Algorithmic pricing scrutiny now spans real estate, hotels, and healthcare, raising a fundamental question: How do courts distinguish lawful pricing software from unlawful coordination?

Companies have long relied on market intelligence for pricing strategies, gathering competitor data, analyzing industry trends, and adjusting prices accordingly. For decades, antitrust law set clear boundaries around how companies exchange and use this information. But the technology enabling these practices has changed fundamentally. Revenue management software and algorithmic pricing tools now process vast data volumes and generate pricing recommendations with unprecedented speed and sophistication.

These tools offer business value but trigger antitrust litigation that reshapes how courts and regulators view pricing practices. At TransPerfect's LegalNEXT conference in New York City, a panel of antitrust practitioners explored the litigation risks, enforcement trends, and compliance strategies emerging from this shift. The antitrust experts' insights reveal high stakes: federal enforcement actions, multidistrict litigation, and state attorney general investigations proliferate.

The Expansion of Algorithmic Pricing Litigation

At the conference, panelists noted that high-profile investigations into pricing software for multifamily residential real estate sparked widespread attention to algorithmic pricing. This scrutiny spawned litigation waves—private class actions consolidated into multidistrict litigation, as well as enforcement actions by the Department of Justice and multiple state attorneys general, including Washington, DC, and Arizona.

The antitrust experts further observed that similar strategies now target industries beyond real estate. Recent cases focus on hotel operators in Las Vegas and Atlantic City that use pricing recommendation systems, while healthcare cases examine how pricing tools facilitate coordination among competitors.

While circumstances differ, these cases share common allegations: competitors using common pricing software conspire to fix, raise, or stabilize prices, violating section 1 of the Sherman Act.

Emerging Legal Standards from Recent Court Decisions

As these cases moved through courts, LegalNEXT panelists observed patterns emerging in how judges evaluate algorithmic pricing claims. The antitrust experts noted that courts focus on several key factors:

• Independent pricing authority: Whether users retain the ability to reject or deviate from software recommendations.
• Data sources: Whether algorithms rely on confidential competitor data versus public information or each user’s individual data.
• Adoption patterns: Whether adoption timelines across companies suggest coordination.

According to the panelists, whether algorithms incorporate confidential competitor information has proven particularly significant among these factors in case outcomes. Yet the fundamental question remains whether competitors agreed to restrain competition, with courts evaluating how algorithms function and what data they process.

Government Enforcement: An Evolving Approach

The experts also discussed how civil litigation has produced mixed results for plaintiffs, while government enforcement agencies have adopted an expansive interpretation of algorithmic pricing risks.

Federal agencies signaled this shift before recent high-profile cases. In 2023–24, the DOJ and FTC withdrew longstanding policy guidance on competitor collaborations, citing the need to address algorithmic pricing and AI-driven coordination.

Panelists highlighted the agencies' evolving position. In recent enforcement actions, the DOJ argues that algorithmic pricing arrangements can constitute illegal agreements, even when users retain discretion to reject recommendations. The agencies treat pricing recommendations as per se price fixing when they eliminate independent decision-making among competitors, viewing the joint delegation of key pricing decisions to a common agent as the legal equivalent of direct information sharing.

The panelists observed that this enforcement approach has remained consistent across administrations. The DOJ and FTC have filed similar statements in multiple algorithmic pricing cases. For example, a recent statement of interest in the MultiPlan case maintained that using common pricing algorithms can constitute concerted action even when competitors use the algorithm differently.

Meanwhile, recent enforcement settlements have begun drawing clearer lines, distinguishing between external nonpublic data and confidential competitor information.

Beyond Section 1: Merger Review and Other Implications

The algorithmic pricing debate extends beyond traditional Sherman Act enforcement. Panelists identified two emerging areas where algorithmic pricing creates compliance complexities: merger review and government contracting.

Merger review challenges. Panelists explained that FTC and DOJ merger guidelines allow agencies to challenge mergers that increase the risk of coordinated action, even without an actionable section 1 violation. Algorithmic pricing complicates this analysis. If many small competitors use similar pricing software, coordination might be easier than traditional methods suggest. Conversely, if companies customize algorithms to reflect their specific cost structures and strategic goals, prices may diverge rather than converge. Traditional merger analysis factors become unclear when algorithms drive pricing decisions rather than human judgment, making it more challenging to evaluate whether past coordination occurred.

Government contracting considerations. Panelists noted that for government contractors, algorithmic pricing raises questions beyond antitrust law. Contractors filing certificates of independent pricing face potential scrutiny when using algorithmic tools, as certificate requirements may differ from antitrust law's agreement standards. This creates a compliance intersection that enforcement agencies have begun examining, particularly where algorithmic pricing decisions intersect with certification obligations.

Understanding Algorithmic Pricing in Litigation and Enforcement

Companies using algorithmic pricing tools increasingly face private litigation, DOJ enforcement actions, and state attorney general investigations. LegalNEXT panelists identified several patterns emerging from these matters.

What Regulators and Courts Examine

Litigation and regulatory inquiries consistently focus on a core question: What data does the algorithm use? Software using public or internal company data presents fewer concerns than tools incorporating competitors’ confidential information. Courts also examine whether companies retain meaningful discretion to deviate from algorithmic recommendations based on business judgment, competitive conditions, and other factors.

What Stronger Defenses Demonstrate

Companies with more successful litigation outcomes show that algorithms serve as one input among many—not the sole determinant of pricing strategy. Documentation showing independent decision-making proves particularly significant in these matters.

What Compliance Programs Address

Panelists discussed how the DOJ references guidelines emphasizing four areas in the algorithmic pricing context:

• Whether compliance programs specifically assess antitrust risks associated with the algorithmic pricing tool, including examining whether the software uses competitor information
• Whether companies implement concrete safeguards—such as technical controls on data inputs, human review processes, or limitations on software use—rather than relying solely on passive awareness of compliance risks
• Whether compliance officers and relevant technical personnel understand the system's fundamental mechanics and data sources well enough to identify potential issues
• Whether organizations can detect potential problems through periodic audits, anomaly detection, or pricing pattern reviews rather than relying solely on external complaints or regulatory inquiries to surface issues

The Path Forward: Uncertainty and Adaptation

Predicting algorithmic pricing enforcement's future is challenging. Technology evolves rapidly, with AI systems becoming more sophisticated.

The antitrust expert’s consensus suggests information exchange and algorithmic coordination will remain enforcement priorities. But how antitrust law principles apply to specific technologies and business practices will continue evolving through litigation and enforcement actions.

Panelists noted that successful litigation outcomes involve organizations that understood their tools, demonstrated independent pricing decision-making, ensured personnel understood antitrust compliance implications, and maintained process documentation. As enforcement approaches shift, organizations positioned to respond effectively approach algorithmic pricing with transparency and deliberate implementation strategies.

Partner with Antitrust Experts

As algorithmic pricing litigation and enforcement actions intensify, organizations need dedicated specialists who understand antitrust regulatory complexities.

TransPerfect Legal’s Antitrust Practice Group provides specialized support for second requests, merger clearance proceedings, and government investigations worldwide—with dedicated antitrust project managers and follow-the-sun support. We work alongside your counsel to deliver forensic collection, eDiscovery, managed review, and technical expertise designed specifically for antitrust matters.

Contact our Antitrust Team to discuss how our dedicated specialists can support your matter.