Judge Sceptical of DOJ Push to Make Google Share Search Data with AI Firms

In a closely watched antitrust case that could reshape the digital economy, a U.S. federal judge in Washington, D.C., expressed scepticism on Friday over the Department of Justice (DOJ)’s proposal to force Google to share and syndicate its search results with generative artificial intelligence (AI) companies such as OpenAI.

The case stems from the DOJ’s 2020 lawsuit alleging that Google unlawfully maintained its monopoly in the online search market through exclusionary contracts and anti-competitive behaviour. While the court already found Google liable for antitrust violations last year, the focus has now shifted to determining the appropriate remedies to restore competition.

Judge Questions Scope of Proposed Remedy

During a hearing on May 31, U.S. District Judge Amit Mehta questioned whether mandating Google to provide its search index and ranking algorithms to rivals—particularly AI developers—was an appropriate or feasible antitrust remedy.

The DOJ’s argument, led by antitrust chief Jonathan Kanter, is that without access to the foundational data behind Google Search, emerging AI-driven search engines will struggle to compete. DOJ lawyers argue that companies like OpenAI, Anthropic, and Microsoft’s Bing AI require syndication access to Google's core data to create viable alternatives.

Google Pushes Back on Syndication Order

Google’s legal team, meanwhile, contends that compelling it to share proprietary search data would violate both its intellectual property rights and First Amendment protections, as search results reflect editorial judgment.

“This is not just data—it’s curated content,” said Kent Walker, Google’s President of Global Affairs. “Forcing syndication is a recipe for stifling innovation, not encouraging it.”

Legal scholars also warn that such a remedy could set a dangerous precedent by making dominant tech firms effectively data utilities, a move that could chill private investment in algorithm development and proprietary search technologies.

Legal Context: Structural vs. Behavioural Remedies

The dispute highlights a broader tension in antitrust law between behavioural remedies, such as prohibiting certain conduct, and structural remedies, which may require breaking up a company or mandating data sharing.

Under Section 2 of the Sherman Antitrust Act enacted in 1890, courts may impose remedies that “terminate the illegal monopoly power and prevent its recurrence.” However, such remedies must be proportional, targeted, and legally enforceable.

Impact on AI and Search Innovation

The outcome of the DOJ v. Google remedy phase could profoundly affect the future of generative AI and search engine competition. AI startups increasingly rely on vast amounts of web data to train large language models (LLMs), and Google’s search corpus remains one of the richest such sources globally.

Yet Mehta’s caution suggests the court may hesitate to engineer market competition through forced interoperability, especially when it involves sensitive intellectual property and fast-evolving AI technology.

Legal analysts predict a likely compromise may involve stricter controls on Google’s default agreements with device makers and browsers, rather than an outright mandate to share its search data.

Summary

As the DOJ seeks to curb Google’s dominance in search by leveraging the rise of AI-based competitors, the court faces a complex question: Can competition be restored without infringing on property rights or stifling innovation?

The answer, expected later this year, could redefine the balance between antitrust enforcement and tech regulation in the AI era.