Role of Artificial Intelligence in Construction Industry of Pakistan

Abstract

The quick development of technology, with a focus on Artificial Intelligence (AI), has resulted in significant changes on a worldwide level. The integration of AI across the full project lifecycle is still in its infancy in the construction sector. To improve the performance of the construction business, rising digital advances like AI must be embraced, although construction companies in developing countries have lagged slightly in doing so. The world has seen tremendous changes as a result of the quick development of technology, particularly Artificial Intelligence (AI). However, the adoption of new digital advances like AI in the construction industry, particularly in developing nations like Pakistan, is still in its early phases. The built sector's construction organizations in these nations have been sluggish to understand the value of integrating AI. This study tries to pinpoint the key organizational elements required to encourage AI adoption in Pakistani construction businesses. This research tries to identify the vital organizational elements that are crucial for promoting the use of AI in the construction industry. To do this, a quantitative survey strategy was used to collect data, using a snowball sampling technique to select industry experts as respondents. These professionals were polled on the issues surrounding the use of AI in building. In order to determine the crucial organizational elements that can accelerate the adoption of AI within the sector, an exploratory factor analysis (EFA) was subsequently conducted on the acquired data. Data from participants will be gathered using a quantitative survey methodology for the project. The relationship between these constructs will also be established via confirmatory factor analysis. The study suggests a number of elements, broken down into four categories, that influence organizational AI adoption: a creative organizational culture, competence-based training, group decision-making, and strategic analysis. Additionally, a confirmatory factor analysis (CFA) was used to provide more light on the connections between the discovered constructs. This study offers a thorough list of characteristics that are essential for promoting corporate AI adoption. Notably, this research presents organizational factors related to AI adoption in the construction and related industries using both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), a method that has not been frequently used in the articles identified in the systematic literature review (SLR). Prior studies have addressed organizational factors related to AI adoption in the construction and related industries. A deeper understanding of the underlying elements and how they interact within the context of AI adoption in the construction industry is made possible by the use of CFA, which increases the construct measurement's accuracy. The ultimate goal of this research is to improve knowledge of the underlying elements of these constructs and how they relate to AI application in Pakistan's construction sector. The study aims to add to knowledge and awareness of the potential of AI in Pakistan's construction business by putting light on these organizational aspects.