Artificial Intelligence in Smart Construction (Industry Readiness and Challenges in Implementation in Kuwait)

The integration of artificial intelligence (AI) in construction has become a global trend, offering enhanced efficiency, safety, and sustainability. However, the extent of AI deployment and the readiness of firms to embrace it vary significantly across regions. This study explores the state of AI adoption in Kuwait’s construction sector by assessing perceived benefits, organizational readiness, implementation barriers, and industry outlook. A structured questionnaire was distributed to 180 professionals including civil engineers and project managers useing a structured questionnaire included five key dimensions to collect data from a representative sample. The study was conducted over four months, from October 2024 to January 2025. Findings reveal moderate levels of current AI integration and readiness, with cost, lack of expertise, and cultural resistance identified as key challenges. The study offers practical and theoretical implications for guiding smart construction transformation in Kuwait and similar regional contexts. Construction firms can benefit from investing in AI-focused training, improving technical infrastructure, and fostering a culture of innovation. Government agencies and industry associations should prioritize the development of a national AI roadmap, offer financial incentives, and facilitate public-private collaborations. These efforts can address the barriers identified and leverage the positive perceptions to build a more AI-ready construction ecosystem in Kuwait.

Authors

Publication Details

Journal
Academic Journal of Research and Scientific Publishing
Published
2025-04-05
DOI
https://doi.org/10.52132/ajrsp.e.2025.72.2
Citations
2
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
2.01
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article

Artificial Intelligence in Smart Construction (Industry Readiness and Challenges in Implementation in Kuwait)

Meshan Alotaibi, Ahmad Alshemmari
2 citations
Academic Journal of Research and Scientific Publishing
BIM and Construction Integration
2.01
article

Artificial Intelligence in Smart Construction (Industry Readiness and Challenges in Implementation in Kuwait)

Meshan Alotaibi, Ahmad Alshemmari
article en
2 citations

Abstract

The integration of artificial intelligence (AI) in construction has become a global trend, offering enhanced efficiency, safety, and sustainability. However, the extent of AI deployment and the readiness of firms to embrace it vary significantly across regions. This study explores the state of AI adoption in Kuwait’s construction sector by assessing perceived benefits, organizational readiness, implementation barriers, and industry outlook. A structured questionnaire was distributed to 180 professionals including civil engineers and project managers useing a structured questionnaire included five key dimensions to collect data from a representative sample. The study was conducted over four months, from October 2024 to January 2025. Findings reveal moderate levels of current AI integration and readiness, with cost, lack of expertise, and cultural resistance identified as key challenges. The study offers practical and theoretical implications for guiding smart construction transformation in Kuwait and similar regional contexts. Construction firms can benefit from investing in AI-focused training, improving technical infrastructure, and fostering a culture of innovation. Government agencies and industry associations should prioritize the development of a national AI roadmap, offer financial incentives, and facilitate public-private collaborations. These efforts can address the barriers identified and leverage the positive perceptions to build a more AI-ready construction ecosystem in Kuwait.

Academic Journal of Research and Scientific PublishingVol. 6(72)
Openalex Percentile: Top 16%
BIM and Construction Integration
2.01
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Artificial Intelligence in Smart Construction (Industry Readiness and Challenges in Implementation in Kuwait) — Meshan Alotaibi, Ahmad Alshemmari · Academic Journal of Research and Scientific Publishing (2025) | TGRS Research Map | TGRS