Competition watchdogs deploy AI to detect cartels and bid-rigging
Competition authorities across Europe are increasingly using AI to identify anticompetitive behavior, a shift that lawyers say will likely trigger more investigations and dawn raids.
The European Commission's 2024 investigation into tyre manufacturers offers the clearest example. Regulators used AI to analyze hundreds of thousands of public statements and earnings calls from companies including Michelin, searching for signs that firms were coordinating prices through public signals.
The AI screening flagged potential coordination indicators, leading to dawn raids in January 2024. When Michelin challenged the raids before the EU's General Court, the court upheld the commission's approach. The ruling validated using AI to screen publicly available information as justification for inspections-provided authorities combine the AI analysis with manual review of findings.
That combination of automated and human analysis appears critical. The court found the methodology legitimate only because regulators paired quantitative AI screening with qualitative human assessment.
National authorities follow suit
Spain's competition authority, the CNMC, has deployed an AI tool trained on public-procurement data to flag potentially collusive bids. Lithuania's Competition Council piloted AI-driven e-discovery tools to detect cartel activity, including an AI platform designed to spot signs of collusion in documents.
Britain's Competition and Markets Authority is testing an AI system to identify bid-rigging in public contract bids.
The EU launched the Digital Transformation in Competition Law Enforcement project in January to upgrade AI capabilities across 15 member-state authorities. The scheme aims to close gaps in digital enforcement capacity.
Wider adoption expected
Competition authorities globally recognize that AI integration is becoming necessary for enforcement, according to analysis by McCann FitzGerald. While adoption rates vary, authorities show a clear willingness to adopt new operational methods.
The shift reflects a broader reality: as companies adapt to exploit emerging technologies, regulators need better tools to detect violations. AI allows authorities to process volumes of data-public statements, procurement records, communications-that would be impractical to review manually.
For legal teams advising companies under investigation, understanding how regulators use these tools matters. The tyre case shows that AI-generated leads can survive legal challenge if paired with rigorous manual analysis.
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