Roadmap on Artificial Intelligence-Augmented Additive Manufacturing

Author(s)

• Ali Zolfagharian
• Liuchao Jin
• Qi Ge
• Wei-Hsin Liao
• Andrés Díaz Lantada
• Francisco Franco Martínez
• Tianyu Zhang
• Tao Liu
• Charlie C.L. Wang
• Mohammad Hossein Mosallanejad
• Reza Ghanavati
• Abdollah Saboori
• Alejandro De Blas De Miguel
• William Solórzano-Requejo
• Yi Cai
• Xiangyang Dong
• Huangyi Qu
• Najmeh Samadiani
• Guangyan Huang
• Austin Downey, University of South CarolinaFollow
• Yanzhou Fu
• Lang Yuan, University of South Carolina - ColumbiaFollow

Document Type

Article

Abstract

Artificial intelligence-augmented additive manufacturing (AI2AM) represents a transformative frontier in digital fabrication, where artificial intelligence (AI) is embedded not as a peripheral tool, but as a central framework driving intelligent, adaptive, and autonomous additive manufacturing (AM) systems. The objective of this Roadmap is to present a comprehensive vision of the state-of-the-art developments in AI2AM while charting the future trajectory of this rapidly emerging field. As AM applications continue to expand across diverse sectors, conventional design and control strategies face growing limitations in scalability, quality assurance, and material complexity. AI uses tools like computer vision, generative design, and large language models to help solve problems in scalability, quality assurance, and material complexity, allowing for real-time defect detection, digital twin integration, and closed-loop process control. This roadmap brings together leading contributions from twenty internationally recognized research groups by uniting perspectives from materials science, computer science, robotics, and manufacturing. This work aims to create a cohesive framework for advancing AI2AM as a multidisciplinary science. The ultimate intent of this work is to establish a foundation for coordinated research and innovation in AI-powered AM and to serve as a strategic entry point for future breakthroughs in autonomous and sustainable production.

Digital Object Identifier (DOI)

https://doi.org/10.1002/aisy.202500484

Publication Info

Published in Advanced Intelligent Systems, Volume 8, Issue 4, 2026, pages e202500484-.

Rights

© 2026 The Author(s). Advanced Intelligent Systems published by Wiley-VCH GmbH

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

APA Citation

Zolfagharian, A., Jin, L., Ge, Q., Liao, W., Díaz Lantada, A., Franco Martínez, F., Zhang, T., Liu, T., Wang, C. C. L., Mosallanejad, M. H., Ghanavati, R., Saboori, A., De Blas De Miguel, A., Solórzano‐Requejo, W., Cai, Y., Dong, X., Qu, H., Samadiani, N., Huang, G., & Downey, A. (2026). Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing. Advanced Intelligent Systems, 8(4),e202500484.https://doi.org/10.1002/aisy.202500484