Artificial Intelligence for Sustainable Industrial Design: A Systematic Literature Review Based on a Technology–System–Institution Framework

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Authors: Xinyu Li, Yingyan Zhang, Conghu Liu, Junyi Zhao, Kai Li
Cited by: 1
References: 92

Abstract

The rapid development of artificial intelligence (AI) is driving the transformation of industrial design towards sustainability. However, a systematic integration framework that can effectively clarify how AI promotes sustainable product design across multiple dimensions remains lacking. This systematic review comprises a detailed analysis of 113 core articles from the Scopus and Web of Science databases (covering 2015–2025), following PRISMA guidelines, examining publication trends, key journals, and citation impacts. From the perspectives of technology, systems, and institutions, this study systematically analyzes AI technologies and their possible application in promoting sustainable industrial design. Based on these findings, the challenges in applying AI in industrial design sustainability are discussed, such as technological controllability, system integration barriers, and policy lags. Key directions for future research are also identified. This review constructs a multi-dimensional framework to systematically explain the applications and mechanisms of AI in promoting sustainable industrial design. It also offers clear theoretical foundations and practical guidance for researchers, practitioners, and policymakers, facilitating the advancement of industrial design in a more sustainable and systematic direction.

Fields of Study & Subjects

Digital Transformation in Industry Design Education and Practice Sustainable Supply Chain Management

Publication details

Journal / source
Processes
Publisher
MDPI AG
Volume
14
Issue
5
Pages
779–779
Publication date
27 February 2026
Language
EN