Build Back Botter: What Artificial Intelligence Means for the Construction Workplace

“Hey Chat GPT, finish this building.” This dare, written on a billboard that went viral last year, captures a truth and a stereotype about the world of construction. The truth is that the construction industry will, for the foreseeable future, rely primarily on human intelligence and manpower to convert raw material into buildings and highways. Although the computational power of artificial intelligence (AI) models is doubling every four to nine months1 and thus outperforming Moore’s Law,2 no one expects robots and algorithms to build the next Burj Khalifa. The stereotype is that the construction industry is hidebound, ever the domain of manual labor and diesel-powered hydraulics, instead of cutting-edge technology. But, as it has done with all major sectors of the economy, AI is starting to transform the construction industry, which accounts for more than $1 trillion in annual GDP and employs more than eight million persons.

Despite the industry’s tendency to move slowly when adopting new technologies, construction companies are increasingly integrating advanced AI systems into their operational blueprint. Indeed, AI is now used in every phase of the project lifecycle, from design and planning to supply chain and project management and quality control. Some upsides of AI in an industry daunted by hefty spending and long delays are cost efficiency and sped-up timetables for project completion. For construction workers, AI offers advantages such as improved on-the-job training, the creation of new jobs to facilitate the use of AI, and sophisticated tools that will aid workers in their performance and decision-making. Significantly, AI also promises to improve worker safety and make the industry more accessible for workers with disabilities.

Uses of AI in Improving Worker Safety

Construction ranks among the most hazardous industries for workers. In the United States, there were more than 1,000 construction-related fatalities annually from 2019 to 2022. The Occupational Safety and Health Administration (OSHA), the U.S. Department of Labor agency responsible for enforcing workplace health and safety regulations, classifies the four major construction hazards as falls, caught-in or caught-between hazards (such as trench collapses), struck-by hazards, and electrocution. Under the federal Occupational Safety and Health Act (OSH Act), employers have a duty to monitor worksites and prevent hazardous conditions from developing. As it does with other major industry sectors, OSHA issues specific regulations targeting the safety risks unique to the construction sector. Despite regulatory oversight and employers’ own efforts to minimize hazards, a combination of human error, noncompliance (whether willful or negligent), and other factors open the door for costly and tragic mishaps resulting in injury, death, and legal action against employers.

AI serves to mitigate some such risks, which have long been part and parcel of the construction workplace, reducing the likelihood workers will be harmed on the job. As employees enter a worksite, AI-powered control systems, armed with computer vision and image analysis algorithms, can determine whether workers are authorized to access the specific site, and can scan their safety attire for compliance with personal protective equipment (PPE) standards set by OSHA. Whereas safety professionals used to rely solely on walkarounds and inspections to perform spot checks, AI-powered cameras placed around a worksite can now continually monitor conditions, searching for hazards and detecting noncompliance with health and safety standards. Upon detecting a violation, these systems alert safety managers to take preemptive remedial measures. In addition to AI’s role in ensuring that workers comply with safety standards, AI is also used to ensure heavy machinery is functioning properly. For instance, predictive maintenance systems driven by AI assess the condition of equipment and gauge the need for maintenance, thereby preventing failures that can cause worker injury.

Another important AI-based development is the proliferation of wearable safety devices shown to be effective in preventing falls, assessing fatigue, monitoring workers’ mental status, and mitigating musculoskeletal injuries and disorders. Wearables include smart hard hats that detect worker fatigue and overheating (prompting the employee to take a break); proximity sensors that can reduce the incidence of struck-by hazards; and smart monitors that can measure air quality (such as a dangerous concentration of silica dust), screen for noise levels that risk hearing loss, and detect when a worker has made a dangerous movement (e.g., of the sort that can lead to a fall).

Uses of AI in Improving Worker Accessibility

The industry can also benefit from AI-enabled advances that assist workers with disabilities. When it enacted the Americans with Disabilities Act (ADA) in 1990, Congress intended to open everyday commercial, economic, and social opportunities to disabled persons. Under certain circumstances, the ADA requires employers to provide a reasonable accommodation to applicants and employees with disabilities to allow them to perform the essential functions of a job.

Due to its often-strenuous physical demands, construction work presents unique challenges for workers covered by the ADA, and today, only around six percent of persons employed in construction report having a disability. AI stands to broaden employment opportunities for construction workers with disabilities by permitting them to assume functions they could not previously have performed or permit them to enter the trade in the first place. The ability of some wearable technologies to supplement mobility and muscle function, such as exoskeleton suits and robotic arms, may lower employment barriers for those with physical impairments. Moreover, digital applications such as Building Information Modeling software, virtual and augmented reality tools, and voice user interfaces, may hold untapped potential to expand both opportunities for disabled persons and the universe of reasonable accommodations that employers will be able to provide. The cost of the AI technology at issue is relevant, however, as the law limits reasonable accommodations to those accommodations that do not impose an undue hardship on a business’s operation. The high costs associated with robotics, for instance, may limit AI’s short-term impact on efforts to increase accessibility to employment opportunities in construction.

When integrating AI into their business models, construction companies should carefully weigh the costs and benefits of this technology. As with any new technology, there are attendant risks, including with respect to privacy, discrimination, cybersecurity and other workplace concerns. But in its promise to enhance safety in an industry that suffers from a high rate of fatalities and injuries, as well as its capacity to lower barriers to participation by persons with disabilities, AI is pointing the way to the future of construction.

See Footnotes

2 Moore’s Law is the observation that the number of transistors on an integrated circuit will double every two years with minimal rise in cost.  It is a widely used benchmark for the speed of technological evolution and performance improvements.  See

Information contained in this publication is intended for informational purposes only and does not constitute legal advice or opinion, nor is it a substitute for the professional judgment of an attorney.