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

• 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.