Adapting to and Getting Ahead of Changes in Antitrust and Other Regulatory Demands in 2025 and Beyond

Seismic shifts in the legal and regulatory landscape are underway, driven by evolving federal policy, shifting state priorities, and the rapid advancement of artificial intelligence (AI) and other emerging technologies.  These developments present both significant risks and transformative opportunities for businesses.

In this article, we examine each of these forces of change and argue that, while ongoing federal and state developments warrant close attention, it is the rise of AI and advanced technologies that pose the most urgent challenges—and the greatest potential—for organizations facing regulatory scrutiny.  These tools can both complicate and strengthen compliance programs, enabling companies to:

1. Enhance internal controls to better align with regulatory requirements; and
2. Anticipate and prepare for future investigations and enforcement actions.

Now is an ideal time for companies to assess and upgrade their document and information governance practices to meet the demands of a rapidly changing enforcement environment.

The Federal Landscape

The second Trump administration has articulated a lack of interest in enforcing certain laws, such as the Foreign Corrupt Practices Act, and a desire to curtail many regulatory agencies, including, but not limited to, the EEOC, CFPB, FDA, and CFTC.  At the same time, it has threatened the use of agency enforcement powers, including those of the DOJ and the FCC, which would arguably further current administration priorities.  While the federal enforcement landscape is decidedly mixed, many areas will undoubtedly see less enforcement activity.

The future of antitrust enforcement is one such mixed picture.  For example, the administration has replaced the prior leadership at the FTC; Andrew Ferguson, the new FTC Chairman, has said he plans to reduce scrutiny of mergers and acquisitions while maintaining oversight of Big Tech.^[1]  While the newly restructured FTC may adopt a more favorable stance towards mergers and acquisitions by adhering to traditional antitrust theories, bipartisan concerns in sectors such as Big Tech, healthcare, and energy indicate that antitrust compliance will remain of utmost importance for these companies.^[2]  Chairman Ferguson is also expected to lead a Commission that is more open to accepting remedies and behavioral adjustments to address issues in problematic mergers and acquisitions.^[3]

On February 24, 2025, at a Washington Reporter event sponsored by the Coalition for App Fairness, Chairman Ferguson outlined his approach to antitrust regulation and previewed the FTC’s agenda for the upcoming year.  The discussion addressed the state of online competition and mobile app marketplaces, with Chairman Ferguson emphasizing the importance of free and competitive online markets as vital drivers of growth and innovation.  “When the economy is vibrant, new ideas come to the fore and can be marketed very quickly.  We must consider potential losses of innovation and consumer choice.  My role is to use antitrust laws to curb monopoly power and promote innovation.”^[4]  More recently, on July 8, 2025, the DOJ Antitrust Division, in conjunction with the Postal Service, announced a new “Whistleblower Rewards Program” designed to “incentivize individuals to report postal-related antitrust crimes that undermine the competitive process or market competition across industries.”^[5]

Given the mixed messaging, companies trying to decide on the best and “safest” posture to maintain in the current environment need to keep two things in mind; although enforcement priorities may have changed, the law and the statute of limitations, has not.  As of now, no laws have been repealed or enacted; however, the government can change its priorities at any time.  A case can be made that, despite the ground shaking, nothing truly exceptional has yet.  What companies are experiencing today is similar to what they have experienced episodically over the past half century.  For example, Jimmy Carter selected Michael Pertschuk to head and reinvigorate the FTC in 1977.  Four years later, Ronald Reagan brought in James Miller and the Chicago School of Economics to rein in an overzealous FTC.  The pattern continued with each change of administration, up to Joseph Biden’s selection of Lina Khan in 2021 to revitalize the FTC, preceding Donald Trump’s recent selection of Andrew Ferguson.  We, of course, do not know who or what is next, but history suggests a pattern nonetheless.

The bottom line for businesses today is to continue current initiatives or improve their compliance programs, especially by ensuring that their business documents and records are accounted for and readily accessible.  Consumer trust is vital to the success of any business; in the long run, misconduct harms production, worsens employee morale, and makes it difficult to hire good talent.^[6]  A company whose loftiest target is to avoid a law enforcement action is aiming too low.

