The industry has accumulated decades’ worth of data that, with the help of AI-driven analysis, could be tapped to boost construction productivity, prevent schedule overruns, improve cost-effectiveness, bridge labor gaps, and reduce risks. By Michele Morgan, SAP The construction industry accounts for 14.2% of global GDP .
But as other industries have steadily grown their productivity in the last few decades, construction productivity has been stuck in the mud. Between 1970 and 2020, as aggregate productivity for the U.S.
economy doubled, labor productivity in the U.S. construction sector declined an average of 1% a year .
Some estimates put this at $30 billion to $40 billion in losses. Meanwhile, schedule and cost overruns are the norm. Just 8.
5% of megaprojects ($1 billion or more) meet or exceed their time and budget expectations, according to one study . On top of all of that, skilled labor is growing scarce as older workers leave the industry and fewer young people enter its ranks. While other industries have embraced the digital world to improve efficiency and performance, construction has historically been slow to adopt technology, says Dr.
David Jason Gerber, director of the M.S. in Advanced Design and Construction program at University of Southern California.
It’s not hard to understand why. After all, you can’t digitize concrete. Construction is a low-margin, materials-based, physical labor-intensive field.
But AI could spur construction’s digital transformati.