Acting Assistant Attorney General Omeed Assefi delivered a pointed message to dealmakers last week. Companies cannot wave the banner of artificial intelligence to justify mergers that raise competitive concerns unless they bring hard data to support those assertions. The warning, issued at an event at New York University on May 7, underscores a growing impatience within the Justice Department’s antitrust division toward unsubstantiated technological disruption arguments.
“We know when you are trying to mislead us,” Assefi said, according to prepared remarks. He added that officials hear claims about AI replacing entire industries “a lot.” But for the department to take such arguments seriously, “we expect it to be backed up with actual evidence.” The comments come as merger activity in technology and media sectors accelerates amid rapid advances in generative tools and data analytics.
Dealmakers have increasingly leaned on narratives of industry transformation. They argue that fast-moving technologies render traditional market definitions obsolete or that combined entities will innovate faster against emerging threats. Yet antitrust enforcers remain skeptical. They demand concrete proof. Projections alone fall short. Internal strategy documents, customer behavior data, and competitive analyses must demonstrate that the touted disruption will actually materialize and benefit consumers.
This stance builds on years of heightened scrutiny. The DOJ and Federal Trade Commission have challenged several high-profile transactions where parties invoked innovation or disruption without sufficient support. Recent signals suggest enforcers apply the same rigor to AI-related defenses. Reuters first reported the remarks, highlighting how Assefi, who oversees merger reviews, welcomed engagement from parties at any stage while drawing a firm boundary against evasion.
But the caution extends beyond rhetoric. Antitrust officials have grown attuned to patterns. Some companies appear tempted to position AI as a catch-all justification for consolidation that might otherwise draw blocks. Assefi acknowledged that temptation directly. He signaled the division possesses the sophistication to spot when such claims lack foundation. That recognition reflects deeper institutional learning. Staff now routinely probe beyond surface-level assertions about future capabilities.
Consider the broader context. Media and technology industries face genuine upheaval from AI-driven tools that automate content creation, personalize recommendations, and reshape advertising markets. Officials recognize this. In April remarks, Deputy Assistant Attorney General Charlie Beller urged “cautious humility” when assessing mergers in broadcast and media distribution amid streaming and AI shifts, as covered by Bloomberg. Yet humility does not equate to credulity. Enforcers insist on evidence that specific mergers preserve or enhance competition rather than merely consolidate power under the guise of progress.
The message carries practical weight for corporate counsel and investment bankers. Merger filings that rest heavily on vague promises of AI-fueled efficiencies or competitive repositioning now face elevated risk of second requests, extended reviews, or outright challenges. Parties must prepare robust economic analyses, competitor benchmarking, and forward-looking simulations grounded in observable trends. Unsupported storytelling will not suffice.
Nor does the warning arrive in isolation. The antitrust division continues to pursue cases involving information sharing, algorithmic coordination, and concentrated markets where technology plays a central role. Earlier this year, officials expressed concerns about potential collusion facilitated by common AI tools or data platforms. Those worries intersect with merger policy. A deal that increases reliance on shared AI infrastructure, for instance, could amplify anticompetitive risks if not carefully examined.
Assefi’s NYU appearance also served a procedural point. He emphasized that merging parties should approach the division early and often. Dialogue remains open. The department wants to understand novel business models and technological claims. Engagement, however, must rest on candor. Attempts to gloss over competitive overlaps with futuristic AI projections will meet resistance. “We get it,” he said. The frequent invocation of AI has not escaped notice.
This approach aligns with evolving judicial expectations as well. Courts have grown more demanding of empirical support in antitrust matters. Recent decisions stress the need for evidence over theory in both government challenges and private litigation. Merger parties that anticipate litigation must therefore build records that withstand Daubert scrutiny and cross-examination. Anecdotes about AI’s potential no longer carry the day.
Industry observers note the timing. With major technology firms expanding their AI footprints through acquisitions, partnerships, and talent hires, regulators scrutinize these moves closely. Some transactions fall below Hart-Scott-Rodino thresholds yet still attract interest. The DOJ has signaled willingness to investigate non-reportable deals where competitive harm appears likely. AI-related arguments in those contexts will receive the same evidentiary demands.
Critics sometimes charge that such rigor stifles innovation. They argue that antitrust agencies lack the technical expertise to evaluate fast-moving fields like machine learning. Assefi’s comments push back on that view. The division, he implied, understands the technology well enough to distinguish genuine disruption from convenient excuses. That confidence stems from hiring economists, data scientists, and technologists in recent years. The agency no longer relies solely on traditional industrial organization models.
Still, challenges remain. Predicting AI’s impact on specific markets proves difficult even for experts. Capabilities advance unpredictably. New applications emerge rapidly. Enforcers must balance skepticism with openness to novel competitive dynamics. Overly rigid standards could discourage beneficial combinations that accelerate development in areas like drug discovery, climate modeling, or supply chain optimization.
The DOJ appears to thread that needle by insisting on evidence tailored to the transaction. Parties might demonstrate, for example, that a merger enables integration of complementary datasets that improve model accuracy in ways rivals cannot match. Or they could show how combined engineering talent will tackle problems neither firm could address alone. Such showings require more than press releases and visionary slides. They demand internal forecasts, R&D pipelines, and third-party validation.
Legal teams have taken note. Advisories from major firms now stress the importance of substantiating technology-driven efficiencies early in deal planning. Economic experts increasingly incorporate AI-specific variables into merger simulations. Counsel coach executives to avoid loose language in board presentations that could later undermine regulatory arguments.
Assefi left room for legitimate claims. The division does not dismiss AI’s transformative power outright. It simply demands proof that the specific merger at hand will deliver pro-competitive benefits rather than reduce incentives to innovate or raise barriers for entrants. That distinction matters. Many AI markets remain fluid, with low barriers in some segments and high concentration in others. Accurate market definition becomes critical, and evidence helps draw those boundaries.
The warning also reflects continuity with prior leadership. Both the Biden and current administrations have prioritized vigorous antitrust enforcement in technology sectors. Differences exist in emphasis and specific targets. Yet the core requirement that parties substantiate their assertions has endured. Assefi’s remarks reinforce that consistency while tailoring the message to current deal rhetoric.
Looking ahead, expect the division to apply this framework across dockets. Media mergers involving AI-enhanced content platforms, semiconductor deals tied to advanced computing, and software combinations that embed machine learning capabilities will all face similar questions. How does the transaction alter innovation trajectories? What evidence shows new entrants will face meaningful opportunities post-merger? Can the parties quantify claimed efficiencies?
Answers to those questions will shape outcomes more than any blanket invocation of artificial intelligence. Dealmakers who prepare accordingly stand a better chance of securing clearance. Those who treat AI as a talismanic defense risk prolonged battles or blocked transactions. The DOJ has made its position clear. Evidence, not buzzwords, will decide the fate of contested mergers in the age of intelligent systems.
WebProNews is an iEntry Publication