U.S. regulators have begun rewriting the rulebook for how competing companies can work together in the age of AI and big data.
This all started because the old rules, written in 2000, were withdrawn in December 2024. Regulators felt they were hopelessly outdated for today's digital economy, where algorithms and massive data pools are common. This withdrawal, however, left a vacuum, creating significant uncertainty for businesses that rely on data sharing for things like setting industry standards or benchmarking performance.
So, what pushed them to act now? A major factor is the recent crackdown on what's called 'algorithmic collusion'. The most prominent example is the lawsuit against RealPage, a software company that provides rental price recommendations to major landlords. The Department of Justice (DOJ) alleged that landlords were using RealPage's algorithm, fed with sensitive, real-time data from competitors, to artificially inflate rent prices. This case sent a clear signal that regulators are targeting digital tools that facilitate price-fixing.
First, the legal actions against RealPage and its clients have created a de facto blueprint for the new rules. Settlements in these cases have focused on prohibiting the exchange of real-time, non-public, and disaggregated competitor data. In simple terms, companies can't share fresh, detailed pricing information from their rivals through a third-party platform. Instead, any shared data should be old, aggregated, and anonymized to prevent coordination.
Second, leadership changes at the Federal Trade Commission (FTC) also played a role. The new FTC Chair, Andrew Ferguson, had previously dissented when the old guidelines were withdrawn, arguing that it was irresponsible to remove the rules without a replacement ready. Now in charge, he is moving to fill that gap. The U.S. is also looking to international examples, as the European Union already updated its own guidelines in 2023 to address algorithms specifically.
Ultimately, this new guidance aims to draw a clear line between pro-competitive collaboration and illegal collusion. For businesses, this means a new, modern set of rules is on the way that will define the future of data sharing and algorithmic pricing.
- Algorithmic Collusion: When competing companies use a shared algorithm or software to coordinate their prices or output, effectively acting like a cartel without explicit agreements.
- Disaggregated Data: Highly specific, individual data points that have not been bundled or anonymized. For example, the exact rent for a specific apartment unit, rather than the average rent for a neighborhood.
- Antitrust: Laws and regulations designed to promote fair competition in the marketplace by preventing monopolies, price-fixing, and other anti-competitive practices.