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CCI flags rising competition risks in AI; collusion, data monopoly by big tech under lens
The CCI study also extends its scrutiny to AI’s user industries—sectors such as e-commerce, digital marketing, and retail. The study highlights that “control of a few large firms across the AI stack may create barriers to entry for smaller players.”
The report titled “Artificial Intelligence and Competition” highlights that large technology firms—or hyperscalers—hold a decisive edge in data access and computing resources.
Artificial intelligence (AI) may be India’s next big growth engine, but its rapid adoption across sectors has also exposed worrying competitive distortions, according to a market study by the Competition Commission of India (CCI). The study warns that entrenched Big Tech dominance, algorithmic collusion, and opaque AI models could reshape markets in ways that stifle innovation and consumer choice.
While AI has turbocharged efficiency, innovation, and predictive decision-making, the CCI notes that it also risks concentrating market power in the hands of a few technology giants who control the data, infrastructure, and foundation models that underpin the AI ecosystem.
The report titled “Artificial Intelligence and Competition” highlights that large technology firms—or hyperscalers—hold a decisive edge in data access and computing resources. Over years of operating massive digital platforms, these companies have amassed vast datasets, giving them a competitive advantage that startups cannot easily match.
The study highlights that “control of a few large firms across the AI stack may create barriers to entry for smaller players.” It points to data access, computing resources, and cloud dependence as major entry barriers, with global Big Tech players like Google, Microsoft, Amazon, and NVIDIA dominating the AI infrastructure layers.
Startups and smaller AI developers are compelled to depend on these firms for critical cloud and computational infrastructure, often through restrictive contractual arrangements. This dependence, the report cautions, creates a bargaining power imbalance and could foster long-term overreliance on a few players.
The study warns that such concentration could give rise to ecosystem lock-in, where users find it difficult to switch between platforms due to compatibility issues and high switching costs — effectively cementing the dominance of a few large firms.
Collusion by Code: The Rise of Algorithmic Coordination
Perhaps the most striking finding is the growing risk of algorithmic collusion — where AI systems, designed for profit optimisation, “learn” to align prices without any explicit human coordination. The study classifies these as monitoring, signalling, and self-learning algorithms, capable of reaching supra-competitive pricing outcomes autonomously.
The CCI notes that AI’s “black-box” nature complicates regulatory detection and enforcement. In global precedents such as the Topkins and GB Eye cases, AI systems were found to have tacitly coordinated pricing, mirroring cartel-like outcomes.
In India, 37% of surveyed startups cited AI-facilitated collusion as a key concern, followed by price discrimination (32%), predatory pricing (22%), and new or heightened entry barriers (22%).
AI and User Industries: Collusion and Price Discrimination Risks
The CCI study also extends its scrutiny to AI’s user industries—sectors such as e-commerce, logistics, digital marketing, and retail. It finds that while AI integration has vastly improved operational efficiency, it has simultaneously introduced new competition risks.
Firms now employ AI-driven dynamic pricing systems that can adjust thousands of products’ prices in real time. While efficient, such systems can unintentionally lead to price alignment across competitors, effectively mimicking collusion.
Further, AI-enabled personalised pricing, which tailors prices to individual consumers based on behavioural data, can disadvantage vulnerable groups and erode consumer trust. This practice, the report notes, raises fairness concerns when consumers are unaware they are being charged differently.
The study points to increasing mergers, acquisitions, and partnerships across the AI stack, allowing Big Tech to consolidate control over data, chips, and talent. Practices such as self-preferencing—where dominant platforms promote their own AI products—and exclusive access to essential inputs could raise rivals’ costs or restrict market access.
“Control of a few large firms across the AI stack may create barriers to entry for smaller players,” the CCI observes, adding that removing these bottlenecks is critical to fostering a level playing field.
India’s regulatory framework, including the Competition (Amendment) Act, 2023, equips the CCI to address new-age market challenges such as hub-and-spoke cartels, deal-value thresholds, and AI-enabled anti-competitive conduct. Complementary efforts under the IndiaAI Mission, with an outlay of ₹10,300 crore, aim to expand compute infrastructure and support startups.
The CCI has recommended self-audits of AI systems for competition compliance, greater algorithmic transparency, and inter-regulatory coordination. It plans to organise workshops on “AI and Competition Compliance” and collaborate with international regulators to monitor global best practices.
The CCI’s findings encapsulate a key dilemma: AI is both a catalyst for innovation and a potential vector for market distortion. As self-learning algorithms become more autonomous, competition regulators face the urgent task of crafting frameworks that preserve innovation without enabling digital monopolies.
The report concludes: “AI is reshaping the competitive dynamics in both the AI industry and its user industries. While it brings about innovation and efficiency, it may introduce challenges related to market concentration, entry barriers, and anti-competitive practices.”
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