Harnessing the Power of Artificial Intelligence in Construction

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Words by: Ayad Chammas

As the Construction industry stands at this technological intersection, questions arise: Can AI redefine its grasp of construction pathways, human resources, equipment, and project management?

In earlier days of construction, sharing project data was almost anecdotal, often based on “rules of thumb” or reliant on bulky yearly estimate books. These methods, though functional at the time, were neither dynamic nor real-time. With AI, the construction industry is no longer restricted to such static modes of operation. It offers an innovative lens, allowing for the harnessing of real-time, accurate data, a stark contrast from past practices.

Indeed, AI’s footprint in construction is rapidly expanding. A report suggests that the AI-driven construction market, which stood at $496.4 million in 2021, is poised to catapult to a staggering $8.6 billion by 2031.

Over the past five years, distinct AI-driven solutions have emerged as game changers in a few of the construction industry sectors such as safety, Quality Control, predictive maintenance, resource allocation, autonomous construction and real time project monitoring. The tangible AI-driven improvements in construction are undeniable. 

However, AI’s current limitations include replicating human soft skills, interpretive intelligence, and nuanced human relationships necessary for effective project management. That in addition to the legal challenges related to Data collection, ownership and transfer. Companies who wish to implement Ai, will have to ensure that they understand the legal risks around the use of Ai before they embark on large scale deployment. They need to be mindful of the possible legal implications and act wisely to mitigate them.   

“Digital literacy” is also key for the new construction professional workforce. And construction professionals need to adapt to a new reality where they will have tools at their disposal to help them make decisions via the use of data, therefore, it is important to learn how to define the set of data related to the problem they are looking to solve. In order to digitally allocate and interpret data.  Also, the behavior on site needs to be focused on tech enablement as Tech can help insurance companies to get more comfortable with performance of sites and a better assessment of risks embedded. 

From the author’s perspective, Ai has a long way to go, and we may not see Ai replacing humans in the industry as in other industries. Construction remains a human centric activity with a variety of specialties. In a way every project is unique, the industry is also a multi stakeholder industry where General Contractors, Engineers, Architects and customers each have their own set of targets and hence the gaps between each stakeholder needs to be bridged. We do not see Ai bridging those gaps in the near future and it will remain a human function for an unforeseen amount of time. The allure of AI’s potential to redefine construction methodologies and address age-old industry challenges is undeniably tantalizing. The imperative, however, remains: is the industry harnessing the right data streams to maximize AI’s potential?


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