THE IMPACT OF ARTIFICIAL INTELLIGENCE AND MACHINE ALGORITHMS ON COMPETITION LAW FRAMEWORK IN INDIA

Abstract

The rapid integration of Artificial Intelligence (AI) and machine learning algorithms into digital markets has significantly transformed business practices and competitive dynamics across jurisdictions, including India. While algorithm-driven technologies have enhanced efficiency, transparency, and consumer choice, they have simultaneously introduced complex challenges for competition law enforcement. This paper critically examines the impact of artificial intelligence and machine learning algorithms on the Indian competition law framework, with a particular focus on algorithmic price-fixing, data-driven collusion, discriminatory pricing, and personalised advertising. It explores how self-learning algorithms can facilitate tacit coordination among firms without explicit human intervention, thereby undermining traditional notions of agreement, intent, and liability under the Competition Act, 2002. The study highlights the growing difficulty faced by competition authorities in detecting and regulating anti-competitive conduct in digital markets where pricing and strategic decisions are increasingly automated. Through doctrinal and analytical research, the paper evaluates whether the existing legal provisions—especially those relating to anti-competitive agreements—are sufficiently equipped to address AI-driven collusion and market distortions. It argues that while AI and algorithms offer undeniable economic benefits, their unchecked deployment poses serious risks to market fairness and consumer welfare. The paper concludes by emphasising the need for a nuanced and adaptive competition law framework in India, capable of balancing innovation with effective regulation, and calls for regulatory clarity to address emerging challenges posed by intelligent, autonomous systems.