Regulators Sketch Framework for ‘America First’ Antitrust Policy

Unlike in past years, federal antitrust enforcers skipped this year’s American Bar Association Antitrust Spring Meeting. Frustrations with ABA policy led senior leadership at both the Federal Trade Commission and US Department of Justice Antitrust Division to instead join a separate event hosted by FGS Global and the Capitol Forum to discuss enforcement priorities. State antitrust enforcers, however, still attended the event and used it to highlight their enforcement priorities.

FTC Chair Andrew Ferguson and Assistant Attorney General Gail Slater used the competing forum to emphasize that an “America First” antitrust policy requires agencies to vigorously enforce the antitrust laws—particularly against large corporations and special interests. It was the latest in a growing set of data points suggesting this administration’s antitrust enforcement will be more aggressive and less pro-business than past Republican enforcers.

Many antitrust observers believed Lina Khan’s departure, whose positions left her stigmatized by the business community, would usher in less aggressive antitrust enforcement. However, with both federal and state enforcers remaining proactive, businesses are unlikely to experience the anticipated antitrust leniency that they may have originally expected.

Labor Market Issues

Despite some who anticipated laxer antitrust enforcement of labor market issues in the coming years, both federal and state enforcers stressed that labor investigations and cases will be a focal point going forward. Notably, Ferguson clarified that his past objection to an FTC noncompete rule didn’t indicate a hands-off approach to noncompete agreements.

His dissent reflected his doubt that the agency had authority to enact such a broad rule. While he thought a catch-all rule was inappropriate, Ferguson said he believed these provisions can run afoul of the antitrust laws and are often problematic. Indeed, he suggested the FTC may create a labor task force to investigate these issues. He also indicated that the FTC will continue active enforcement against noncompete provisions to ensure robust labor competition is an integral part of an “America First” antitrust policy.

State enforcers likewise highlighted successful labor market antitrust cases and emphasized their importance to constituents. They indicated plans to investigate markets less likely to be targeted by federal enforcers, such as fast food and grocery workers. This policy would expand labor investigations beyond traditionally focused “skilled” labor industries (such as medical and engineering).

Businesses in all markets should expect a swath of labor market investigations in the coming years and should prepare accordingly. Previously, employers may have believed they could enact noncompete provisions with little antitrust risk.

This is no longer the case. Regardless of their market, businesses should proactively evaluate any noncompete agreements in their contracts rather than wait for an announcement or investigation to do so—because by that time, it is often too late to mitigate antitrust risk.

Artificial Intelligence

Ferguson previously committed to end “the FTC’s attempt to become an AI regulator.” But businesses shouldn’t view this FTC policy shift as an indication that AI enforcement will wane. State and foreign enforcers appear ready to step in quickly if the FTC deprioritizes enforcement, particularly in highly concentrated industries where AI use could help companies become entrenched as market leaders and block new entrants.

There is no unified regulatory approach to AI risks in antitrust, leading to different standards across jurisdictions. These discrepancies increase uncertainty and risk, as conduct overlooked by federal enforcers may attract European or state enforcers’ attention.

Pricing algorithms—a type of AI that suggests pricing levels based on either public or anonymized confidential information—have led to uniform scrutiny across enforcers, however. Enforcers have investigated whether they facilitate collusive behavior without direct communications among competitors and contend that the use of such technology may be anticompetitive.

Regardless of the jurisdiction, enforcers have highlighted automatic acceptances as collusive conduct in their antitrust investigations and litigation. Without implementing and detailing independent decision-making underlying ultimate pricing decisions, “setting and forgetting” the AI algorithm may be considered indicative of a conspiracy to increase market prices among competitors using the same software.

To mitigate risk, companies should ensure human oversight in pricing decisions and regularly monitor pricing recommendations. For example, many algorithms have customizable features to decline automatic acceptances of pricing suggestions.

Businesses also should be aware of the data used by AI algorithms, as antitrust risk increases if the data is sourced from competitors. Businesses that use these technologies must collect documentation outlining the various factors and independent reasoning behind pricing decisions.

AI use can also impose significant document preservation risk, which continues to be an important issue for courts and federal regulators. Like problems faced with ephemeral messaging, such as messages that auto-delete, companies may need to preserve AI inputs for legal compliance or potentially face adverse rulings that can undermine future investigations and litigation.

Businesses should develop policies and guidelines for AI use, as well as AI input and output preservation, to mitigate risk. Businesses that employ a reactive policy—only evaluating AI use and policy in the face of an investigation or case—will be less likely to escape fines, litigation, or damages.

What to Do

Both AI and labor markets promise to be focal points of antitrust enforcers in the coming years. Business can prepare by:

• Reviewing employment agreements with noncompete provisions to ensure they serve an important business purpose and are limited in scope
• Evaluating any AI use involved in competitive analysis or decision making, particularly those involved in setting or suggesting pricing
• Ensuring litigation holds capture both AI inputs and outputs

Proactive reviews of these issues can mitigate antitrust risks and potentially avoid investigations. Delaying evaluations until under antitrust scrutiny substantially increases legal risk, as problematic evidence is often created long before investigations or litigation begin.

This article does not necessarily reflect the opinion of Bloomberg Industry Group, Inc., the publisher of Bloomberg Law and Bloomberg Tax, or its owners.

Author Information

Shylah Alfonso and Christopher Williams are partners at Perkins Coie.

Counsel Ryan Maddock and Caroline Tunca contributed to this article.

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