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Introduction
The Competition Commission of India (CCI) has released a pivotal "Market Study on Artificial Intelligence and Competition" report on 6 October 2025 (Report). This six-chapter document provides a foundation for the regulatory response to artificial intelligence (AI) in India.
The Report covers AI fundamentals (framework, market, and industry applications in e-commerce, finance, and healthcare). The key actionable insights for enterprises and the regulator are summarized below.
Key Competition Concerns Raised by AI
The CCI has identified six primary areas where AI could raise antitrust issues, summarized in the table below:
|
Concern Area |
Description |
Competition Risk Highlighted |
|
Algorithmic Coordinated Conduct |
AI-driven pricing algorithms leading to tacit collusion (e.g., self-learning algorithms autonomously maximizing profit and adapting to achieve collusive outcomes). |
Anti-competitive market outcomes without explicit agreements. |
|
Algorithmic Unilateral Conduct |
Dominant firms using AI to abuse their position (e.g., self-preferencing, targeted predatory pricing, tying/bundling). |
Exclusionary and exploitative practices that harm competitors and consumers. |
|
Pricing Practices |
Use of dynamic, personalized, and targeted pricing (e.g., tailoring prices to individual willingness to pay, with 52% of firms using dynamic pricing). |
Lack of transparency and potential unfairness for consumers, especially vulnerable groups. |
|
Entry Barriers |
Resource concentration making it difficult for startups (e.g., 68% of startups cite data availability as a challenge, 61% cite cloud costs/talent shortages). |
Reduced innovation due to control of essential resources (data, compute, talent) by established players. |
|
Reduced Transparency & Choice |
Opaque "black-box" algorithms and limited supplier options creating uncertainty and dependency for smaller players. |
Ecosystem lock-in, hindering compliance, innovation, and effective competition. |
|
M&A and Partnerships |
Acquisitions and alliances that expand power across the AI stack, gaining access to data and technology (e.g., acquisitions by Gupshup, big tech partnerships). |
Potential for foreclosure, dependencies, or reduced competition in emerging markets. |
Action Plan for a Competitive AI Ecosystem
The Report provides a dual-pronged approach: Best Practices for Enterprises and Governance Measures for the Regulator/Government.
- Best Practices for Enterprises
(Compliance)
Enterprises are strongly urged to proactively embed competition compliance into their AI systems by implementing self-audit systems explained below: -
- Self-Audit of AI Systems:
|
Audit Focus Area |
Key Actions for Compliance |
|
Governance & Oversight |
Establish systems to evaluate competition risk; involve senior management in high-risk AI deployments; document all decision-making. |
|
Algorithm Design & Development |
Review programmed objectives; assess training data for bias; document design choices and expected market effects. |
|
Testing & Validation |
Run controlled experiments to test for unintended anti-competitive effects; validate across multiple market scenarios. |
|
Monitoring & Control |
Implement continuous behavior monitoring; set triggers for human review of decisions; maintain detailed audit logs. |
|
Transparency |
Ensure explainability of core functions; enable disclosure of key parameters to stakeholders; create concern-reporting mechanisms. |
|
Compliance Integration |
Train technical teams on competition law; integrate competition review into the overall risk assessment and compliance program. |
The Framework Implementation Process is a six-step sequence that
begins with Preparation (assembling the team and identifying AI
systems) and System Mapping (documenting AI logic). This is
followed by a Risk Assessment to pinpoint high-risk areas, leading
to a Detailed Audit where the compliance checklist is applied.
Finally, Findings & Recommendations (developing
prioritized fix plans) are translated into action during the
Implementation & Follow-up stage (carrying out remedial actions
and scheduling re-assessments).
- Improve Transparency:
The Report highlights that opaque AI decision-making can harm competition and consumers by concealing unfair practices and limiting choice. It urges enterprises to improve transparency by explaining how and why AI is used, outlining key decision parameters, and sharing this information clearly and regularly. These steps aim to reduce information asymmetry and build trust without revealing proprietary details.
- Governance measures (CCI & Government)
The CCI has suggested measures to build regulatory capacity and reduce market barriers:
|
Governance Area |
Proposed Action by CCI / Government |
|
Focused Advocacy |
Organize a conference on "AI and Regulatory Issues"; conduct workshops on "AI and Competition Compliance" for market sensitization. |
|
Removing Entry Barriers |
Expand national computing resources for startups/MSMEs; promote open-source frameworks; develop high-quality, non-personal data repositories. |
|
Regulatory Capacity Building |
Strengthen the CCI's technical capabilities in AI/data science; set up a Think Tank of academics and policy experts on digital markets. |
|
Inter-regulatory Co-ordination |
Maintain open channels with other regulators (e.g., data protection, cybersecurity); explore MoUs for structured consultation. |
|
International Cooperation |
Collaborate with global competition authorities through cooperation agreements; participate in multilateral platforms (OECD, ICN) to adopt best practices. |
Comments
The release of this Report marks a definitive step towards integrating AI oversight into India's antitrust framework. By clearly articulating the risks, from algorithmic collusion and unilateral conduct to heightened entry barriers, the Report sets a critical foundation. Equally, it signals the CCI's strong intent to actively monitor and regulate the AI landscape. A proactive self-audit using the framework provided is the immediate key step to ensure your AI systems and pricing practices are fully compliant with Indian competition law.
The content of this document does not necessarily reflect the views / position of Khaitan & Co but remain solely those of the author(s). For any further queries or follow up, please contact Khaitan & Co at editors@khaitanco.com.
