.org/10.1016/j.jbusres.2019.07.039
Sun, J. J., Bellezza, S., & Paharia, N. (2021). Buy Less, Buy Luxury: Understanding and Overcoming Product Durability Neglect for Sustainable Consumption. Journal of Marketing, 85(3), 28–43. https://www.jstor.org/stable/27114292
Surbakti, F. P. S., Hutahaean, H. A., Inderawati, M. M. W., Madjid, J. M., Sely, L. E., & Yee, Y.-M. (2025). How AI-driven personalization shapes green purchasing behavior among youth in Java Island. Sustainability, 17(21), 9600. https://doi.org/https://doi.org/10.3390/su17219600
Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222. https://doi.org/10.1111/1467-8551.00375
Trong Nguyen, L., Nguyen, T. H., Ngoc Nguyen, H., Dai Nguyen, L., Thi Thu Nguyen, D., & Duy LE, L. (2023). Determinants of green consumer behavior: A case study from Vietnam. Cogent Business & Management, 10(1). https://doi.org/10.1080/23311975.2023.2197673
Wadia, A. K., & Rawal, N. (2026). AI-Enabled Creative Marketing for Eco-Friendly Campaigns. In Marketing in a Digital World. Palgrave Macmillan. https://doi.org/https://doi.org/10.1007/978-981-95-6505-4_9
Wang, H., Jiang, S., Li, X., Alipour, O., & Agag, G. (2026). Can AI make us less green? Insights from four experiments on digital speed, time perception, and sustainable consumption. Journal of Retailing and Consumer Services, 90, 104696. https://doi.org/https://doi.org/10.1016/j.jretconser.2025.104696
Wang, P. (2019). On defining artificial intelligence. Journal of Artificial General Intelligence, 10(2), 1–37. https://doi.org/10.2478/jagi-2019-0002
Zambrano-Vélez, W., Carrión-Bósquez, N., Bernal-Peralta, J., Vélez-Luna, A., Villacís-Mejía, C., Tobar-Cazares, X., et al. (2026). From Artificial Intelligence to Green Purchasing Behavior: The Role of Environmental Knowledge and Green Truth in Shaping Environmental Attitudes and the Purchase of Organic Products in University Students. Sustainability, 18(10), 5167. https://doi.org/https://doi.org/10.3390/su18105167
Zhang, F., Cui, Y., & Zhang, S. (2026). Confronting AI-generated information diversity and uncertainty and heterogeneous impact on sustainable consumption. 106(November 2025).
Zulaikha, S., Dewi, I. R., & Kurniawati, M. (2026). Unveiling the intellectual landscape of artificial intelligence and consumer behavior. Discover Artificial Intelligence, 6(2). https://doi.org/https://doi.org/10.1007/s44163-025-00740-9