As construction workers complete tasks on site, artificial intelligence analyzes data from wearable biosensors and environmental monitors for early signs of fatigue and heat stress; and when it detects them, sends personalized, real-time alerts before symptoms start.
This heat stress early-warning system — developed by the Safety Automation and Visualization Environment Laboratory, or SAVE Lab, in collaboration with Achen-Gardner Construction, Willmeng Construction and CHASSE Building Team — helps ensure construction workers go home safe and healthy at the end of the day, says Siyuan Song, an associate professor of construction engineering, who leads the lab at the Ira A. Fulton Schools of Engineering at Arizona State University.
It’s one way researchers in the School of Sustainable Engineering and the Built Environment use AI to create solutions for challenges in the construction industry. They are also using AI to develop human-centered construction technologies, study how workers learn with virtual reality, improve safety training through eye tracking and analyze complex construction data.
How researchers use AI to improve construction
Song’s research focuses on one of AI’s most immediate applications in construction: protecting workers from heat stress, psychological strain and physical fatigue.
“Each of these is difficult to observe until it becomes dangerous, and that is exactly where AI helps,” she says. “It monitors conditions no human observer could track, recognizes that two construction workers in identical conditions can respond differently and shifts safety management from reacting to incidents toward preventing them.”
SAVE Lab researchers create immersive virtual-reality safety training environments to analyze how workers learn and respond to hazards. They also use large language models to analyze accident reports, study the impact of extreme weather and evaluate safety training.
Another example is work done in the Pooladvand Research Group, led by Shiva Pooladvand, an assistant professor of civil and construction engineering and management at ASU. The group is developing the next generation of human-centered construction technologies by connecting construction engineering, robotics, computer science, cognitive science, human factors and immersive environments such as virtual reality.
“I use AI to analyze multimodal data captured from workers and the environment to identify patterns related to workers’ decision-making, behavior and safety to anticipate unsafe working conditions or identify workers who may be at risk,” Pooladvand says. “This enables more personalized interventions to enhance safety, automation and productivity.”
At the Construction Workforce and Technology Lab, Ricardo Eiris, an assistant professor of construction management, uses AI to improve construction education and workforce training through emerging technologies. His research combines AI with human-computer interaction, virtual reality, digital twins and drones to help people better understand construction sites and learn in settings that go beyond the limits of physical classrooms or jobsites.
“I use AI as a tool for expanding how people learn, train and interact with complex built environments,” Eiris says. “Rather than treating AI as a stand-alone technology, I leverage it to support immersive experiences, model human behavior and create more realistic, responsive systems that can improve learner performance in construction.”
Kenn Sullivan, a professor of construction management, uses AI to assist with statistical modeling, visualization and testing different analytical approaches. He also uses it to document his research team’s methods, decisions and workflows to share with the next student who joins the team.
Construction leaders put AI to work
The same emphasis on practical applications carried into the AI for Construction 2026 Contractors Summit, where more than 90 construction professionals exchanged examples of how they are using AI and discussed challenges preventing wider adoption.
Hosted by the Del E. Webb School of Construction and the new AI in Construction Consortium, the summit brought together contractors, construction companies, faculty members and students.
“The contractors summit and the proposed industry consortium originated from our executive council as opportunities for construction companies, technology providers, faculty members and students to learn from one another in a collaborative environment,” says Tim Becker, programs chair of the Del E. Webb School of Construction.
At the summit, construction leaders expressed how they find value by applying AI in agent-based workflows for specific tasks in business development, virtual design and construction, safety, visual analysis, scanning and project controls. Speakers described applications in field verification, financial forecasting and workforce training while identifying persistent challenges such as fragmented data, privacy concerns and the need to demonstrate a return on investment.
At Okland Construction, Senior Virtual Design and Construction Manager Hamilton Ramirez says the company uses Siteaware to overlay drone imagery onto 2D floor plans to identify deviations in sleeves and other components, preventing the need to do rework on site. They also use rented robot dogs from BostonDynamics, equipped with FieldAI, to take laser scans and 360-degree photos inside buildings where drones cannot go to check for missing work and other issues.
Other speakers demonstrated how AI can improve work beyond the jobsite. Tatjana Fosdick, data innovation manager at GCON Inc., described collaborating with colleagues in finance and analytics to use AI to create a capital forecasting process. The new process can be updated in 30 minutes each month, replacing a time-intensive, manually updated, 20-tab spreadsheet.
At Sundt Construction, Director of Innovation Eric Cylwik and his team built a custom GPT that helps interns identify unfamiliar equipment from jobsite photographs. Beyond supplying an answer, the tool suggests questions interns can ask their superintendents, helping them learn while building relationships with experienced professionals.
The summit provided ASU researchers insight into the problems construction companies are trying to solve, while giving industry professionals an opportunity to connect with researchers and future talent. Additional professional education programs and knowledge-sharing events are being planned.
Preparing the next generation of construction leaders
As AI changes how construction work is performed, faculty members guide students’ responsible use of AI in their courses, preparing them to apply it effectively throughout their careers as the industry evolves.
Over nine months, AI tools went from being able to complete almost none of Sullivan’s class assignments to completing about 50% to 60% of them. This rapid shift led him to reconsider what he teaches, how he assesses learning, what he expects students to do independently and to redesign his curriculum.
In his AI in Construction course, students conduct data analysis, develop custom AI skills and agent-based workflows, build working software applications and create portfolio websites to showcase the solutions to problems they tried to solve.
“By the end of the course, they have something tangible to show a potential employer,” Sullivan says.
Learning to build with AI is only part of the preparation. Students must also understand its limitations and know how to evaluate its output.
“In class, we discuss examples of AI being used in actual construction projects, how it’s applied and its pros and cons,” Pooladvand says.
Students learn to verify AI-generated information and combine it with engineering judgment, she says.
That’s why a strong foundation in construction methods, estimating, scheduling, safety, contracts and project management is essential for students.
“In many ways, AI makes that foundational knowledge even more important,” Sullivan says.
In Song’s Advanced Construction Safety Engineering and Management course, students learn how computer vision, wearable sensing, machine learning and virtual reality reshape safety practice. SAVE Lab’s virtual reality-supported safety training and jobsite sensing deployments become case studies and provide hands-on experiences for students.
“Responsible AI use is essential in our field for a simple reason: In construction, decisions have physical consequences,” Song says. “An unverified AI output in an essay is an academic problem. An unverified AI output in a safety plan, cost estimate or schedule is a potential hazard to people and projects.”
