Publication Details
Title:
The Role of AI in Transforming Construction Innovation and Enhancing Safety Standards in Ghana.
Details:
Technology has been instrumental in shaping construction practices worldwide, yet its adoption for innovation and safety management remains underutilized in
Ghana's construction industry. This study investigates the transformative potential of artificial intelligence (AI) in addressing critical challenges such as
inefficiencies, low productivity, and inadequate safety standards. Through a comprehensive review of existing literature, case studies, and contextual analysis, the
study highlights how AI technologies, such as predictive analytics, machine learning, and computer vision, can optimize construction workflows, mitigate risks,
and improve decision-making processes. Four specific objectives guide the research:
(1) To assess the current state of AI adoption in Ghana's construction
industry.
2) To analyze the impact of AI on enhancing construction safety standards in the country.
3) To identify the challenges and barriers to AI implementation
within the Ghanaian construction sector.
4) To propose strategies for integrating AI to advance both safety and innovation in the construction industry
Data were collected using a structured survey administered to 164 construction professionals and stakeholders. This was further complemented by insights from case studies
and an extensive review of relevant literature.
The survey responses were analysed using both descriptive and inferential statistical methods to provide a comprehensive understanding of the findings. The findings reveal a strong preference for AI applications in project management and resource allocation, which are seen as critical to improving efficiency and sustainability. However, adoption in areas like safety monitoring, robotics, and general construction tasks remains limited due to high costs and inadequate infrastructure. The study highlights AI's potential to enhance construction safety, with technologies for hazard detection and predictive analytics receiving high ratings from respondents. Despite this, barriers such as a lack of skilled workers, financial constraints, and resistance to change pose significant challenges. Strategies for overcoming these barriers include targeted workforce development, leveraging predictive safety systems, and adopting AI-driven robotics to streamline workflows. These findings underscore the need for a comprehensive approach to AI integration, combining policy support,
training programs, and financial incentives to foster widespread adoption. By addressing existing challenges and prioritizing safety-focused applications, Ghana’s
construction sector can harness AI to improve operational standards, reduce risks, and drive innovation. This study contributes to the growing discourse on AI in
construction, providing actionable insights for stakeholders aiming to enhance the industry's readiness for technological transformation.