ALGORITHMS, DATA & DOMINANCE: A COMPETITION LAW STUDY OF BIG TECH PLATFORMS

Abstract

Digital platform markets have transformed the global economy by establishing a new model of value extraction built on data, algorithmic prediction, behavioural surveillance, and network effects. A small number of firms—Google, Amazon, Apple, Meta, and Microsoft—have leveraged their role as digital intermediaries to accumulate unparalleled economic and infrastructural dominance. Their business practices include self-preferencing, exclusionary product design, leveraging personal data across services, and imposing restrictive conditions on market participants. Traditional antitrust legal standards, primarily price-centric, struggle to address harms that manifest not as rising prices but as loss of choice, privacy intrusions, reduced innovation, and locked-in consumer dependency. This paper examines how competition authorities in India, the European Union, and the United States are adapting legal principles to the realities of algorithm-driven platform power. Through case studies, regulatory interventions, and policy developments such as India’s Digital Competition Bill (2024) and the EU’s Digital Markets Act (2023), the study evaluates shifts from reactive enforcement to proactive structural regulation. It concludes that digital markets require a hybrid enforcement model combining ex-ante rules, data governance, and algorithmic accountability to ensure fair contestability, preserve consumer autonomy, and prevent irreversible concentration of economic power.