In the age of big data and artificial intelligence, businesses are increasingly using algorithms to make important business decisions. This trend raises antitrust concerns that companies need to be aware of.

In February 2023, Principal Deputy Assistant Attorney General Doha Mekki of the Antitrust Division of the U.S. Department of Justice (DOJ) discussed the antitrust risks associated with algorithms. She noted that algorithms are increasingly being used by businesses to make decisions about pricing, product development, and other important business matters. This raises the risk that algorithms could be used to engage in anticompetitive conduct, such as price fixing or market allocation.

Mekki highlighted the DOJ's recent enforcement actions against companies that allegedly used algorithms to engage in anticompetitive conduct. For example, in 2020, the DOJ filed a civil antitrust lawsuit against two major airlines alleging that they used algorithms to coordinate prices. In 2021, the DOJ filed a civil antitrust lawsuit against a major technology company alleging that it used algorithms to stifle competition in the online retail market.

Mekki also said that the DOJ is committed to ensuring that businesses can use algorithms to innovate and compete, but that the DOJ will also take action to prevent algorithms from being used to harm competition.

Recently, at the ABA Antitrust Law Spring Meeting, the DOJ and FTC announced that they are taking steps to address this issue, including:

  • Hiring data scientists, computer scientists, and economists to help them better understand and detect anticompetitive conduct by algorithms.
  • Conducting outreach to industry experts and technologists to learn more about how algorithms work.
  • Developing new guidance on the antitrust risks associated with algorithms.

The DOJ and FTC are not alone in their concerns about algorithmic pricing. Other antitrust enforcers, including state AGs, and international regulators around the world are also taking steps to address this issue. For example, the European Commission has published a report on the use of algorithms in competition law enforcement. The report identifies a number of challenges that antitrust enforcers face in investigating and prosecuting anticompetitive conduct involving algorithms.

Similarly, antitrust class action lawyers are also preparing for the challenges posed by algorithmic pricing. They are hiring data scientists and economists to help them understand how algorithms work, conducting discovery to obtain information about pricing algorithms, working with economists and other experts to develop economic theories of harm, and bringing cases in jurisdictions that are favorable to antitrust plaintiffs. Additionally, they are working to educate judges and juries about the potential for pricing algorithms to be used to engage in anticompetitive conduct.

The use of algorithmic pricing is a growing trend, and it is likely to continue to grow in the years to come. As this trend continues, companies need to be vigilant to comply with the antitrust laws and make sure they have done everything to defend their pricing practices if challenged by regulators or litigants.


Businesses that use algorithmic pricing should consider measures to help avoid antitrust risk. Some tips for avoiding liability include:

  • Do not disclose publicly any information about pricing algorithms or pricing tools. This information is considered competitively sensitive and could be construed by regulators or plaintiffs as a form of communication or tacit collusion with competitors.
  • Document your pricing decisions. This documentation will help to show that your pricing decisions were made independently and were not the result of tacit collusion with competitors through algorithmic means or otherwise.
  • Conduct a thorough antitrust review of your pricing algorithm. This review should identify any potential antitrust risks associated with your pricing algorithm. This includes ensuring that the algorithm is based on objective factors—such as cost, demand, and quality—and it should not be designed to give any one customer an unfair advantage. If any risks are identified, take steps to mitigate them by implementing changes to the pricing algorithm and any suspect business practices and updating your antitrust compliance program.
  • Incorporate the risks of pricing algorithms into an updated antitrust compliance policy and provide training to employees. The policy should clearly state that businesses are prohibited from engaging in any anticompetitive conduct, even if that conduct is accomplished through pricing algorithms. Training should cover the potential antitrust risks associated with pricing algorithms, as well as the company's policies and procedures for preventing and detecting anticompetitive conduct. Consider hiring experienced antitrust counsel that can provide expert advice on the antitrust risks associated with pricing algorithms and help draft a policy that is tailored to the specific needs of the business.


For companies looking to implement pricing algorithms, there are different considerations to take into account, depending on whether the business is undertaking to develop the technology on its own or hiring an outside vendor or consultant.

Some best practices to ensure antitrust compliance when companies are developing pricing algorithms on their own include:

  • Work with IT to understand your technology. In-house counsel should work with IT to understand how the company's pricing algorithms work. This will help counsel to identify potential antitrust risks and to ensure that the algorithms are designed and used in a way that complies with antitrust law.
  • Train IT in antitrust. IT professionals should be trained in antitrust law so that they are aware of the potential antitrust risks associated with pricing algorithms. This training should cover topics such as price fixing, market allocation, and conscious parallelism.
  • Monitor self-learning algorithms. Self-learning algorithms are algorithms that can learn and adapt on their own. These algorithms can be a valuable tool for businesses, but they can also pose antitrust risks. Businesses should monitor self-learning algorithms to ensure that they are not being used to engage in anticompetitive conduct.
  • Design pricing algorithms to be transparent and nondiscriminatory. This means that the algorithm should be based on objective factors—such as cost, demand, and quality—and it should not be designed to give any one company an unfair advantage.

When selecting a vendor or consultant to purchase or design a pricing algorithm, companies should consider these best practices to help ensure that their use of third-party software complies with antitrust law:

  • Conduct and document due diligence to understand safeguards that third-party companies have in place to mitigate antitrust risks. This includes understanding the company's antitrust compliance program, its market share, and the technology and inputs it uses.
  • Review and ensure that contractual provisions and structural and technological mechanisms are in place to mitigate antitrust risks. This includes provisions that prohibit price fixing and market allocation.
  • Beware of adopting a particular algorithm or software with the understanding that others in the industry are using it or will be using it and that it will help coordinate or stabilize pricing. This is a red flag for antitrust concerns.
  • Be extremely cautious in using algorithms that rely on data from third parties to set prices, wages, or production levels. This is because third-party data can be inaccurate or biased, and it can be difficult to ensure that the data is not being used to engage in anticompetitive conduct.
  • Discourage representations by the manufacturer about sales to your competitors or other information revealing how competitors use the software. This information can be used to coordinate pricing or other anticompetitive conduct.
  • Have antitrust counsel present in discussions with third-party software developers when choosing a third-party pricing software. This will help to ensure that the company is aware of the antitrust risks associated with third-party software and that it is taking steps to mitigate these risks.

Companies should tread carefully to ensure that their use of algorithmic pricing complies with antitrust law. This will help to protect their businesses from antitrust liability and ensure that they are able to continue to use this powerful tool to their advantage.

In addition to the tips in this blog post, businesses should also consult with an antitrust attorney to ensure that their use of algorithmic pricing complies with the law.

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.