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

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Listed:
  • 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)

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.

Suggested Citation

  • Mustapha Zakari & Kurbom Tieru Chris & Boahene Akomah Benjamin & Yankah Jonas Ekow, 2024. "Limitations for the Implementation of Artificial Intelligence in Construction Health and Safety in Ghana," Baltic Journal of Real Estate Economics and Construction Management, Sciendo, vol. 12(1), pages 103-118.
    • Handle: RePEc:vrs:bjrecm:v:12:y:2024:i:1:p:103-118:n:1007
    DOI: 10.2478/bjreecm-2024-0007
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    References listed on IDEAS

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    1. Nongiba Kheni & Andy Dainty & Alistair Gibb, 2008. "Health and safety management in developing countries: a study of construction SMEs in Ghana," Construction Management and Economics, Taylor & Francis Journals, vol. 26(11), pages 1159-1169.
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