The "Shifting" State of Antitrust Terrain

Both the Sherman Antitrust Act and the Clayton Act allow for state enforcement.  States have always played a vital role in the enforcement of the Federal Antitrust laws, often appearing as co-plaintiffs in actions initiated by the federal government, and even more significantly, pursuing their own actions of alleged federal law violations.  For example, a coalition of 51 states and territories has filed actions alleging price-fixing among members of the generic pharmaceutical industry.  Similarly, a coalition of Republican Attorneys General has challenged the commitment of three investment firms to invest in environmentally friendly businesses.  The Nebraska Attorney General has also sued heavy truck manufacturers, challenging their membership in the Clean Truck Partnership.  Arguably, these cases portray the states’ interest in antitrust enforcement not being limited to the climate of any one political party, and further suggest that private businesses should not relax their compliance programs and recordkeeping because they (mis)perceive a slowdown in federal enforcement and fewer federal investigations.

Apart from their roles in investigating and enforcing federal laws, most states have their own antitrust laws.  Some, such as the California Cartwright Act, are long established and carry both civil and criminal sanctions.  Others are much newer, including Washington’s recent law modeled after the Uniform Antitrust Pre-Merger Notification Act, which went into effect on July 27, 2025^[7] and permits the State Attorney General to receive a Hart-Scott-Rodino filing concurrently with the initial federal filing, while adhering to the same confidentiality obligations.^[8]  Still, other antitrust laws are pending before various state legislatures.  For example, if finally enacted, the 21^st Century Antitrust Act, NY S. 6748, will, among other things, create a presumption of illegality when “dominant” firms engage in exclusive dealing; requiring merging parties to submit their premerger filings to the State AG, and enabling the State AG to pursue unfair methods of competition that result in “incipient” violations of the antitrust laws or cause harm that is comparable to other violations of those laws.  Apart from perhaps the NY S. 648 prohibition of unfair methods of competition, none of these laws enlarge substantive federal law governing competition, but rather affect evidentiary and production burdens only.

In short, private entities would be well advised to continue and even improve their compliance and recordkeeping practices in anticipation of state law enforcement actions and investigations, and the potential of future federal actions. 

The AI and New Technology Avalanche: Perils and Opportunities

AI has transformed business operations, allowing companies to process extensive data sets and automate intricate tasks in unprecedented ways.  As a result, AI has caught the attention of law enforcement in two important ways.  First, AI is seen by law enforcement authorities as a tool that can improve their own operations.  Second, AI is seen by the same authorities as a tool for private parties to violate the antitrust laws.  Because both can and will affect private parties and their compliance, information management, and records retention and production practices, we address them separately.

Antitrust 3.0 – Computational Antitrust

Just as the gradual adoption of rigorous economic analysis in the final quarter of the last century defines “Antitrust 2.0”, a landmark paper by Dr. Thibault Schrepel suggests that the adoption of AI and new technologies, or Computational Antitrust, will define “Antitrust 3.0” in the future.^[9]  While a full, or even a fair, description of Computational Antitrust is beyond the scope of this article, suffice it to say that Computational Antitrust might be defined as the application of legal informatics and mechanization of antitrust legal analysis to include the “implementation of computational methods . . . to detect, analyze, and remedy anticompetitive practices.”^[10]  The Computational Antitrust Project (CAP) claims 67 participating competition agencies globally, including the DOJ and FTC.  Advocates of Antitrust 3.0 argue that Computational Antitrust will enable:

The active detection of anticompetitive practices, the use of forensic tools for analyzing evidence, and the development of platforms that facilitate access to data from entities under investigation; (2) the ability, within merger control, to analyze datasets or generate simulations to assess claims related to efficiencies, substitutability, and market contestability, and other relevant issues; and (3) retrospective evaluation of agency interventions and the implementation of competition policies, with an emphasis on generating predictive insights.^[11]

This suggests that in the future, private businesses can and should expect regulators to seek even larger quantities of data than they presently do.^[12]  Indeed, it is not difficult to anticipate production demands for “any and all data and information relating to algorithmic inputs, outputs, source codes, program architectures and protocols, AI prompts, test and audit results, and oversight measures,” among other things.  It is equally foreseeable that regulators will process that data to produce results that the parties who own the data may not fully anticipate, and demand that they comply with investigative production demands very quickly.^[13]  

Preservation, Retention, and Production Practices

Just as competition authorities are seeing AI and other new technologies as a means to improve their own operations, they are also taking a critical look at the use of AI by private entities.  Specifically, the business use of AI has raised concerns among enforcers due to their perception that its use may foster anticompetitive practices and the sharing of sensitive information.  For example, one such concern is that algorithms might facilitate price-fixing, predatory pricing, and the implementation of discriminatory pricing strategies, which may adversely harm consumers.  In their view, the rapid progress and continuous evolution of AI technology has resulted in the deployment of increasingly sophisticated algorithms.  This growing complexity poses significant challenges to antitrust authorities in detecting and addressing potentially anticompetitive behavior.  

