New technologies, new paradigms, and the use of artificial intelligence have made the job of regulators in the antitrust arena more difficult. These challenges require expertise at the intersection of antitrust and technology risk to avoid leading regulators astray from promoting competition, which is the fundamental purpose of antitrust laws.

　　Those issues have come to a head in many unexpected areas.Following the COVID-19 pandemic, rents began to skyrocket, increasing over 14 percent in 2022 alone. Some states saw increases of over 20 percent. The Biden administration announced a nationwide effort to “lower housing costs.” While rent control schemes drew the biggest headlines, antitrust enforcers also decided to take action in the housing and rental market.

　　The Department of Justices Antitrust Division recently reported that they opened a criminal investigation into RealPage—a property management company—and the property owners who use RealPage’s algorithm-based software designed to help determine ideal rental price-points. This raises serious questions about how the nation’s antitrust cops view technology-based market innovations. This criminal investigation follows at least three statements of interest filed by the DOJ and Federal Trade Commission in the past year supporting private class action plaintiffs bringing civil claims that pricing algorithms amounted to illegal collusion. The FTC now seems to be turning its interest to algorithmically-driven dynamic pricing, or the practice of adjusting prices based on demand and other factors to make personalized price offers.

　　The development of AI has become a Rorschach test for politicians and policymakers. Some see it as positive, a sign of advancing technology coupled with the belief it will benefit human progress. Others see something more sinister: fear of the unknown, concerns about the concentration of power in certain corners of the tech industry, or simply the desire for government involvement and regulations as the technology is in its infancy. These debates have morphed into accusations that AI will lead to economic inequity and anticompetitive behavior.

　　Perhaps these fears have led to current regulatory pushes. By itself, the use of AI algorithms does not necessarily reduce competition, nor is it the type of price fixing or other collusive behavior that antitrust laws typically prohibit. Software companies in the property management industry gather and analyze data points on current market conditions and use a proprietary algorithm to suggest an optimal rental price to the user. The property owner is free to accept or reject the proposed price, and of course, a renter is not obligated to accept the price.

　　Property owners—like nearly all retail businesses—have collected and analyzed data from the earliest days of commerce.The utilization of mathematical or algorithmic models to do what was once done using pen and paper is also not a new phenomenon. Since at least the 1980s, airlines have used dynamic pricing models to set fares based on demand, time, and availability. These strategies were adopted as a consequence of deregulation and low-cost competitors, and made air travel more competitive for consumers. More recently, hotels and ride-hailing apps have employed differential pricing.The private sector is not alone in adopting such pricing structures. In many urban areas, including in the Virginia suburbs of Washington, DC, government-operated toll roads employ “congestion pricing,” which sets toll costs based on supply and demand.

　　If not careful, the DOJ and FTC risk misapplying antitrust laws by bringing actions against dynamic pricing models that are otherwise normal. Even if chalked up to the growing calls to move away from the consumer welfare standard (which ensures that antitrust enforcement actions come from concern over consumer harms, and not other improper considerations), the antitrust regulators appear to be taking issue with the fact that artificial intelligence allows larger amounts of data to be analyzed faster and more efficiently. But that does not necessarily imply an antitrust violation. To plausibly claim an antitrust violation, the Sherman Act requires three elements: 1) a contract or conspiracy among two or more entities; 2) that unreasonably restrains trade; and 3) affects interstate commerce.

　　When done properly, algorithmic AI technology should be seen as a shift towards smarter, more efficient market mechanisms, not as a tool of anti-competitive behavior.

　　Using AI software to examine data and market forces to suggest pricing does not imply the users of the software have entered into an agreement, contract, or conspiracy to fix prices. Far from being anticompetitive, algorithmic pricing represents a natural evolution of market efficiency and innovation. By automating price optimization, software companies empower their users to adapt to market changes swiftly, fostering greater transparency and efficiency.

　　Although AI represents new frontiers, the classic antitrust cases may provide answers for why current fears are overblown.Nearly one hundred years ago, as mass retail of consumer goods took the nation by storm, the Supreme Court found in United States v. Colgate that a manufacturer’s announcement of a resale price without coercion is not a violation of antitrust laws. Users of this property management AI software (and similar software companies in other sectors) are similarly not forced, coerced, or pressured to use its suggestive pricing structure.

　　More recently, in Ohio v. American Express, with credit cards replacing cash transactions (often to the understandable ire of some merchants) the Supreme Court emphasized the need to consider the broader market context, suggesting that superficial analyses of technological impacts can lead to flawed antitrust conclusions. The court held that an “anticompetitive effect” must not merely bring negative impacts on one component of a market but also prove harmful to the competitive process. The DOJ and FTC would be well-served to remember this today.

　　In its statement of interest in a rent-pricing antitrust case, the DOJ stated that “given the amount of information an algorithm can access and digest, this new frontier poses an even greater anti-competitive threat than the last.” But hotels, airlines, car rental companies, and even government agencies routinely utilize similar algorithms to optimize prices. The government fails to explain what is fundamentally different here and why the property managers’ utilization of algorithmic software warrants antitrust intervention.

　　The stakes are high here. If the DOJ and FTC’s probes gain traction, will a cottage industry of lawsuits against similar AI software systems in other politically sensitive sectors quickly arise?

　　Misguided action from the FTC and DOJ on this case risks setting a worrying precedent that could discourage innovation in other sectors where algorithmic pricing is prevalent. If the mere use of such technology invites antitrust scrutiny, companies across various industries may hesitate to adopt or develop similar solutions, fearing regulatory reprisal and burdensome litigation. This could impede progress and limit the potential benefits that algorithmic pricing can offer consumers and businesses, hindering the growth of a dynamic and competitive market.

　　Rather than constraining these companies out of fear, the DOJ and FTC should encourage healthy competition and innovation through implementing clear, predictable regulatory frameworks. Doing so will allow businesses to understand the rules of the game.

　　The DOJ and FTC should also continue to focus on hiring attorneys with STEM degrees and broad tech policy experience. Making these hires will reassure the public that the government is focusing its antitrust efforts on truly bad actors—not on those who merely employ new ways of conducting established business. Consumers will continue to benefit from these advancements in innovation while remaining safeguarded against genuine anti-competitive behavior that may arise from future companies that use this nascent technology.

　　When done properly, algorithmic AI technology should be seen as a shift towards smarter, more efficient market mechanisms, not as a tool of anti-competitive behavior. It would be a shame to see the DOJ and FTC act in a manner, even if well-intentioned or beneficial in the short term, that impedes the growth of these markets for the decades to come.