Potential domains, challenges and evaluation standards for integrating artificial intelligence and BIM into construction processes

Purpose This research examined the potential integration of artificial intelligence (AI) with building information modeling (BIM) in construction organizations, the main operational difficulties of integrating BIM and AI and the assessment criteria for integrated BIM–AI in construction companies. Design/methodology/approach The study combined the strategic alignment model and balanced scorecard theoretical views to establish sub-constructs for the application domains, operational problems and assessment criteria of integrated BIM–AI. Findings The study’s findings indicate the potential applications of BIM–AI, including an AI-supported BIM content recommender system, predictive AI models for defect identification and an AI-generated structural engineering BIM model. The operational hurdles to integrating BIM and AI include disparities between AI and BIM models, the loss of skilled personnel and motivation and excessive workloads. Originality/value This study’s originality stems from its innovative approach to showcasing the effective use of AI in BIM for construction operations, as well as strategies for establishing smooth integration and interoperability between BIM and AI systems.

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Institutions

Publication Details

Journal
Frontiers in Engineering and Built Environment
Published
2025-08-11
DOI
https://doi.org/10.1108/febe-09-2024-0056
Citations
1
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
1.01
Controls
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article

Potential domains, challenges and evaluation standards for integrating artificial intelligence and BIM into construction processes

Obuks Ejohwomu, Emmanuel Dele Omopariola, Oluseye Olugboyega, Omolola Khadijat Osundare
1 citations
Frontiers in Engineering and Built Environment
BIM and Construction Integration
1.01
article

Potential domains, challenges and evaluation standards for integrating artificial intelligence and BIM into construction processes

Obuks Ejohwomu, Emmanuel Dele Omopariola, Oluseye Olugboyega, Omolola Khadijat Osundare
article en
1 citations

Abstract

Purpose This research examined the potential integration of artificial intelligence (AI) with building information modeling (BIM) in construction organizations, the main operational difficulties of integrating BIM and AI and the assessment criteria for integrated BIM–AI in construction companies. Design/methodology/approach The study combined the strategic alignment model and balanced scorecard theoretical views to establish sub-constructs for the application domains, operational problems and assessment criteria of integrated BIM–AI. Findings The study’s findings indicate the potential applications of BIM–AI, including an AI-supported BIM content recommender system, predictive AI models for defect identification and an AI-generated structural engineering BIM model. The operational hurdles to integrating BIM and AI include disparities between AI and BIM models, the loss of skilled personnel and motivation and excessive workloads. Originality/value This study’s originality stems from its innovative approach to showcasing the effective use of AI in BIM for construction operations, as well as strategies for establishing smooth integration and interoperability between BIM and AI systems.

Frontiers in Engineering and Built EnvironmentVol. 5
University of Cape Town (ZA), University of Manchester (GB), Obafemi Awolowo University (NG)
Openalex Percentile: Top 19%
BIM and Construction Integration
1.01
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Potential domains, challenges and evaluation standards for integrating artificial intelligence and BIM into construction processes — Obuks Ejohwomu, Emmanuel Dele Omopariola, et al. · Frontiers in Engineering and Built Environment (2025) | TGRS Research Map | TGRS