Limitations for the Implementation of Artificial Intelligence in Construction Health and Safety in Ghana

Mustapha Zakari (), Kurbom Tieru Chris, Boahene Akomah Benjamin and Yankah Jonas Ekow
Additional contact information
Mustapha Zakari: Department of Construction Technology and Management, School of Built and Natural Environment, Cape Coast Technical University, Cape Coast, Ghana
Kurbom Tieru Chris: Department of Construction Technology and Management, School of Built and Natural Environment, Cape Coast Technical University, Cape Coast, Ghana
Boahene Akomah Benjamin: Department of Construction Technology and Management, School of Built and Natural Environment, Cape Coast Technical University, Cape Coast, Ghana
Yankah Jonas Ekow: Department of Construction Technology and Management, School of Built and Natural Environment, Cape Coast Technical University, Cape Coast, Ghana

Baltic Journal of Real Estate Economics and Construction Management, 2024, vol. 12, issue 1, 103-118

Abstract: Building accidents and fatalities are prevalent, especially in rising nations like Ghana, despite rapid technical developments. Weak regulations, training, and change resistance typically undermine traditional safety measures. This study aimed to identify potential obstacles that prevent the implementation of artificial intelligence (AI) in construction health and safety in Ghana. A survey research approach was employed to get the study population, which consisted of 110 construction experts made up of project managers, site engineers, skilled workers, and safety officers complete the questionnaire. Data analysis included descriptive statistics, chi-square, and regression. According to varied demographic responses, AI increases design and engineering, safety and security, and human resources efficiency, decision-making, and safety. Lack of innovation culture, training, and regulation harms health and safety. Using AI promises to overcome these hurdles by minimising risks, improving worker well-being, and safe work environment. The Ghanaian industry study focus and small sample size may prejudice, as the limitations of the study. Samples must be larger and more diversified to generalise. The practical implication is that Ghanaian builders may use the study’s findings. Understanding AI’s potential and limitations helps them develop AI solutions and problem-solving methodologies. Safety, cost, and worker well-being can improve. The successful integration of AI in construction health and safety can affect society. AI can reduce workplace accidents and improve productivity, well-being, and healthcare costs. This work adds to the growing body of knowledge on AI’s building safety applications in emerging economies like Ghana. It identifies environmental restrictions and enables governments, industry leaders, and researchers to develop and implement AI solutions.

Keywords: Artificial intelligence (AI); construction industry; Ghana; health; safety (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/bjreecm-2024-0007 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:bjrecm:v:12:y:2024:i:1:p:103-118:n:1007

DOI: 10.2478/bjreecm-2024-0007

Access Statistics for this article

Baltic Journal of Real Estate Economics and Construction Management is currently edited by Ineta Geipele

More articles in Baltic Journal of Real Estate Economics and Construction Management from Sciendo
Bibliographic data for series maintained by Peter Golla ().