Artificial intelligence effects on construction project management and a future perspective

Abstract

Artificial intelligence (AI) has many effects on the world as technologies based on AI create a new way of life and business climate by changing people, companies, and industries. Regarding digital transformation and innovation strategies, in particular, industries and their stakeholders can play active and/or passive roles in these changes. At this point, the role that the construction industry (CI) and its stakeholders prefer to take can have the potential to influence the construction ecosystem's future and functioning. The aim of this research is to determine the present and prospective future effects of AI technologies on the CI on the basis of construction project management (CPM) and to reveal development and transformation perspectives in this direction. The following objectives were accomplished in this study: to identify AI's presence and effect on Project Management Knowledge Areas (PMKA), Project Management Process Groups (PMPG), Performance Domains, and Project Delivery Principles; to review AI's adaptation to education on CPM; to examine the situation of application areas of AI in CPM on the basis of CI; to determine the readiness of academics and private sector employees in the CI for AI technology; to indicate SWOT analysis for the integration of AI into CPM; to provide an HR perspective on the industrial impact, human resources loss, and demand that this interaction will generate; and to propose strategies for integrating AI into the CI based on CPM. To accomplish the aim and objectives of this research, an in-depth literature review, online questionnaire survey, and online interviews were carried out. The sample for the questionnaire survey consisted of academics and professionals who have academic publications and/or experience on AI, CPM, and CI. Among the questionnaire survey participants, 67 participants answered all questions. The sample for the online interviews consisted of academics and professionals who have academic publications and/or experience on AI, CPM, and CI. Online interviews were conducted with the participation of 19 interviewees from different countries. Interviews took 28 minutes on average. Interviews were conducted by obtaining the knowledge, experience, and future predictions of experts in the AI and CI. All acquired data and information obtained through questionnaire survey and interviews were processed with various analysis and statistical methods, and correlations and interactions were presented. Main topics on findings obtained within the scope of this thesis: Regarding AI's impact on the CI in terms of project management approaches, the project management knowledge areas that AI may have a significant impact on the future have been identified. Furthermore, prominent areas in project management processes, performance areas, and delivery principles have been identified. Regarding the adaptation of education on the basis of CPM, it has been presented that it may be efficient and necessary to renew the curriculum at the undergraduate level in the short term on the basis of AI applications and data science. On the basis of CPM, AI application area which is the most anticipated area to be used both in the current situation and in the future has been identified. Factors limiting AI applications within the framework of CPM may be their ability to comprehend and utilize AI. Survey participants have emphasized that academics and professionals with AI knowledge are more likely to be ready and feel excited about AI technologies. Within the framework of the SWOT analysis, possible opportunities, drivers for the integration of AI into CPM as well as potential threats and barriers against the integration of AI into CPM have been identified. More than half of the skill sets of construction project managers are likely to change in the next 10 years. On the basis of CPM, capabilities that may be required in the future, and capabilities that may not be required by construction project managers in the future have been identified. In terms of qualified human resources needs, the health-safety knowledge area in construction is likely to have the highest human resource needs, both today and future, but it is also probably the one that may require acquisition of new skills the most. Even if, the communication management field is expected to have intensive human resources in the future, the need for acquiring new skills can probably be the least. Other areas where there is likely to be a high need for qualified people have been identified within the scope of this research as well. These areas may also be the areas that can probably necessitate human resources the least in the next 10 years. Accurate data-rich organizations can be more likely to gain a competitive advantage in the future by utilizing AI technologies. AI can probably contribute the most to pre-construction processes in the future. While it is possible that AI's impact on CPM can take at least 11 years to reach 80% or higher levels, it could take at least 17 years to complete its full integration and achieve the highest efficiency. Main recommendations on findings obtained within the scope of this thesis: The use of AI in the CI needs to start by providing the necessary data and financial support to start-up companies and focusing on the development of various potential use-cases. Furthermore, construction companies need to provide basic training to their workers. The strategy of digitalization and innovation in the CI can be conducted on the basis of AI, data, human, and government, and construction companies. The presence of construction companies in each of these four pillars (i.e., AI, data, humans, and government) can enable AI applications to perform better. AI is likely to be effective at the following four levels in the CI in the future: at the first level, assistant-support systems, at the second level the workforce itself, at the third level the building construction from planning to delivery, and at the fourth level, intelligent systems that implement and optimize every phase throughout the building lifecycle without intervention. This study presents a CPM approach based on people, technology, and innovation by providing the intersection of AI, CI, and project management disciplines. This study's main contribution to the literature is that it provides a new AI-based future perspective to the disciplines of construction, architecture, engineering, and management, besides providing the current situation analysis of the construction ecosystem. Even if the findings in this thesis cannot be generalized, they provide ideas and tendencies in approaches. All stakeholders in the construction ecosystem can benefit from this research. People who want to make a career in the CI, academics who want to do research and development in the CI basis on technology, construction companies that want to provide technological transformation-innovation-agility, and government institutions that want to create-develop regulations for the CI on the basis of AI and digitalization.