Prohibit Surveillance Price & Wage Setting

HB26-1210 addresses a relatively new and contested economic phenomenon: the use of algorithmic pricing software that aggregates real-time competitor data and uses it to recommend or automatically set prices and wages. Critics argue this practice functions as de facto price-fixing or wage-fixing without requiring competitors to communicate directly, thereby evading traditional antitrust enforcement. The bill targets both the businesses that use such tools and the third-party vendors that provide them, creating liability on multiple levels of the commercial chain.

The constitutional basis for the bill rests on Colorado's broad police powers to regulate commerce within its borders and its authority to supplement federal antitrust law under the Sherman and Clayton Acts, provided state law does not conflict with federal statutes. Colorado joins a small but growing number of states exploring similar legislation, as federal regulators — including the FTC and DOJ — have begun scrutinizing algorithmic collusion but have not yet enacted comprehensive rules. The bill reflects a state-level effort to move faster than federal action.

Fiscally, the bill's impact on state revenues is likely modest. Enforcement costs would fall on the Colorado Attorney General's office. However, broader economic effects could be significant: proponents argue prices for consumers and wages for workers could rise if anti-competitive coordination is disrupted, while opponents argue compliance costs and reduced data access could disadvantage Colorado businesses relative to competitors in other states.

Historically, price-fixing and wage-fixing have been per se violations of federal antitrust law since the early 20th century. The novel question is whether algorithmic tools that achieve the same economic outcome through indirect data sharing constitute illegal coordination. Courts have not definitively settled this, and the bill anticipates that ambiguity by creating a state-level prohibition that does not require proof of explicit agreement — only the use of a covered algorithmic tool.

Stakeholders affected include retail businesses, landlords, employers, software vendors offering pricing analytics, workers in wage-suppressed industries, and consumers who may pay inflated prices. The real estate rental market — where algorithmic pricing tools like RealPage have drawn federal scrutiny — is a particularly prominent flashpoint. Labor markets in gig economy, hospitality, and healthcare sectors are also heavily implicated.

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Colorado's HB26-1210, signed by the Speaker of the House, makes it unlawful for businesses to use algorithmic software tools that gather competitors' pricing or wage data and use that information to set their own prices or employee pay. The law targets so-called 'surveillance pricing' platforms — third-party software services that effectively allow rival companies to coordinate market behavior through shared data without ever speaking directly. Both the businesses using these tools and the vendors selling them can face liability under the new statute.

Supporters of the bill — including consumer advocates, labor groups, and progressive lawmakers — argue that algorithmic pricing has created a new form of collusion that existing antitrust law was not designed to catch. They point to federal lawsuits against RealPage, a property management software company accused of helping landlords across the country artificially inflate rents, as a real-world example of the harm. Proponents say the bill empowers Colorado's Attorney General to act against these practices without waiting for Congress or federal regulators to move.

Opponents, including business associations and technology industry groups, warn that the bill's language is broad enough to sweep up legitimate market research and competitive intelligence tools that do not harm competition. They argue that understanding what competitors charge is a normal part of business and that penalizing companies for using data analytics could drive investment out of Colorado. Some legal scholars also question whether the bill's theory of liability — that using a shared algorithm constitutes coordination even without direct communication — will survive court challenges.

For ordinary Coloradans, the bill's practical significance depends heavily on enforcement. If the Attorney General successfully prosecutes cases under the new law, renters in cities like Denver could see relief from algorithmically inflated rents, and workers in sectors like healthcare or hospitality could see wages rise as wage-setting algorithms are disrupted. If courts reject the legal framework or enforcement proves too technically complex, the law may have little practical effect — leaving the question of algorithmic collusion to be resolved at the federal level.