Vol. 5 No. 2 (2024)

Standard Journal Issues

Harnessing Artificial Intelligence for Transformative Impact in the Ghanaian Construction Sector

Published 2024-10-26

  • Zakari Mustapha
    • ,
  • Benjamin Boahene Akomah
    • ,
  • Ofosu Emmanuel Kwaku
    • ,
  • Morena William Nkomo
    • ,
  • Wellington Didi Thwala

Zakari Mustapha
Department of Construction Technology Management, School of Built and Natural Environment Cape Coast Technical University, Ghana

Benjamin Boahene Akomah
Department of Construction Technology Management, School of Built and Natural Environment Cape Coast Technical University, Ghana

Ofosu Emmanuel Kwaku
Department of Construction Technology Management, School of Built and Natural Environment Cape Coast Technical University, Ghana

Morena William Nkomo
Department of Construction Management and Quantity Surveying, University of Johannesburg, South Africa

Wellington Didi Thwala
Department of Engineering, Built Environment and Information, Walter Sisulu University, South Africa

Abstract

The integration of artificial intelligence (AI) in the construction industry holds significant promise for enhancing various aspects of project management and execution. AI offers unprecedented opportunities for streamlining processes, enhancing productivity, and elevating safety standards. The study explored AI implementation opportunities and how AI technologies can drive innovation, enhance decision-making processes, and propel the sector toward a more efficient and digitised future in the construction industry. To fill the gap, the study adopted a quantitative research approach to offer a holistic assessment of the effects and opportunities for the advancement of AI in Ghanaian construction settings. Based on the quantitative survey data obtained from 97 participants from 10 construction companies in the Central Region of Ghana and the literature review, the study revealed several benefits of AI implementation. The importance of using AI has been seen in design and planning, safety management, and the quality of delivered projects. Regression analysis also expands on the relationships between the identified AI-based efficiencies, underlining that increased utilisation can enhance productivity and safety and reduce adverse environmental impacts. Further, in the context of Ghana, the study outlined areas of importance for constructing AI in the construction industry: construction monitoring, energy efficiency, and supply chain. These findings have depicted the sector’s awareness of AI and its value as a tool for improving effectiveness in operations and implementing sustainable measures. Overall, the knowledge generated by this study proves beneficial for directing strategic planning and advancing innovation in the context of the Ghanaian construction industry. In as much as it acknowledges the gap and the prevailing theoretical literature, it ushers in a guide for availing AI-driven growth in the construction sector in terms of productivity, quality, and sustainability in Ghana and the global space.

Keywords

Artificial Intelligence, Construction Industry, Innovation, Sustainability

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