Mapping Cost Intersection Through LCC, BIM, and AI: A Systematic Literature Review for Future Opportunities

The increasing integration of digital technologies in the construction sector is transforming the processes of buildings design, management, and evaluation throughout their life cycle. Life Cycle Costing (LCC), Building Information Modeling (BIM), and openBIM standards play a key role in promoting economic and environmental sustainability. More recently, Artificial Intelligence (AI) has unlocked novel possibilities for data-driven decision-making and cost optimization. However, the integration of LCC, BIM, and AI is insufficiently explored in the current literature. This study presents a systematic literature review (SLR) aimed at analyzing two distinct lines of research, LCC–BIM and LCC–AI, and identifying underexplored opportunities for their future convergence. A dual-stream approach was adopted to analyze scientific contributions based on LCC–BIM and LCC–AI separately, using bibliometric analysis and the systematic screening of peer-reviewed articles from 2015 to 2025. The findings reveal that while LCC–BIM integration shows growing methodological maturity, AI-based applications are still in an early stage, with limited implementation in construction-specific contexts. The review identifies key challenges, including data fragmentation, a lack of interoperability, and limited standardization, as significant impediments to integrated digital workflows. By highlighting these gaps and proposing actionable future directions, the paper outlines future research directions focused on open data models, AI-enhanced cost estimation, and the development of interoperable frameworks to support sustainable and intelligent cost management in the Architecture, Engineering, and Construction (AEC) sector.