Construction companies are increasingly turning to Artificial Intelligence to streamline estimating, manage submittals and Requests for Information, and assist with contract review. While the technology is often touted for driving efficiency and cost savings, a new legal challenge highlights a potential downside: higher costs for materials, equipment, and labor as algorithmic pricing spreads across the industry.
Earlier this year, several construction companies filed class-action antitrust lawsuits against the largest equipment rental providers in the United States, alleging a conspiracy to artificially inflate equipment rental prices. The suits have been consolidated as In re Construction Equipment Antitrust Litigation (Case No. 1:25-cv-03487) in the United States District Court for the Northern District of Illinois. At the center of the case is the “Rouse Rental Insights” program, which collects real-time, confidential pricing data from invoices and uses Artificial Intelligence to aggregate information and generate a daily recommended “RRI Price” for each class and category of equipment, factoring in seasonal shifts and market conditions.
Plaintiffs contend that by sharing confidential pricing data with the RRI tool and agreeing to use its Artificial Intelligence driven price recommendations, the rental providers have effectively conspired to raise rates. They argue the alleged price increases are especially harmful because the market has relatively few large providers, purchasing equipment is uneconomical for most contractors compared to renting, and demand for rentals is not highly sensitive to price changes. The complaint includes a chart showing substantial growth in U.S. construction equipment rental revenue since 1997, which plaintiffs attribute in part to the alleged conspiracy.
The litigation remains ongoing. Its resolution could influence how Artificial Intelligence is used in construction markets beyond equipment rentals. If rental companies successfully defend the RRI approach, other industry participants may adopt similar algorithmic pricing models, potentially resulting in higher prices in additional segments of the construction industry.
