Transparency, Self-Audits Vital for Fair AI Markets: CCI
New Delhi: Artificial Intelligence (AI) is transforming India’s economic and competitive landscape at a pace that challenges traditional market structures and regulatory frameworks, the Competition Commission of India (CCI) said in a landmark market study released today.
Conducted through the Management Development Institute Society (MDIS), the Market Study on Artificial Intelligence and Competition examines the country’s AI ecosystem in depth—its structure, emerging competition issues, and the adequacy of current legal and regulatory responses.
The report finds that AI adoption in India is accelerating rapidly, reshaping competition, business operations, and regulatory priorities. The study’s findings, based on both primary and secondary research—including literature reviews, stakeholder interviews, and structured surveys—show that AI is no longer confined to experimental stages but has become central to business strategy and consumer engagement across sectors.
According to the study, the size of the global AI market has grown from USD 93.24 billion in 2020 to USD 186.43 billion in 2024, and is projected to reach USD 1 trillion by 2031. In India, the market has expanded from USD 3.20 billion in 2020 to USD 6.05 billion in 2024, and is expected to surge to USD 31.94 billion by 2031. This exponential growth is fuelled by the increasing use of AI in banking, healthcare, retail, logistics, education, and e-commerce—where it is deployed for dynamic pricing, demand forecasting, personalised recommendations, and automated decision-making.
The study outlines the AI industry stack, which includes the upstream (data, infrastructure, and development layers) and downstream (application and deployment layers). At the base lies the data layer, involving collection, processing, and labelling of data; the infrastructure layer provides computing resources like servers and AI-optimised chips through cloud and edge computing; and the development layer focuses on algorithms, programming tools, and foundation models such as large language models (LLMs). Downstream, AI models are fine-tuned for sector-specific use, integrated into decision-making systems, and run on high-compute resources.
Major global players dominate these layers—Appen, Amazon Web Services (AWS), Google, Microsoft Azure, ScaleAI, NVIDIA, Intel, and AMD—with startups beginning to emerge across segments of the Indian AI stack. India’s own AI startup ecosystem, the report notes, is vibrant and increasingly innovative. Around 67 per cent of surveyed AI startups operate in the application layer, focusing on deploying AI for end-use sectors. A significant 76 per cent rely on open-source technologies, 88 per cent use machine learning (ML), 78 per cent employ natural language processing (NLP), 66 per cent use generative AI (LLMs), and 27 per cent work in computer vision (CV).
The study’s primary research reveals a strong focus on customer analytics: about 90 per cent of firms use AI to monitor customer behaviour, and 27 per cent apply it for supply-chain efficiency. Nearly 69 per cent use AI for demand forecasting, 24 per cent for pricing trends, and 21 per cent for inventory predictions. Such tools enhance efficiency and productivity, offering competitive advantages through cost reductions and improved service delivery. However, the CCI cautions that firms not adopting AI risk losing competitiveness and consumer loyalty in an increasingly AI-driven economy.
While acknowledging AI’s vast benefits, the CCI report raises critical competition concerns. It warns of market concentration, data dominance, algorithmic collusion, and opaque pricing models that could distort fair competition. Based on startup perceptions, 37 per cent cited risks of AI-facilitated collusion, 32 per cent feared price discrimination, and 22 per cent highlighted predatory pricing. The study details four categories of pricing algorithms that raise red flags globally—monitoring, parallel (hub-and-spoke), signalling, and self-learning algorithms. Some of these systems, particularly self-learning ones using deep reinforcement learning, can autonomously adjust prices in ways that mimic collusive outcomes without explicit coordination among firms.
The report observes that the opaque or “black-box” nature of such algorithms complicates detection and enforcement, necessitating new regulatory tools and inter-agency cooperation. It adds that AI-driven price discrimination—targeting specific consumer groups based on predictive analytics—can erode trust and harm vulnerable consumers.
The CCI also flags structural challenges to competition in AI markets, including limited access to data, talent, computing power, and cloud services, all of which create entry barriers. These barriers, the report notes, favour large incumbents that control vast, high-quality datasets and have the financial means to train complex AI models. Smaller startups, by contrast, struggle with high infrastructure costs and limited data access.
To address these issues, the CCI highlights ongoing government measures, particularly the India AI Mission, which has earmarked ₹10,300 crore to strengthen India’s AI capabilities, expand compute infrastructure, and empower domestic startups. It recommends that government policy continue to prioritise affordable access to AI resources and capacity building to foster a level playing field.
The report acknowledges that mergers, acquisitions, and strategic partnerships are increasingly used by big tech and AI firms to consolidate their presence across multiple layers of the AI stack. While such collaborations can promote innovation, the CCI warns that they may also create anti-competitive dependencies, warranting closer scrutiny under competition law.
On the regulatory front, the study examines global and Indian frameworks aimed at ensuring responsible AI development. It notes that jurisdictions worldwide are focusing on algorithmic transparency, accountability, and AI governance. In India, key initiatives such as the National Strategy for AI (NITI Aayog, 2018), the National AI Portal, and various policy documents from the Ministry of Electronics and Information Technology (MeitY) reflect the government’s commitment to building a secure, innovation-driven AI ecosystem.
Legal reforms like the Competition (Amendment) Act, 2023—introducing provisions for hub-and-spoke cartels, deal-value thresholds, and settlement and commitment mechanisms—enhance CCI’s ability to respond to digital market challenges. Complementary efforts, including the Digital Personal Data Protection Act, 2023, demonstrate India’s integrated approach to fostering innovation while safeguarding fair competition and consumer interests.
To promote responsible autonomy and transparency, the CCI urges enterprises to incorporate self-audits of AI systems for competition compliance. The report includes a guidance note and an indicative framework for such audits, enabling businesses to identify potential risks proactively. It also encourages companies to adopt clear communication policies and transparency measures to reduce information asymmetry and maintain consumer trust.
In a forward-looking move, the CCI announced it will organise a conference on “AI and Regulatory Issues”, hold advocacy workshops on “AI and Competition Compliance”, and set up a dedicated think tank on digital markets with special focus on AI. The Commission will also enhance its technical capabilities and infrastructure, coordinate with other regulators, and engage with international competition authorities to share best practices.
The study findings mark a critical juncture in India’s economic and regulatory trajectory. The CCI’s analysis makes clear that the future of competition in India will depend not only on innovation and efficiency but also on transparency, accountability, and equitable access to AI resources. As AI continues to redefine how markets operate, the Commission’s call for responsible and fair deployment may shape the contours of India’s next phase of digital transformation.
– global bihari bureau
