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March 26, 2026Journal of Competition Law & Economics0 citationsOpen Access

AI-Enabled Price Discrimination as an Exploitative Abuse of Dominance under EU Competition Law

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MMMiroslava MarinovaUniversity of East LondonCBChristian BergqvistBakulev Scientific Center for Cardiovascular Surgery Russian Academy of Medical Sciences

Key Points

  • This article investigates whether EU competition law effectively addresses algorithmic price discrimination that harms consumers.
  • Analyzed existing literature on algorithmic price discrimination and tacit collusion.
  • Examined the applicability of Article 102(a) of the Treaty on the Functioning of the European Union.
  • Evaluated the effectiveness of current EU competition law frameworks.
  • Identified gaps in the current EU competition law regarding algorithmic price discrimination.
  • Argued for stronger enforcement measures under Article 102(a) to protect consumers.
  • Highlighted the potential for algorithmic pricing to lead to exploitative practices.

Abstract

ABSTRACT The development of artificial intelligence and the growing use of algorithms to optimize prices have generated significant debate about their benefits and potential adverse effects on competition and consumers. Two key issues dominate this discussion: algorithmic price discrimination through personalized pricing and algorithmic tacit collusion. Although the risks associated with algorithmic tacit collusion have been extensively studied, the potential harms from algorithmic price discrimination remain underexplored. This article examines algorithmic price discrimination from an EU perspective and whether the current EU competition law framework is adequate to tackle algorithmic price discrimination that harms consumers. It argues for robust competition law enforcement under Article 102(a) Treaty on the Functioning of the European Union to ensure that algorithmic pricing does not become a tool for exploitative abuse in the digital economy.

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Cite This Study

Marinova et al. (2026) studied this question.

synapsesocial.com/papers/69c4cc75fdc3bde448917bc6https://doi.org/10.1093/joclec/nhag006
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