In its waning days, the Biden-Harris administration launched a campaign against so-called “digital price fixing,” targeting AI-driven pricing algorithms in industries like housing, groceries and hospitality. These cases seem more like political theater than sound legal reasoning — a last ditch effort to blame AI-powered tools rather than the administration’s economic policies for high inflation and rising consumer costs.

For example, the DOJ’s suit against the web-based property management solutions RealPage, which it expanded to landlords on Jan. 7, followed Biden’s public condemnation of rent pricing algorithms. This coordinated assault comes as Democrats like Sen. Elizabeth Warren decry AI pricing technologies while championing legislation to ban them.

Political grandstanding of this sort threatens American innovation and economic growth. The Trump Administration must stand against it. Incoming Attorney General Pam Bondi and Antitrust Division Head Gail Slater must rein in regulators to enable AI’s pro-competitive growth.

Stripped of their political implications, these cases pit the technological evolution of economically beneficial pricing strategies against overbearing extensions of antitrust law. Perhaps the most basic lesson in all of microeconomics is that the “price” of any item is set where supply meets demand. This theory is clearest in the case of commodities — items considered identical in all respects. The earliest commodities were agricultural products, like a bushel of wheat. When buyers and sellers negotiated each sale individually, some buyers and some sellers got great deals — but many sellers were left holding wheat they wanted to sell while many buyers went home hungry. Commodities exchanges improved the efficiency of those markets. Prices converged to the point that all sellers willing to take the price sold and all buyers willing to pay it bought.

Over time, the information revolution has allowed us to treat more items as commodities. Equity shares and securities trade almost exclusively on exchanges. A generation ago, airline pricing algorithms recognized that to most fliers, airline seats are effectively commodities. First eBay, then Amazon, standardized pricing on many items that are not commodities — but that many buyers treat as if they were. 

Many economists recognize that the overall effect of such “commodifications” has been to benefit consumers. The AI-driven algorithms that the Biden Administration and its allies attempted to squelch represent the next step in this centuries-long pro-consumer drift. To launch their attacks, they have had to contort antitrust law, attempting to push it beyond its role of protecting competition into a role in which its misapplication has long plagued the American economy: the stifling of innovation.

The attacks on rents and hotel rooms

The DOJ’s case against RealPage and the landlords who use it is flawed both factually and legally. RealPage holds itself out as a tool for property managers to optimize rents, based on market information gathered from users and external sources. In short, it allows property managers to improve the efficiency and accuracy of their pricing analyses — a step towards the commodification of rental units. Other products emerging as part of the AI wave perform similar tasks in other industries.

The Biden administration and its allies contorted this simple, pro-competitive, efficiency-enhancing function into an anticompetitive conspiracy to raise rents and harm tenants — implausibly painting RealPage as a monopolistic behemoth in the property management space. Even a quick glance at facts and law undercut these claims. For the future of both innovation and the American economy, it’s crucial to rein in these misguided attacks on pricing efficiency.

Under Section 1 of the Sherman Antitrust Act, collusion requires an intentional conspiracy to fix prices. RealPage’s algorithm represents but one more evolutionary step in data-drive price optimization. It neither mandates uniform adoption nor creates a conspiracy among users. Under standard antitrust metrics, RealPage’s market share — less than 8% of the property management industry — is far too small to exert monopolistic control or to restrict competition meaningfully. Furthermore, the presence of un-rented properties leaves consumers with many alternatives and undercuts claims of widespread harm.

District courts that have examined similar claims have reached the right conclusion. In Gibson v. Cendyn Group LLC, the plaintiffs alleged that Cendyn’s software inflated hotel room prices by coordinating pricing decisions among competitors. The court dismissed the case, noting that there was no evidence of an agreement, the timing of the software over a ten-year period rendered a coordinated price-fixing scheme implausible, the software relied on publicly available data and the absence of an obligation to follow Cendyn’s pricing suggestions demonstrated independent decision-making rather than coordinated conduct.

RealPage’s software draws upon public and anonymized data to recommend prices to independent landlords. Its recommendations may be higher or lower than those that the landlord had been contemplating, depending upon market conditions — and the landlord is under no obligation to accept them. In short, it’s a step towards commodification and the emergence of efficient exchange-like pricing.

Comparable flaws plague nearly all attacks on AI pricing, whether emanating from the Biden Administration, like-minded state AGs or class action lawyers. Where prices are rising, these efficiency-enhancing measures are simply not the cause.

The Biden Administration’s exit did not end the issue. Smelling blood, class-action lawyers and State AGs intend to extract a heavy price from the companies marketing these AI-driven pricing algorithms. Consumers and taxpayers will end up footing the bill. Take, for example, the appeal of Gibson — an effort to leverage laws against intentional, coordinated behavior to police incidental, innovation-driven changes to the market. 

Flawed arguments of this sort simply refuse to die; plaintiffs resurrect them to challenge nearly every technology-driven advance in pricing efficiency.  A decade ago, in In Re Text Messaging Antitrust Litigation, Judge Richard Posner reiterated that allegations of price fixing must go beyond mere possibility of collusion — they must also be plausible. Sheer speculation over the causes of circumstantial evidence like converging prices hardly suffice. If the DOJ wants to prosecute software users, it must do more than merely speculate about their incentives or declare selected observations suspicious. It must “reveal the smoking gun or bring to light additional circumstantial evidence” of actual, intentional, collusion. Improved algorithmic use of public information cannot possibly qualify. 

The broader stakes

The antitrust laws protect competition, not competitors. The decades in which the government deployed antitrust to squelch or control innovation proved deadly to the American economy — leading to the economic “malaise” President Carter identified in the 1970s. The Trump team must channel the Reagan Administration’s pro-innovation and pro-competition policies that powered America’s economic resurgence.