Automation in Construction· 2026Q1· Review
BIM and AI for optimising energy, economy, and environment in construction projects: Systematic review (2014–2026)
- 0citations
- Q1SCImago
- 2026year
Short summary
A systematic review of 57 studies (2014-2026) found that only 9% of research combining Building Information Modelling (BIM) and Artificial Intelligence (AI) simultaneously optimizes energy, cost, and carbon emissions (3E nexus) across the construction project lifecycle.
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Key points
- Only 9% of 57 reviewed studies (2014-2026) jointly optimize energy, cost, and carbon emissions using BIM and AI.
- Key themes include BIM-BEM interoperability, AI-driven energy prediction, AI-based HVAC control, lifecycle carbon assessment, and digital twins for 3E co-optimization.
- Significant gaps identified are fragmented toolchains, single-dimension optimization, lack of Global South context, and missing end-to-end digital twin pipelines.
- The review proposes seven prioritized research directions based on identified gaps and stakeholder mapping.
AI-generated from the title and abstract; the full text is not read.
Abstract
Buildings account for roughly 37% of global energy use and 40% of energy-related CO 2 emissions, yet Building Information Modelling (BIM) and artificial intelligence (AI) are seldom combined to address energy, economy, and environment (the 3E nexus) simultaneously. However, existing reviews have not systematically examined the joint application of BIM and AI to address 3E objectives across the full project lifecycle in a PRISMA 2020-compliant review. This paper synthesises 57 primary studies (2014–2026) from four databases, with within-rater screening agreement κ = 0.83 . Five themes structure the review: BIM–BEM interoperability, AI-driven energy prediction and multi-objective design optimisation, AI-based HVAC control, lifecycle carbon assessment, and digital twins for 3E co-optimisation. Most strikingly, only 5 of 57 studies (9%) address energy, cost, and carbon in a single workflow. Four gaps, namely fragmented IFC/gbXML toolchains, single-dimension optimisation, limited representation of Global South contexts, and the lack of an end-to-end digital twin pipeline, motivate seven prioritised research directions with stakeholder mapping and feasibility assessments.
The authors' abstract, as published at the source. Automation in Construction, 2026 · DOI ↗
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Field: Building and Construction
Building and ConstructionEngineering