AI’s Market Dominance: Built on Data, Driven by Control
[By Vashmath Potluri & Shubhranshu] The authors are students of NALSAR, Hyderabad. Introduction In December 2024, Asian News International (ANI) filed a copyright infringement suit against OpenAI, alleging that its large language models (“LLMs”) had reproduced ANI’s news content without consent. While the case is widely perceived as a test of India’s copyright regime, it reveals a deeper and more systemic competition law issue: OpenAI, backed by Microsoft’s infrastructural and financial resources, enjoys exclusive control over high-quality training data through Reddit and Stack Overflow, and privileged integration into Microsoft’s software and cloud ecosystems as its models power AI features across Microsoft 365 Copilot and GitHub Copilot via the Azure OpenAI Service.. In 2024, over 60% of professionals in India reported using tools like ChatGPT and Microsoft Copilot, signalling the rapid mainstreaming of generative AI. Yet Indian AI startups attracted only $92 million in funding that year, compared to $13 billion in the United States, an imbalance that highlights the structural disadvantage domestic firms face in accessing essential AI inputs like data, computing, and distribution. This article uses the ANI v. OpenAI dispute as a lens to introduce a competition law perspective that has been largely overlooked. It argues that OpenAI’s conduct may amount to abuse of dominance under Section 4 of the Competition Act, 2002 (“The Act”), and calls for a suo motu investigation by the Competition Commission of India (“CCI”). This argument proceeds in two parts. First, it defines the relevant market as upstream and downstream, comprising access to training data and development of Application Programming Interface (“API”) which are software tools that enable developers to integrate AI models into their products and services, to establish a denial of market access and vertical leveraging which refers to the use of dominance in one market, such as access to data, to gain an unfair advantage in another, such as enterprise-facing AI services. Secondly, it highlights doctrinal gaps in the Act to deal with non-pricing exclusionary conduct, which conduct restricts rival participation not through higher prices, but through control over essential inputs, technical lock-ins, and bundling arrangements. Accordingly, it proposes a two-pronged reform drawing inspiration from the EU, UK, and USA to strengthen the ex-ante framework of India’s competition regime in the era of AI. Delineating the Relevant Market: A Layered Approach A scrutiny of potential abuse of dominance by the CCI against OpenAI should begin with defining the relevant market under Sections 2(r), 2(s), and 2(t) r/w 19(7) of the Act. These sections together provide for traditional factors like substitutability, price sensitivity, and consumer choices, but they become inadequate in the context of generative AI, where market power is determined by access to high-quality training data and compute infrastructure. To address this, the article adopts a layered market structure: an upstream market for access to training data and a downstream market for API’s. This approach finds support in Shamsher Kataria v. Honda Siel Cars India Ltd., where the CCI held that the aftermarket for spare parts and services was distinct from the primary car market due to structural lock-in, limited alternatives, and information asymmetry. Though linked technologically, the markets were considered economically independent by the CCI. This reasoning directly applies here. In Upstream, access to high-value training data is scarce and non-replicable, granting early movers like OpenAI a durable edge. In Downstream, developers integrating proprietary models via APIs face high switching costs, limited interoperability, and opaque performance metrics. These conditions result in technical and contractual lock-ins, which create sustained reliance on the dominant provider’s ecosystem. Together, these combined features justify treating the training and deployment layers as separate, yet interrelated, markets. Upstream Market: Denial of Access to Training Data Section 4(2)(c) of the Competition Act, 2002 prohibits a dominant company from doing anything that leads to the denial of market access “in any manner.” In Umar Javeed, Sukarma Thapar, Aaqib Javeed v. Google LLC & Ors, this phrase was interpreted broadly to hold that unfair conditions, creation of technical barriers, or lack of transparency constitute denial of access. This applies directly to OpenAI’s conduct in the upstream market of generative AI, which involves access to large, high-quality datasets like news articles, coding forums, and online discussions. These data sources are essential for training LLM’s. However, the real advantage lies not in general access to data, but in control over high-quality, non-replicable datasets that significantly improve model performance. OpenAI’s exclusive deals with platforms like Reddit and Stack Overflow give it early access to high-quality conversational data crucial for fine-tuning large language models. Indian developers, however, face major hurdles: India’s copyright law lacks a text and data mining (TDM) exception, annotated datasets in local languages are scarce, and compute access remains prohibitively expensive. While there’s no formal refusal of access, these combined legal and infrastructural barriers make it commercially unviable for domestic firms to compete. This amounts to a constructive denial of market access, which constitutes an abuse under Section 4(2)(c) of the Act where exclusion occurs not through outright refusal but through systemic disadvantage. This pattern of exclusion is reinforced by OpenAI’s own GPT-4 Technical Report, which acknowledges the use of a mix of public and licensed data, highlighting the importance of access to curated datasets. Similarly, the UK Competition and Markets Authority (CMA) has cautioned that exclusive control over high-quality, non-public datasets can give certain firms an undue competitive advantage and restrict market competition. In its recent assessments of foundation models, the CMA has treated such data as a core input and highlighted the risk of market foreclosure resulting from closed data ecosystems. This framework provides a valuable basis for the CCI in applying Section 19(4) of the Act, which focuses on factors such as control over key inputs, barriers to entry, and the ability to operate independently of competitive constraints. Recognising data as infrastructure allows the CCI to identify exclusionary conduct even in markets where price or output manipulation is absent. OpenAI reflects this structure: it controls critical training data, is deeply integrated into Microsoft’s infrastructure, and
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