With everything going digital, the construction industry is too shifting from an analog to a digital future. In the face of stagnant productivity growth, increased competition, and the chronically skillful workforce scarcity, the use of machine learning and artificial intelligence (AI) applications have been assessed by the engineering and construction industry to transform their operations.
Likewise, in the past decade, the construction technology market has grown enormously. Ambitious start-ups and software developers have taken advantage of the technological potential for the traditionally underserved industrial sector by releasing products designed to simplify workflows throughout the construction process.
Furthermore, cloud applications and platforms for all-in-one building management have proliferated in recent years. As a result, AI and machine learning are the next major trend in construction technology.
Despite a slow initial adoption rate, building leaders are now becoming more interested in AI tech’s potential for transformation. For the next five years, tech adoption is expected to be steadily progressing as construction-centric applications and products continue to hit the market.
With AI technologies being integrated into their workflows, companies will have to face certain common challenges, including improving the data infrastructure. The quality and availability of data for successful results will depend on AI and machine-learning applications.
Building firms must combine all these data in one place and one format to use AI’s transformative capacities. The whole industry is only starting to tackle the problem by seeking ways of breaking down the institutional silos that provide isolated data to prevent effective analysis by AI and machine learning platforms.
Where AI Triumphs
An almost daily drift of information is generated over the life cycle of a construction project from RFPs to specifications, logs, and daily reports. At the present project, managers and building supervisors have no effective tools to grasp information quickly. Instead, they must read hundreds of documents and take up any piece of the page by page information. All the information takes a huge amount of time to be digested and understood.
With the implementation of AI, manual tasks can be automated repeatedly and reduce the time spent on mundane, but necessary administration. The general contractors may, by simplifying and reducing the administrative overhead, reassign the freed hours of man to other work that will help faster completion of projects.
The log of a project would traditionally be produced manually with hundreds of pages of a specific book and the compilation of a spreadsheet. This may take hundreds of hours for bigger projects with thousands of pages. The use of AI here for compilation and registration reduces a fraction of the time required.
The Project Itself
AI is also good for communication as this type of system can help direct engineers to implement and improve the performance of specific projects.
This would be based on past projects and on checking existing plans for the project design and implementation phases. By providing this information, engineers can take decisive decisions on the basis of the evidence they may not have beforehand.
Building sites can be daunting with huge structures and risky heights, but autonomous machinery can now be introduced to employees outside the vehicle. The vehicle can determine the safest route using sensors and GPS.
Getting AI Right
Although the use of AI technology will continue to increase in the construction industry, it needs to be promoted by factors. It must be remembered that the building industry is driven by people. This makes the studying curve essential for AI applications. There is limited time available to a building employee to learn how to use a product. The product needs to be quite intuitive and seamless to encourage adoption and use.
The problem for developers is to create AI apps that give the customer experience as much attention as they do to perform workflows. If the product is not perfect, builders will find it harder to integrate into their daily jobs and will most likely pass it onto their familiar, manual processes.
As these questions are resolved and the final barriers to broad AI technology are lifted, the construction sector will be prepared to make innovation and productivity even more effective. In five years’ time, the use of AI and machine learning technology will not be the exception in the industry.
