Artificial Intelligence (AI) use in construction industry



With the increasing complexity of problems in the construction industry, researchers are exploring computational smart systems to seek smart solutions. Therefore, the purpose of this article is to analyze the research published on “smart systems in the construction industry” in the last years. This is achieved to observe understand historical trends and current patterns in the use of different smart systems and potential aspects of further research. With the advancement and spread of information and communication technologies, concepts such as artificial intelligence (AI) have been incorporated fast in human life. With utilizing and discussion of all published articles the results will provide the importance of artificial intelligence (AI) in construction industry. In future studies, integrating artificial intelligence with construction industry by using software’s compatible with BIM (Building Information Modelling) need to develop WBS (work-breakdown structure) to success the detailed projects.

Keywords: Artificial intelligence (AI), Construction industry, BIM (Building Information Modelling)


  1. Introduction

Artificial intelligence is a sub-part of the computer science, being sophisticated to treat computers wisely and increasingly larger realms. AI participates intensively in computer science passion for abstraction, programming and logical formalism and detail – algorithms on behavioral data, synthesis on analysis, and science on science (how to) (what to do). All these features mentioned in Nilsson’s book. Artificial intelligence (AI), also known as machine intelligence, is a branch of computer science that aims to permeate software with the ability to analyze its environment using either predetermined rules and search algorithms, or pattern recognizing machine learning models, and then make decisions based on those analyses. In this way, AI utilize to mimic biological intelligence to allow the software application or system to act with varying degrees of autonomy, thereby reducing manual human intervention for a wide range of functions. The success of this field is to explore how to emulate and perform some of the intelligent function of human brain, so that people can develop technology products and built relevant theories. The beginning of: artificial intelligence’s rise and fall in the 1950s. The secondary step: as the expert system emerging, a new upsurge of the research of artificial intelligence appeared from the end of 1960s to the 1970s. The thirdly step: in the 1980s, artificial intelligence made a great progress with the development of the fifth-generation computer. The fourthly step: in the 1990s, there is a new upsurge of the research of artificial intelligence: with the development of network technology, especially the international internet technology, artificial intelligence research by a single intelligent agent began to turn to the study of distributed artificial intelligence based on network environment.

Global economic competition has aroused many organizations to explore potential opportunities for enhancing the delivery of their products or services. This challenge has become apparent in the construction industry as well, with customers/partners demanding a better service and projects that meet their requirements more meticulously. This inclination towards transformation of construction operations has challenged the industry to become more efficient, integrated and more attractive, both in the eyes of society and its prospective. Furthermore, several government, industry or research-laboratory construction change initiatives have emerged in most developed countries. In parallel with, and to serve these initiatives there has been a rigorous effort, within the research and academic sector, to investigate and implement existing and emerging intelligent solutions that facilitate the improvements required to develop the construction industry. Worldwide, the construction industry is one of the main sectors that was estimated to reach an approximate US$5.5 trillion at the end of 2007. (Harmon 2003). The huge investment made in construction operations worldwide is representative of approximately 4.6% of gross domestic product expended at the national level (El-adaway, 2008). An industry of this size and budget, therefore, has across-the-board effects on the development and affluence of nations. The construction industry’s effects to the nation’s economy is, however, inhibited by an increasing number of problems that unfold and often intensify as projects progress. Research on applying intelligent systems (such as artificial intelligence techniques) to the management of construction industry projects started in the 1980s (Hua, 2008). These methods were, in some areas, compared to traditional simulation and statistical regression approaches to progress enhancements in areas of strive productivity, litigation, forecasting demands, cost estimations, optimizing construction site layout, cash flow prediction, and bidding in construction project. More notable, in a review of the use of intelligent systems solutions (e.g. artificial neural networks) in the field of construction management, cited the benefits of artificial intelligence techniques over mathematical and statistical models in situations where the process to be modelled is complex and where traditional models lack the ability to learn by themselves, generate solutions and respond adequately to highly quality, incomplete or previously unknown data. The scope and applicability of intelligent systems solutions clearly indicates that this area can and has addressed a multiplicity of organizational problems with the support of a large variety of techniques– which can help solve complex decision-making problems and provide solutions into them. In addition, the most developed artificial intelligence-based method nowadays in construction industry using BIM (Building Information Modelling. The results stated that artificial intelligence in the construction market is expected to show a growth of 350% or 450% in total in 2018 from $ 407.2 million to 2023. Building Information Modeling (BIM) is the most important reason to expect this increase in construction sector. With the use of BIM, companies are going to save 40% of a project for goods.


  • Benefits of Artificial Intelligence for Construction Industry

Today, the application of AI shows a rising trend in the use of computer processing to undertake tasks that would normally demand human intelligence. The technique allows for increased performance speeds coupled with a higher degree of accuracy. On construction sites, the use of robotics can assist in performing certain tasks such as welding, laying bricks and demolition. Increased spending on research and development can increase global use of robotics, with more autonomy and intelligence through the application of AI approaches. A key component of artificial intelligence is data. At various stages of the construction process, the data collected can be compared across various projects in different construction firms to offer valuable learning information for AI applications. AI methods can also be used in product quality control testing and design. And AI programs can deliver precise data and insights to ultimately assist contractors to optimize the safety of the work site. AI applications that utilize visual processing algorithms can be valuable tools for safety professionals pertaining to risk monitoring and prevention. Visuals from the construction site are assessed for safety hazards. Additionally, safety professionals have the opportunity to manage multiple projects without the need for on-site presence. Safety monitoring solutions using AI can scan bulk amounts of visual data, identifying staff and situations that fail to meet set safety requirements. AI can help reimagine how processes are completed. For example, with building information modeling (BIM) and with lessons learned across project teams, AI knowledge is contained in daily reports, schedules and more. At a time when massive amounts of data are created each day, AI is exposed to an endless resource to learn from and adapt to. The data generated in the construction industry is growing. Data gathered from images captured on security sensors, mobile devices and BIM offer a pool of information. While the construction sector adopts technology for capturing data, the issue rests with implementing a system that can manage all the captured data for construction professionals. Another challenge with AI is the inability of related applications to fully program themselves, resulting in cases of errors, incidents or project delays.

