Algorithmic Pricing Emerges as Enforcement Priority for EU & UK Antitrust Regulators

The European Commission and the UK Competition and Markets Authority have both identified algorithmic pricing—including tools used by competitors to generate or benchmark prices—as a priority enforcement area. Businesses should continuously assess their pricing tools, including inputs, outputs, and use cases, to ensure compliance with antitrust laws.

Antitrust laws across the European Union and United Kingdom prohibit agreements or concerted practices that restrict competition. Algorithmic pricing is relevant in this context because interoperable or shared software can potentially serve as a conduit for anticompetitive price coordination.

EU and UK enforcer interest in this topic is no longer merely a theoretical concern. In July 2025, a senior European Commission (EC) official confirmed multiple ongoing investigations into algorithmic pricing. In September 2025, the UK Competition and Markets Authority’s (CMA’s) chief executive described the practice as an “area of focus and concern,” noting the agency is “watching and learning” from US cases and exploring links with generative artificial intelligence (AI).

US PRIVATE ENFORCEMENT AS A PROXY

US private enforcement provides a preview of how antitrust risk may materialize. Common patterns include plaintiffs’ allegations of the following:

• Competitors relying on the same pricing or revenue-management application
• The application ingesting disaggregated, current, or forward-looking non-public, competitively sensitive information (CSI)
• The application generating price recommendations or competitor (price) benchmarks
• Competitors adopting those outputs, leading to reduced price competition

To date, US litigation has centered on software used in connection with real estate rentals, hotel rates, and healthcare reimbursements. For more detail on the US cases, see our LawFlash.

EU AND UK LEGAL FRAMEWORK

European enforcers are expected to consider the existing legal framework and enforcement powers to be broad enough to capture allegations of algorithmic pricing. Under Article 101 TFEU in the European Union and Chapter I of the Competition Act 1998 in the United Kingdom, conduct can be pursued even without an express “meeting of minds,” including where algorithms process CSI or increase transparency in ways that reduce strategic uncertainty. The general concepts enforcers are expected to rely on may include the following:

• Concerted practices: Anticompetitive conduct does not require a formal agreement; it also captures coordination that falls short of an express “meeting of minds.”
• Hub and spoke liability: Intermediaries such as the pricing software vendor can give rise to indirect agreements between competitors.
• CSI input risks: Entering CSI into a shared application—knowing, or where one reasonably ought to know, that rivals may rely on it—can be unlawful even without explicit coordination.
• Vendor liability: Software providers can also be liable if they knowingly enable coordination between competitors.

Whether the traditional antitrust toolkit can effectively address the unique features of algorithmic pricing remains to be seen.

MITIGATING RISK

While any business will have to analyze how the relevant laws apply to their own particular circumstances and activities, companies using or contemplating adopting algorithmic pricing tools in the European Union and United Kingdom should consider whether it is appropriate to take proactive steps to manage risk, including the following:

• Due diligence: Vet third-party pricing software with respect to whether outputs use competitor CSI or promote aligned or elevated pricing.
• Legal caution: Consider seeking legal advice before adopting algorithmic pricing tools also used by other businesses that could be deemed direct competitors.
• CSI inputs: Exercise due caution before providing non-public, current, or forward-looking CSI (e.g., prices, capacity, volumes, or customer identities) into third-party applications. If there is a specific need to supply nonpublic information to an algorithmic tool, assess potential safeguards, including data aggregation and time lags. The nature and scope of appropriate thresholds will vary across industries, market structures, and geographies.
• Documentation: As appropriate, record the intended use cases, data inputs, exclusions, model settings, safeguards, and procompetitive benefits (e.g., lower consumer prices, expanded output).
• Train personnel: Educate staff on the potential legal risks associated with pricing algorithms and exchanging CSI, including through intermediaries.