A 2016 study by the McKinsey Global Institute published in Harvard Business Review ranked the construction industry second to last in digital advancement, ahead of only “agriculture/hunting” of 22 industries studied. Yet as described in a subsequent McKinsey article, the increasing demand for infrastructure, shortage of skilled labor, and stakeholder demand for modernization are creating pressure for the $12 trillion architecture, engineering, and construction industry to join the digital transformation. While exciting advancements such as autonomous construction robots and drones tend to get more visibility, AI-powered knowledge management and data analytics are less visible – yet highly impactful – opportunities for the industry.
At a recent Society of American Military Engineers workshop on AI applications in the AEC industry, Tristan Randall, strategic projects executive at leading industry software developer Autodesk, explained, “AI isn’t just about driving efficiency, it’s about humans collaborating with AI to be more ambitious and creative to ultimately achieve better outcomes.”
Pooja Jain, senior vice president of strategic innovations at $3 billion global designer WSP, agreed. WSP’s building optimization tool, called daisy, balances the three main aspects of sustainability: daylight, operational carbon, and embodied carbon to maximize sustainability holistically. “Daisy enables us to bring sustainability to the forefront at the beginning of design rather than implementing it afterward,” Jain said.
Optioneering in construction phasing and engineering is also made possible by ALICE Technologies. Founded in 2015, ALICE “uses AI to minimize risk, reduce schedules, accelerate planning, and recover from schedule delays by simulating and optimizing the construction execution over millions of possible scenarios,” founder René Morkos, Ph.D., said.
AI-enabled data extraction and knowledge management promises to improve what has been estimated at up to 30% of a designer’s time spent looking for information. Global $8 billion design firm AECOM is addressing this through an internal proprietary system that searches previous documents as varied as proposals, drawings, white papers, and cost estimates while keeping them within the corporate boundary. “By curating our internal knowledge and providing references to source material and employee names, we are helping our employees be more efficient and avoid the ‘fear of the blank sheet of paper,’” executive vice president of national governments business Karl Jensen explained.
Knowledge management and AI can also benefit construction through inventory management and compliance during construction. Revaka is an AI-powered information search tool intended for construction. “Information search is time-consuming because there are too many apps to search through,” said co-founder Fauzan Reza Maulana. Revaka’s ACE, which stands for Assistant for Construction and Engineering, uses machine learning to collate data from specifications, drawings, scopes of work, and construction applications. “We can save a designer time by searching through all those sources to answer questions as specific as ‘what is the range of concrete costs that we’ve used on previous projects above $2 million in Illinois?’ complete with citations,” Maulana said. WSP uses computer vision to automate dull data entry work such as vendor invoices and concrete mix certifications, leading to an immense increase in efficiency and quality control.
Kaushal Diwan is the portfolio manager for WND Ventures and the executive sponsor of DPR’s Innovation and Research & Development Groups. DPR Construction is ranked the sixth largest contractor by Engineering News Record with $9 billion in annual revenue. DPR’s approach to AI-assisted data strategy operationalizes data by embedding analytics in decision-making. “We are leveraging historical data for analytics during data entry to move from lagging to leading and predictive analytics and better, more data-driven decisions,” Diwan said. One exciting outcome of pilot projects is DPR’s use of generative design for drywall. In partnership with startup Hypar, DPR’s pilots showed a remarkable reduction of material waste and increased safety by optimizing the layout of drywall, cutting it off-site, and shipping it to the job site with stacking plans for installation.
Unlike other technologies, “the barrier to entry is low; you don’t have to be a mega-firm to benefit from AI” said Sal Nodjomian, CEO of Matrix Design Group. “Small businesses can easily leverage AI technologies. The private sector moves faster than government, so industry must continue to lean forward and encourage our government partners to follow.” Workshop leader and U.S. Navy Civil Engineer Corps Lieutenant Commander Tim Dahms, U.S. Navy Civil Engineer Corps agreed. “We need to accelerate the pace of learning for the A/E/C industry and those performing work for the federal government to adopt new AI applications to reduce costs and improve schedule performance on the billions of dollars of design and construction contracts awarded each year,” he said.
Autodesk is at the forefront of the industry’s digital transformation, investing nearly $1.4B in research and development in 2023, or about 25% of its revenue. That research has resulted in capabilities like predictive analytics to help with decision-making in Autodesk Construction Cloud – the Autodesk Validation Tool that checks models against requirements – and the AutoCAD Macro Advisor. “The advisor is one way we are making suggestions for designers to improve their use of the software directly within the tool itself,” Randall said.
Jain described WSP’s key principles of AI initiation as embedding responsibility, including governance and AI policy; prioritizing people, including change management, upskilling, and training; and data strategy and governance, which includes data organization, protection for AI effectiveness, and risk avoidance. “In the absence of the right guardrails, leaders can sometimes put gates in place,” Jain said. “Businesses can say no to everything, but it doesn’t take the industry forward.”
“We tend to fear what we don’t understand,” Nodjomian concluded. “An effective way to reduce fear and increase the implementation of AI is through education and thoughtful discussion, which SAME provides.”
Disclosure: I moderated one of the panels at this workshop. Follow me on LinkedIn or check out my other columns here.
