As government scrutiny of algorithmic pricing grows, antitrust regulators should be careful not to confuse innovation with collusion. Pricing algorithms, which build on decades of retail practices like price parity clauses and price-matching programs, shape competition in industries from travel to retail, helping firms respond to changing demand, increase efficiency, and offer consumers better deals. Yet enforcement theories that treat these tools as inherently suspicious could do more harm than good.

Price Parity Is a Longstanding Retail Model

Algorithmic pricing has existed in principle for decades through traditional price parity clauses, which are practices that keep prices consistent across different channels. Algorithmic pricing builds on that same logic but applies it with greater speed and precision, allowing retailers to maintain competitive prices as market data changes. The rise of omnichanneling has further reinforced price parity by pressuring retailers to keep pricing consistent across online and brick-and-mortar locations. Algorithms make the long-standing practice of parity more precise and adaptable.

A recent example from Target illustrates that price parity mechanisms, and by extension algorithmic pricing, do not lead to anticompetitive outcomes.

— According to NetChoice, Target ended its twelve-year price-matching program with competitors like Amazon and Walmart because matching lower prices cut into its profits. This highlights that price matching, even when pursued manually, can be unsustainable in a highly competitive market where rival retailers continuously lower prices.

The fact that manual price matching became unsustainable underscores that the challenge was the pace of competition, and that algorithms are simply tools that help firms respond to those same market pressures more efficiently.

Algorithms Are Tools, Not Cartels

Contrary to misconceptions, the use of pricing algorithms is not the same as price fixing, it is an extension of price parity. Critics often assume that if companies employ algorithms to help offer tailored pricing for consumers, they must be conspiring. In reality, these tools are designed to process information more efficiently. Industries have always set prices in response to supply, demand, costs, and competition—modern tools just allow for these time-tested practices to be done more efficiently. When firms compete vigorously, algorithms tend to increase responsiveness and sharpen price competition.

— As economists at the Mercatus Center pointed out, policymakers risk blaming the technology for dynamics that reflect normal market behavior. Benefits to algorithmic pricing include “allocative efficiency and intensified price competition. Additionally, the negative effects associated with algorithmic pricing tools are wrongly attributed to the tools themselves, when in fact […] they are the result of the broader competitive context the tools are used within.”

That insight is echoed by legal scholars who caution against inflating speculative risks into regulatory overreach. Thibault Schrepel, writing in the Harvard Journal of Law & Technology Digest, argued that fears of runaway algorithmic collusion are overstated and unsupported by evidence.

— He wrote that “algorithmic collusion is not yet quantified, and even if it was, it would not raise fundamental problems for antitrust and competition law.”

Algorithms can promote price transparency, market responsiveness, and lower prices when markets remain open. Overreaching regulation by the Federal Trade Commission (FTC) and the states risks mistaking competitive adaptation for collusion and punishing the innovations that make pricing more efficient, benefiting both businesses and consumers alike.

Marketplaces Show Algorithms Encourage Competition

Just as price parity practices showed that competition drives innovation in retail, digital marketplaces reveal how algorithmic tools extend that competition across millions of sellers. These systems help small businesses adjust prices dynamically and meet consumer demand, lowering barriers by enabling all sellers to compete in real time.

Amazon’s Merchant Fulfilled Network provides an example of how accessible algorithmic pricing has become, allowing sellers to choose from a variety of pricing tools and fulfillment models to compete on equal footing.

— According to Marketplace Pulse, third-party sellers now account for more than 62 percent of all items sold on Amazon, a record high in late 2024 as independent merchants increasingly use algorithmic pricing to stay competitive across the platform.

Open marketplaces allow thousands of sellers to compete simultaneously on price, speed, and service, pushing everyone to perform better. Heavy-handed enforcement that limits these tools would weaken competition by reducing seller participation and depriving consumers of the lower prices and greater choice that algorithmic systems help deliver.

Enforcement Without Evidence Could Backfire

Algorithms respond to the data and incentives around them. Economic research shows that algorithmic tools can influence prices under certain market conditions, but there is no evidence that they inherently lead to collusion or persistent overpricing. What matters is the market context, including the level of competition, the quality of data inputs, and how frequently algorithms update their prices, rather than the inherent use of algorithmic systems.

— In the American Bar Association’s Antitrust Magazine, researchers wrote that “[r]ecent economic research finds that pricing algorithms can theoretically sustain supracompetitive prices under some circumstances. However, this nascent strand of the literature does not determine conclusively that the use of algorithms always leads to elevated prices, so determining whether prices are indeed higher than they should be (based on a competitive benchmark) still requires a case-by-case analysis.”

Algorithms respond to the data provided to them by firms and they are now deeply embedded in industries across the economy. CCIA has warned that new, sweeping regulation would undermine these procompetitive benefits and stifle innovation that benefits consumers.

— “AI algorithms platforms can foster competition by helping companies maximize profits and provide better value to consumers. […] existing competition laws are best equipped to address these invariably nuanced, case-specific issues while avoiding the inadvertent stifling of pro-competitive, pro-consumer benefits.”

Regulators Should Focus On Competition, Not Theoretical Harms

Algorithms are the latest step in a long tradition of innovation that makes markets more efficient and transparent. Like price parity clauses before them, algorithmic pricing tools help businesses respond to real-time market conditions and consumer demand. Policymakers and regulators should recognize that these tools operate within competitive marketplaces often open to thousands of participants, not dominated by a few firms. Treating them as inherently suspect risks punishing efficiency and undermining the very competition antitrust law seeks to protect. 

Heavy-handed antitrust enforcement risks stifling innovation and competition, and may lead to slower economic growth that picks winners and losers. The smartest way to keep markets competitive is to let competition, not burdensome regulation, do the work.