Construction Industry Embraces Artificial Intelligence to Improve Efficiency and Accuracy
Antwerp, Belgium – In a sly swipe at the inflated hype surrounding artificial intelligence (AI), a billboard was placed at a construction site in Antwerp in June that read, “Hey ChatGPT, finish this building.” While AI won’t be assembling apartments or erecting stadiums any time soon, the construction industry is rapidly embracing the technology to improve project performance and expedite timelines.
Traditionally known for clipboards and Excel spreadsheets, the construction industry is now incorporating digital tools like drones, cameras, mobile apps, and even robots to track and map real-time progress on job sites. This allows builders and contractors to improve scheduling, reduce waste, and enhance overall productivity.
James Swanston, CEO of Voyage Control, a company that develops project management software for construction sites, explains that it’s not about robots building skyscrapers, but rather the ability to gather and utilize the necessary data effectively. The industry has long been considered a digital laggard, but architects have been using digital tools for designing projects and creating blueprints for years.
Helmet-mounted cameras are now capturing site footage to manage crew and material arrivals, while precise sensors detect any discrepancies between project blueprints and actual construction, ensuring accuracy. AI is also being utilized in buying and selling real estate, as JLL, a global broker, recently introduced its own chatbot to provide insights to clients.
The construction industry, despite being the largest in terms of dollar spent, has been the least productive in terms of technological adoption and productivity gains. David Jason Gerber, a professor at the University of Southern California, points out that the industry is ripe for improvement in accuracy, speed, and efficiency to reduce costs and waste.
However, incorporating AI technology into construction faces several challenges, including concerns about accuracy and hallucinations where systems provide incorrect or nonsensical answers. Additionally, data collection is complex due to the varying nature of each construction project, with different topography, local regulations, and contractor teams coming together for each development.
Despite these challenges, startups and investors see vast opportunities for improvement. Machine learning models, which analyze vast amounts of data to identify patterns and predict project progress, hold promise for enhancing overall performance. The pandemic has also propelled construction firms to adopt more digital tools, accelerating technological developments in the industry.
One example is nPlan, a construction consulting firm that uses complex algorithms to map progress in large infrastructure projects and avoid mistakes or supply gaps. By utilizing machine learning systems trained on a database of over 740,000 projects, nPlan seeks to create detailed, real-time project maps to save costs.
Start-ups like Buildots in Israel provide project management guidance via wearable cameras that analyze building progress. Through the analysis of 64 international building sites, Buildots discovered that only 46% of the average work site is being utilized at any given time, highlighting inefficiencies. Their technology aims to improve productivity through enhanced organization and scheduling.
Construction firms are also investing heavily in their own in-house technologies. For instance, Avison Young’s Project Management Services division claims its proprietary software and management programs can cut development time by an average of 20 percent. Suffolk, a large construction firm based in Boston, has a team of 30 data analysts collecting and analyzing job site information, leading to improved progress tracking and accident prediction.
While there is trepidation about AI’s accuracy and safety in an industry where safety is crucial, the reported ability to work faster and cheaper continues to attract interest. Dusty Robotics, a tech firm in California, develops autonomous devices for tracing building blueprints on construction sites, replacing labor-intensive manual methods. Rather than replacing workers, these technologies allow for easier, more efficient work, especially for attracting younger workers who are familiar with modern tools.
The potential for reducing risk is also a promising aspect of AI adoption in construction. The ability to keep projects on task and improve organization has led to cheaper insurance options. Start-ups like Shepherd use construction data to provide contractors with more affordable premiums, while Wint, an Israeli start-up, uses sensors and algorithms to prevent water damage on construction sites, cutting loss rates by up to 90%.
Justin Levine, CEO and co-founder of Shepherd, emphasizes that insurance costs can make a significant difference in project financing. By leveraging AI and technology, the construction industry aims to become more productive, efficient, and cost-effective while improving overall project outcomes.