CCI’s Market Study - What Competition Issues emerge in the AI Industry

We scriberes summarise - sharing portions of interest from Competition Commission of India’s  (“CCI”) recent market study on ‘Artificial Intelligence and Competition’ published on October 6, 2025. We highlight emerging concerns around market dynamics including data concentration, bargaining power imbalance, and dependency on dominant tech firms for infrastructure. Issues like algorithmic collusion, price discrimination, and high entry barriers risk limiting innovation and consumer choice. Stakeholders identified AI-driven collusion, price discrimination, and entry barriers as the most pressing challenges. 

1. Uneven Access to Data : big technology firms through years of operating large-scale platforms and services, they have accumulated vast datasets. As new AI firms and startups increasingly rely on the infrastructure and cloud offerings of these hyperscalers, data often flows back to the incumbents, (depending on the nature of the agreements) further reinforcing their data advantage.

2. Bargaining Power Imbalance: Big technology firms/hyperscalers are the primary providers of infrastructure, so the majority of AI developers and startups including new and upcoming players may have to enter into contractual arrangements in order to get access to infrastructure including high end computing capabilities. This leaves the startups with limited choice of suppliers creating bargaining power imbalance.

3. This also has implications regarding price and access related uncertainty.

4. A few major eco-systems may emerge, with users finding it difficult to switch from one ecosystem to another owing to compatibility issues and transaction costs leading to long-term dependency.

3. First Mover Advantage: usage of ready-to-use algorithms, APIs etc. by users to develop products or services. Any changes or updates to the fundamental algorithm may lead to need for complete rewrite or redevelopment for the user, effectively tying them to a single stack or a specific OEM. 

4. Algorithmic Collusion: enterprises use AI-driven pricing algorithms that may learn to align prices over time. This can lead to outcomes similar to price-fixing, even in the absence of direct human coordination, making detection and enforcement by regulators far more complex.

5. Entrenchment of Dominance and Increased Entry Barriers: enterprises that control vast datasets may be able to train more effective AI models, giving them a substantial competitive edge. This may entrench market power and create high barriers to entry for smaller or newer players, stifling innovation and reducing consumer choice.

6. Price Discrimination: AI enables enterprises to use consumer data to set personalised prices in real time. While this can increase efficiency, it may also raise competition concerns, particularly when consumers are unaware that they are being charged different prices or when vulnerable groups are systematically disadvantaged.

The following competition issues were considered the most significant by stakeholders interviewed by the CCI for its Market Study:

• AI-facilitated collusion (37%), 

• Price discrimination (32%) 

• New/increased entry barriers (22%). 

Predatory pricing (22%), 

• Reduced choice (15%), 

• Reduced transparency (15%)

• Entrenchment of dominance (7%) 

• Exclusionary practices (5%)

Figure 1: Competition issues in AI industry