Artificial intelligence, digital platforms and market competition: Algorithmic pricing, ecosystem power, data-driven dominance and regulatory contestability in contemporary digital markets

This paper examines how artificial intelligence and digital platforms are transforming competition in contemporary markets. Drawing on recent literature, it analyzes three interconnected dimensions: algorithmic competition, platform and ecosystem power, and the adaptation of competition policy to digital-market structures. The review shows that artificial intelligence can improve prediction, innovation and operational efficiency, while also creating conditions for supracompetitive pricing, personalized extraction of consumer surplus and persistent technological advantages. Digital platforms generate comparable tensions through network effects, data accumulation, multi-sided interactions and control over ecosystem governance. These mechanisms can expand market access, reduce transaction costs and support complementary innovation, but they may also strengthen dependence, raise entry barriers and reinforce incumbent positions. The paper further shows that traditional indicators such as prices, market shares and narrowly defined market boundaries may be insufficient to capture competition in digital environments. Data access, multihoming, interoperability, complementor dependence, innovation trajectories and potential competition increasingly shape market outcomes. The findings therefore support a dynamic and ecosystem-based approach to competition analysis. Regulatory intervention should preserve innovation and efficiency-enhancing coordination while addressing practices that transform data, interfaces, algorithmic capabilities or platform control into durable obstacles to entry, rivalry and market contestability