Work

Artificial intelligence-driven green innovation in packaging: A systematic review of adoption and diffusion challenges

Year: 2025

Type: review

Abstract: • A systematic review of 48 studies on AI-driven green packaging innovations (2020–2025). • Machine learning and deep learning are the most adopted AI technologies in packaging. • Key barriers include high costs, technical complexity, and regulatory uncertainty. • Future trends highlight scalability, circular economy integration, and AI model advancement. • A conceptual framework is proposed linking AI technologies, barriers, and innovation trends. Global concern about environmental protection has intensified the demand for sustainable packaging solutions. Integrating artificial intelligence (AI) into green innovation offers a transformative way to address these challenges. This study applies a systematic literature review (SLR) guided by the PRISMA 2020 framework to examine recent AI-powered packaging innovations. Forty-eight peer-reviewed articles, published between 2020 and 2025, were analyzed. The findings show that Machine Learning, Deep Learning, and general AI applications are the most frequently adopted technologies. Biodegradable packaging materials and smart packaging systems represent the main sustainable packaging types. AI applications are concentrated in process optimization, smart packaging monitoring, fraud detection, computer vision, and natural language processing. However, widespread adoption faces obstacles such as high costs, technical complexity, and regulatory uncertainty. Future trends highlight the importance of scalable technologies, advanced AI models, integration with the circular economy, and interdisciplinary collaboration. This review provides a structured framework to guide academics, industry practitioners, and policymakers in adopting AI-driven green innovation for sustainable packaging.

Source: Intelligent Systems with Applications

DOI: 10.1016/j.iswa.2025.200589

Authors: Ye Ma, Nor Hidayati Zakaria, Basheer Al-Haimi, Chen Wu

Institution: University of Technology Malaysia

Language: English

Topic: Impact of AI and Big Data on Business and Society

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Responsible consumption and production, Climate action

Open Access status: gold

Estimated APC paid: $1,790