Algorithmic Pricing and Ranking: The Interplay Between Competition Law and Digital Regulation in the European Union

Autonomous pricing and ranking systems create evidentiary challenges for EU competition law. Experimental research shows that independently deployed reinforcement-learning models can converge on supra-competitive outcomes without communicating, while the opacity of deep reinforcement learning complicates the assessment of algorithmic conduct. This article examines whether records and disclosures generated under EU digital regulation can strengthen the evidentiary basis for applying Articles 101 and 102 of the Treaty on the Functioning of the European Union without altering the substantive requirements for liability. The study combines a review of legal and economic scholarship with a systematic interpretation of relevant legislation and case law. It examines Articles 101 and 102 TFEU, the Artificial Intelligence Act, the Digital Markets Act, the Platform-to-Business Regulation, as well as Court of Justice case law. Online travel agency markets provide an illustrative setting informed by published empirical research. The analysis distinguishes difficulties in proving concerted practices under Article 101 TFEU from difficulties in attributing ranking conduct and establishing its exclusionary effects under Article 102 TFEU. It argues that algorithmic outcomes alone cannot resolve those difficulties. Drawing on Court of Justice case law, the article develops a statutory factual benchmark: an evidentiary framework that uses applicable digital-regulatory obligations to identify relevant governance records and ranking disclosures. It distinguishes directly applicable duties from the AI Act’s contextual relevance to systems outside its high-risk categories. The article proposes that verified noncompliance with applicable documentation or transparency obligations may support a rebuttable inference requiring the undertaking to explain the deficiencies and produce relevant materials. This mechanism would not establish an infringement by presumption or shift the enforcement authority’s legal burden of proof. Where enforcement proceedings overlap, coordination and pro-portionate combined penalties are required. The framework thus offers a means of addressing evidentiary gaps caused by algorithmic opacity while preserving the existing elements of competition-law liability.