AI in construction

Artificial Intelligence (AI) has found a footing across a number of industries, from retail to healthcare. However, it’s safe to say that its adoption in the global construction industry has been paced out and lukewarm. This can be associated to several reasons;  

  • The industry has always been slow in adapting to newer technologies owing to scepticism around unfamiliarity with the technology, and resistance to change 
  • There is also a general lack of awareness around how AI can potentially help the industry 
  • Investment in AI technology requires significant investments, which can be a challenge in a fragmented industry with many mid, small and large-sized companies taking up construction projects 
  • Data is sporadic in the industry, which makes it difficult to build data models, which is a necessity for AI to function effectively 
  • The industry is fraught with a number of regulations and restrictions, which can make it complex for companies to adopt AI technologies while being compliant with industry standards 

Having said that, the future looks promising. A survey by Research & Markets shows that although AI adoption has been lukewarm, it is likely to grow at a CAGR of 35.8% and touch USD 2.1 billion by 2025. Another study indicates that 81% of leaders in the construction industry will adopt AI in their business in the next five years. 

5 Areas Where AI can Impact the Construction Industry 

AI and related technologies have proven to reduce construction costs by 20% and shorten project timelines by 50%. So, there is evidence that these technologies can create a significant impact on the industry, which is already operating on high-risk, low-margin models.  

With this in mind, let’s look at the different ways construction can be beneficial for AI; 

Optimisation of design and planning 

Like we said earlier, AI works effectively on data-based AI models. It can analyse troves of data and generate insights on the most optimal ways to design and plan a project. This can include analysing weather patterns, zone regulations, analysing building codes and other elements that need to be looked into, to ensure safety, sustainability and functionality of a construction project. 

Monitor safety protocols and prevent construction related accidents 

According to the International Labour Organisation (ILO), construction workers account for 7% of the global workforce, but construction-related accidents are at a whooping 30%! 

AI can address these concerns in a significant way. Companies can use AI-based cameras and sensors to monitor the construction site in real-time and ensure that safety protocols and procedures are being followed. This can include ensuring that workers are wearing their safety equipment, adequate provision is being made in hazardous areas, and so on. This can ensure industry compliance and prevent untoward accidents on the construction site. 

Skansa’s massive reduction in construction safety incidents  

Skansa, a Sweden-based global construction industry implemented, a computer-vision software to analyse its construction site footage in real-time in the U.S. The software recognised and flagged off when workers were not wearing PPEs (Personal Protective Equipments), when there was any unsecured equipment lying around, or when an area was a potential hazard. The result? Using this software resulted in a 72% reduction in safety incidents. 

BIM tracking with AI  

AI has capabilities to collect and analyse data during the construction process and ensure that each aspect of the project is being implemented based on the requirements. 

In an earlier blog, we had looked at BIM (Building Information Modeling), and how it can aid the construction industry. With BIM, companies can build a 3D, 4D or 5D model of their project, and enable collaboration across stakeholders to tweak and improvise the design and project as and when required. Currently, the UK leads in adoption of BIM technologies, followed by Germany, Poland, France, and Croatia. 

To read more about BIM and its application in the industry, visit link

Optimise resources and minimise overheads 

With its data analysis capabilities, AI has the ability to enable administrators to manage resources optimally. For example, it can help stakeholders determine how many workers they need for the project, log workers into the system everyday, and shift resources across the site as needed. 

Increased accuracy of forecasted completion dates and predictive maintenance 

AI can prove effective in maintenance and forecasting as well. Once the project is completed, AI can collect data from building sensors to share insights into when a project is due for maintenance. Also known as predictive maintenance, this step can ensure that care is taken in advance, and costs and downtime are reduced with foresight. 

Current State of AI Adoption in the UK Construction Industry 

A Merit expert says, “The UK is not far behind in its adoption of AI technologies like smart sensors, computer vision technologies, predictive analytics, speech recognition and the like.” 

For example, companies in this region are already experimenting with autonomous heavy equipment, like using bulldozers and excavators remotely, with minimal human intervention.  

There is also adoption of robotics to perform tasks like brick laying and welding, and drone technology to monitor construction sites.  

Lastly, there are a number of startups rising in the construction technology space in the UK, to improve workflow productivity, ensure more efficient concrete management, to bring more sustainable practices in the industry by sourcing and utilising construction materials more efficiently, and so on. 

Merit’s Expertise in Data Harvesting & Data Analysis in Construction 

Our state-of-the-art data harvesting engine collects high-volume, industry-specific data at 4 times the speed, with 30% more accuracy than normal scrapers, at a lower cost and with the quality control from seasoned data experts.  

Our solutions help some of the world’s largest construction intelligence brands seamlessly deliver data and insights to their end customers, including:  

  • Delivering curated content from thousands of online documents or PDFs  
  • Aggregating millions of specialised, industry-specific data points  

To know more, visit: 

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