Market concentration could harm India's emerging AI ecosystem, experts say

Even as India’s capabilities in artificial intelligence (AI) are gaining global attention during the ongoing India–AI Impact Summit 2026, experts caution against the monopolistic tendencies that could hinder the digital sovereignty within the country’s emerging AI ecosystem. The concern is that the strengths of domestic AI start-ups are more predominant in the downstream side of AI ecosystem where AI models are deployed for sector specific applications through model fine-tuning while the upstream data layer is primarily dominated by fewer global players.

Concerns over competition and digital sovereignty in India’s AI ecosystem

One of the sessions in the Summit itself saw experts pointing out concerns around competition and digital sovereignty within India’s AI ecosystem after identifying the slow pace of enforcement, with cases moving from the CCI to the Supreme Court of India, often by which time technological change renders remedies ineffective, as one of the key challenges.

The speakers at the session - Competing to Innovate: How Competition Accelerates AI Innovation – pointed out that market concentration is increasing at the foundation model and infrastructure levels, where high capital requirements, advanced computing needs, and control over cloud and semiconductor resources create significant barriers to entry. Dominance in operating systems, browsers, and app stores further entrenches incumbents. Vertical integration across infrastructure and downstream platforms raises risks of self-preferencing, bundling, and restrictive terms that may constrain startups and weaken contestability, the experts flagged.

Incidentally, the findings of a market study carried out by Management Development Institute (MDI), Gurugram for Competition Commission of India (CCI) and published by CCI last year had also identified concentration in the AI value chain, ecosystem lock-in and switching costs, self-preferencing, novel risk of algorithmic collusion, price discrimination, opaque algorithms and even collaborations and partnerships to some extent, as challenges from a fair competition point of view.

The AI industry tends towards concentration due to high upfront costs, access to data, compute and talent. This may give the incumbents substantial and often insurmountable competitive edge, thereby leading to entrenched market power and high barriers to entry for smaller or newer players, who may find it difficult to overcome structural hurdles such as enormous computational requirements, lack of data, or the need for significant user bases to achieve network effects, the study had pointed out. In addition, there could be a situation where few major ecosystems emerge with each having distinct locked-in user base. In such a scenario, users may find it difficult to switch across ecosystems, leading to long-term dependency, the report said.

Exclusive AI deals may distort competition: CCI study

On collaborations and partnerships, the CCI commissioned study found that the agreements and collaborations entered into by large players, can have significant implications for competition, depending on the terms of such arrangements. For instance, exclusive deals for cutting-edge AI chips, data etc. can raise rivals’ costs or deny them essential capabilities. These factors contribute to a risk of reduced market dynamism with fewer startups scaling up and less pressure on incumbents to innovate or price competitively, the study had pointed out.

The study had said that in order to promote development of a competitive AI ecosystem in India, to prevent AI-driven anti-competitive practices and to protect consumer welfare, CCI’s enforcement and advocacy efforts need to be directed towards developing a culture of competition compliance, ensuring fair competition across the AI development value chain and applications and preserving and promoting incentives for innovation.