Artificial Intelligence in 3D Printed Concrete: Sustainability Assessment and Implementation Challenges
Samuel Oseji *
Department of Geology, Riner Engineering (UES), Texas, University of Texas at San Antonio, United States.
Prince Chukwuemeka
Department of Computing and Informatics, Bournemouth University, United Kingdom.
Okes Imoni
Department of Biological Sciences, Niger Delta University, Wilberforce Island, Bayelsa State, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
The integration of Artificial Intelligence (AI) into 3D Printed Concrete (3DPC) is reshaping sustainable construction by enabling real-time optimization, automation, and environmental performance gains. Amid escalating climate change, urban growth, and resource constraints, AI-enhanced 3DPC offers a pathway to resilient and low-carbon built environments. We examine how machine learning, computer vision, and predictive analytics are transforming 3DPC across material design, process monitoring, and lifecycle assessment. Notably, AI-enabled optimization frameworks have demonstrated up to 60% reductions in material waste and 30% improvements in energy efficiency. We analyze AI-driven advancements in mix proportioning, robotic path planning, and sensor-based quality control, emphasizing how dynamic feedback loops support adaptive manufacturing. Socio-economic implications such as shifts in labor demand and emerging skill requirements are also addressed, underscoring the broader workforce transformation underway in AI-automated construction. Key challenges include limited datasets, opaque algorithmic decision-making, integration difficulties in complex site conditions, and high computational costs. To address these, we propose multi-objective optimization strategies, circular economy approaches, and transparent, human-AI collaborative systems. Our findings reveal that fully realizing the sustainability potential of AI in 3DPC depends on interdisciplinary collaboration, interpretable AI models, and forward-thinking policy support. By aligning technological innovation with regulatory frameworks and human expertise, AI-powered 3DPC can serve as a cornerstone for next-generation construction enabling greener, faster, and more inclusive infrastructure development worldwide.
Keywords: Artificial intelligence, 3D printed concrete, sustainability, life cycle assessment, construction automation, circular economy, predictive analytics, built environment