  • The aim of research

Although, the literature review connected to  Boussabaine in 1996 on artificial neural networks in the field of construction management and once more by Hua in 2008 on the applications of quantitative analysis techniques in construction economics and construction management (for both traditional and artificial intelligence techniques), this paper endeavor to broaden the scope of their reviews by further assessing the applicability of modern  types of artificial  intelligent systems in the construction industry. Explicitly in respect of Boussabaine’s and Hua’s conclusion for construction economics and construction management (where it only focused on artificial neural networks and quantitative analysis techniques), this research specifically to use BIM tools and modern artificial techniques aims to:

“identify the historical trends and current patterns in the use of modern types of artificial intelligent system and methods in the construction industry. These techniques and patterns will support in anticipating the future propensities in the use of upgraded intelligent systems in the construction industry”


Th source of building data and utilize with published research, books, written articles and thesis about use of Artificial Intelligence for Construction Industry shows the realistic decade work for modern part of construction using AI techniques and integrate AI tools to simulate real-time based BIM functions. A data collection is obtained to analyze the result of systematic reviews literature. In addition, to analyze a systematic literature review used 200 published articles and books. In addition, using Advanced Search and General search shows that 18600 published articles in General search tool and 2500 articles according to phrases “BIM, Artificial Intelligence, Construction Industry “articles between 2019-2020 years (google scholar). In the light of information above obtain a chart to show the importance of Artificial Intelligence for construction industry.

Research Findings and Discussion

The results of analyzed publications, thesis, books, conference papers and literature review the chart is obtained and discussed about the search results. The use of AI (Artificial Intelligence) for construction industry became challenging and obligatory. The BIM tools integrated by Artificial Intelligence based on real -time simulations, crashes, VR visual walking through project, cost estimation, oxygen-carbon dioxide change estimation by amount of income outcome people on projects and more. The chart given below shows the number of research articles, books and thesis, conference papers published by international studies.

Table 1. Scopus data calculation. The information for literature review is not enough to discuss about results.

Table 2. The chart above shows the articles, books, thesis, and conference papers written between 2017-2020 around last four years about improving Artificial intelligence and Construction Industry.

Table 3. The table above shows us the results from google scholar utilizing literature review via four years data and number of published articles. The graph presents the usage of AI and BIM in Construction Industry from 2016 to 2020.

Conclusion (Results and Suggestions)

To conclude, the paper aimed the current reveals the use of Artificial Intelligence in Construction Industry. The analyzed data obtained from Scopus database (Figure 1). The second step using published books, articles, final thesis and conference papers. All data calculated from 2016 to 2020 reading 24 papers and checking 122 articles. In addition, the development of using Artificial Intelligence and BIM in construction industry improving and become challenging for simpler results and analyzes. From all related topics of using AI and BIM in construction industry the data is calculated and shown in following graphs (Figure 2&3). The effective ways of using AI in construction industry gives a lot of ultimate benefits for cost management, time efficiency, safety management and BIM virtual crashes in construction projects. However, this paper aimed the use of Artificial Intelligence in Construction Industry by literature review, the future suggestions understanding AI and integration of AI into Architectural and Engineering programs to observe more detailed and accurate solutions.


Banihashemi Namini, S. G (2015). Developing an AI based decision making tool for energy optimization of Residential Buildings in BIM, 1-8.

Blanco, Jose Luiz, Steffen (2018). Artificial intelligence: Construction technology’s next frontier, 3-16.

Chien-Ho Ko, Ph.D. (2007). Dynamic Prediction of Project Success Using Artificial Intelligence, 3-5.

El-adaway, I.H. (2008). Construction dispute mitigation through multiagent based simulation and risk management modeling 95, 1-154.

G.B. Hua. (2008). The state of applications of quantitative analysis techniques to construction economics and management, 26(5), 485-497.

Harmon, K. M. J. (2003). ‘‘Dispute review boards and construction conflicts: Attitudes and opinions of construction industry members.’’ Ph.D. dissertation, Nova Southeastern University, Ft. Lauderdale, Fla, 3(4), 1-201.

Jack Goulding, Wafaa Nadim, Panagiotis Petridis. (2012). Construction industry offsite production: A virtual reality interactive training environment prototype, 12-115.

Jake Frankenfield, Gordon Scott (2007).  Investopedia Artificial Intelligence, 1-6.

Olugbenga Olawale Akinade. (2017).  BIM-based software for construction waste analytics using Artificial Intelligence Hybrid Models. 1-34.

Osama Moselhi, Tarek Hegazi, Paul Fazio (2008). Neutral Networks as tools in Construction, 8-25.2

J. Allwood (2014). Techniques and Applications of Expert Systems in The Construction Industry, 1-2.

Raghuvaran Chakkravarthy (2019). Artificial Intelligence for Construction Safety, 1-46.

Reference to the journal publication: Irani, Zahir, Kamal (2014). Intelligent Systems Research in the Construction Industry, 3- 29.

Salman Azhar, Ph.D. (2011).  Building Information Modeling (BIM): Trends, Benefits, Risks, and Challenges for the AEC Industry, 3-15.

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