Similarly, court rulings and legislative measures have drawn particular attention to pricing recommendation algorithms that utilize confidential, non-public information from multiple businesses.  At the federal level, U.S. Senator Amy Klobuchar, along with several other Democratic senators, introduced the Preventing Algorithmic Collusion Act in February 2024 to prohibit companies from using algorithms to collude and set higher prices.^[14]  Senator Klobuchar stated, “Price fixing is illegal under our antitrust laws, but the development of price-setting algorithms can exploit loopholes that could be used to unfairly raise prices on everything from rent to rideshares.”^[15]  The bill has eight Democratic cosponsors, but its passage will be challenging, as it lacks bipartisan support in the Republican-controlled Congress.^[16]  Although this legislation did not advance in the U.S. Congress in 2024, Senator Klobuchar and other senators reintroduced it in 2025.^[17]

With ongoing oversight of the use of AI and algorithms, it is prudent for companies to collaborate with vendors to understand the data and methodologies used in these algorithms to train AI models.  Companies should exercise prudence when engaging with a vendor to develop or implement pricing tools if the same vendor also collaborates with other companies that may be classified as competitors.  Similarly, caution is warranted when working directly with other industry organizations to create AI applications that, while not pricing tools, could still enable other types of information exchange. 

To collaborate effectively, companies should clearly define their AI implementation goals and communicate them to vendors.  Establishing a structure for communication, feedback, and joint problem-solving can foster open dialogue and brainstorming.  This process includes thoroughly vetting vendors, understanding data ownership terms, and ensuring the long-term viability of AI solutions.  Companies should evaluate vendors based on expertise, platform flexibility, data security, and scalability.  Additionally, companies must ensure their risk management protocols can handle AI-driven decisions and adapt to potential threats.  By embracing a collaborative approach, companies can unlock AI's full potential, drive innovation, and mitigate risks while ensuring ethical practices.^[18]  To withstand any future regulatory challenge, the parties should document their respective decisions and the actions they take.

Takeaways

As the antitrust landscape continues to evolve, it is important that organizations and their counsel work together to develop and maintain, or better yet improve, their data governance procedures.  First and foremost, they should bear in mind that both companies and individuals are legally obligated to preserve documents during government investigations or litigation.  In January 2024, the DOJ and FTC updated their antitrust preservation specifications, emphasizing a company’s obligation to retain data from collaboration messaging platforms during investigations.^[19]  This new language specifically includes current methods of collaboration, such as ephemeral messaging and other group and individual communications on platforms such as Microsoft Teams, Slack, and Google Chat.  These requirements apply to messaging application data preservation in Second Requests and other regulatory requests.^[20]

Second, when revising corporate antitrust preservation practices, companies and their counsel should be aware of the increased attention from regulatory agencies on how corporations manage, handle, and use data from third-party messaging applications.  Close regulatory scrutiny will likely continue as the use of messaging applications in company communication grows and collaboration platforms evolve. 

Third, companies should take proactive steps to review their policies and procedures regarding data retention, legal holds, and proper use of communications platforms.  A truly effective and successful competition compliance and information governance program will focus on a corporate culture reinforced by compliance assessments and gap analyses to ensure the company monitors policy adherence, detects transgressions promptly, and maintains adequate data retention and preservation controls.  In this regard, programs to encourage employees to report violations without fear of recrimination and training programs and tests are important components for informing employees of their responsibilities under these policies and procedures, as well as the potential consequences of non-compliance.^[21]

A truly effective program that successfully integrates AI will consider the crucial role the federal government plays through initiatives aimed at fostering the safe, responsible, and secure development and deployment of AI.  In this context, AI preservation refers to maintaining the accessibility and functionality of information over time, including its physical components as well as its associated data and algorithms.  This process involves managing challenges such as data obsolescence, hardware and software compatibility, and ethical considerations related to AI’s societal impact.  The successful integration of AI into archival and preservation practices will complement, rather than replace, human expertise.  These technologies are designed to enhance efficiency in specific tasks, thereby enabling professionals to dedicate greater attention to activities that require human judgment and cannot be fully addressed by current technological solutions.  While many challenges in the field relate to cost-effectiveness and adequate staffing, AI has the potential to optimize resources and alleviate workload pressures.  Ultimately, this approach will allow archivists to spend more time engaging directly with materials and less on system management.^[22]

The views expressed in this article are those of the authors and do not necessarily represent the views of their law firm or any of its clients.