Safeguarding competition: Digital world will need policy intervention

India must act early to define what 'gatekeeper' firms in AI are, ensure that Cloud, compute, & chip providers are not allowed to self-enforce lockins, & force transparency in pricing

From a market of $3.2 billion in 2020, India’s artificial intelligence (AI) economy has nearly doubled to about $6 billion in 2024, and is expected to reach $32 billion by 2031. The Competition Commission of India’s recent “Market Study on Artificial Intelligence and Competition”, however, identifies obstacles that threaten to make this growth extractive rather than inclusive. Some of these include data-access barriers, talent shortages, and high Cloud storage costs. These are not small frictions. Instead, they act as strong barriers to entry for smaller firms and disincentivises them from innovating meaningfully. Compounding the problem, global behemoths like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud already dominate AI in India, starting from data storage to computing power. AWS holds over 32 per cent of India’s Cloud market, and Nvidia, Intel, and AMD monopolise high-end AI semiconductor chips. The report further highlights that 37 per cent of the surveyed AI startups stated facing algorithmic price collusion by big-tech, and others flag AI-enabled price discrimination and predatory pricing, thus threatening consumer welfare and transparency.

 

India is not alone in facing such issues. Europe, for example, has its Cloud and AI Development Act, aiming to triple data-centre capacity in five to seven years and to strengthen sovereignty over AI infrastructure. The European Union is also imposing stricter regulation under its Digital Markets Act (DMA), demanding that some Cloud and AI services be treated as core-platform services to prevent incumbents from locking in market power. In the United States, antitrust agencies have opened probes into major AI players like Microsoft and OpenAI, especially scrutinising deals and partnerships that may give dominant firms privileged control over data, chips, or Cloud infrastructure. Even China is legislating for domestic supply mandates for AI-chips in public data centres to reduce dependence on foreign providers. There are several lessons for India. First, the growing size of the AI economy alone is not enough. Without checks, the explosion of data, infrastructure, and capital will concentrate power in the hands of a few, replicating the digital monopolies elsewhere. Second, regulatory slack or delayed responses cost opportunities. India must act early to define what “gatekeeper” firms in AI are, ensure that Cloud, compute, and chip providers are not allowed to self-enforce lockins, and force transparency in pricing and algorithmic behaviour.

 

While the NITI Aayog’s “National Strategy for AI” and other initiatives launched by the Ministry of Electronics and Information Technology seek to address issues surrounding AI governance and algorithmic transparency, using competition law as a key instrument for addressing AI-driven anti-competitive practices remains equally important. In this regard, the CCI’s recommendations for self-audits of AI systems, algorithmic transparency, and regulatory coordination are timely and necessary, but limited. They are the floor, not the ceiling. More needs to be done. This includes enacting ex-ante regulation, protecting smaller innovators through data trusts, opening data mandates, and imposing penalties for discriminatory pricing and algorithmic collusion even in the absence of explicit coordination. Thus, democratising data, regulating infrastructure, and preventing the concentration of market power remain the key to achieving AI and data sovereignty.