GOVERNING ALGORITHMS CARTELS: A CRITICAL APPRAISAL OF INDIAN COMPETITION LAW IN THE DIGITAL ECONOMY
AUTHOR – SREELAKSHMI LR* & DR. RENU MAHAJAN**
* STUDENT AT AMITY UNIVERSITY
** ASSOCIATE PROFESSOR AT AMITY UNIVERSITY
BEST CITATION – SREELAKSHMI LR & DR. RENU MAHAJAN, GOVERNING ALGORITHMS CARTELS: A CRITICAL APPRAISAL OF INDIAN COMPETITION LAW IN THE DIGITAL ECONOMY, INDIAN JOURNAL OF LEGAL REVIEW (IJLR), 6 (5) OF 2026, PG. 315-328, APIS – 3920 – 0001 & ISSN – 2583-2344.
Abstract
The digital economy have been transforming at an unprecedented pace, wherein artificial intelligence (AI) and machine learning algorithms was no longer mere productivity tools but has to be structural forces shaping the modern market dynamics. This research report have to be delivering an exhaustive critical appraisal of how algorithmic cartels was operating and challenging the existing frameworks of Indian competition law, specifically Section 3 of the Competition Act, 2002.[1] Traditionally, the competition jurisprudence were relying on an anthropocentric framework that require a “meeting of minds” to establish collusion. However, self-learning algorithms has to be capable of achieving tacit collusion without any human communication, which were creating a massive structural enforcement gap. The present study have been exploring the various typologies of algorithmic collusion, which was including the Messenger, Hub-and-Spoke, Predictable Agent, and Digital Eye scenarios. Through an in-depth doctrinal and empirical methodology, the analysis were evaluating landmark cases such as Samir Agrawal v. ANI Technologies Pvt. Ltd. and international precedents like United States v. Topkins and the RealPage litigation. Furthermore, the findings was assessing the recent Market Study on Artificial Intelligence and Competition released by the Competition Commission of India (CCI) in 2025, which were highlighting severe market concentration, such as NVIDIA holding 88% of the GPU market.[2]
The report has to be critiquing the proposed Draft Digital Competition Bill, 2024, arguing that while it introduce ex-ante regulations for Systemically Significant Digital Enterprises (SSDEs), it largely omit specific provisions for autonomous algorithmic price-fixing. The economic models, including Q-learning and Nash equilibrium theories, was proving that algorithms naturally gravitate towards supra-competitive pricing. Ultimately, the research recommend a paradigm shift towards rebuttable presumptions, the reversal of burden of proof, and the integration of algorithmic audits to preserve fair competition. The existing laws has to be evolving rapidly, or the invisible agreements of machines was permanently destroying consumer welfare.
Keywords: Algorithmic Collusion, Competition Act 2002, Artificial Intelligence, Digital Markets Act, Systemically Significant Digital Enterprises, Tacit Collusion, Ex-ante Regulation, Q-learning, Nash Equilibrium.
[1] The Competition Act, 2002 (Act 12 of 2003), s. 3.
[2] Competition Commission of India, “Market Study on Artificial Intelligence and Competition” 9 (2025).