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Artificial intelligence may be transforming how businesses compete, but if their algorithms are tilting the playing field, the Competition Commission of India (CCI) wants them to find out before it does.

In September 2025, the CCI released a Market Study on Artificial Intelligence and Competition (study) to understand the AI stack and the competition concerns swirling around AI markets in India. But the study does more than diagnose problems. It recommends that businesses be proactive and undertake a self-audit of AI systems, particularly if deploying AI in their essential business functions.

This is not the first time the CCI has nudged industries towards self-regulation in its market studies. It has previously recommended similar measures for cab aggregators in the context of surge pricing and for e-commerce platforms. Expertise gathered during such market studies typically informs the CCI’s market interventions.

More recently, the CCI chairperson signalled that the regulator was “getting ready” to act on AI-specific anti-competitive practices and emphasised self-audits to ensure that “there aren’t any hidden anti-competitive outcomes”. The message is clear: if businesses’ AI systems engage in any of the at-risk practices identified by the CCI, then they could find themselves in the CCI’s line of fire.

So, what counts as an at-risk practice? The study flags several practices that deserve closer scrutiny: AI-facilitated collusion, targeted or dynamic price discrimination, predatory pricing, self-preferencing of a company’s own products or services over rivals, and tying and bundling. If these sound familiar, businesses may come into view of the study’s crosshairs.

AI self-audit framework: Six pillars

The study lays out a framework built around six pillars: governance, algorithm design, testing, monitoring, transparency and compliance integration. It includes a Guidance Note for Self-Audit, offering practical tools: tasks organised around each pillar, an implementation process, guidance on documentation to be maintained and a self-audit checklist.

Who should pay attention?

If companies deploy AI-based algorithms, particularly those undertaking at-risk practices, or if they hold significant market power and consumer reach, the self-audit framework is designed with them in mind. The question is not whether the CCI will scrutinise AI-driven markets, but when.

What should businesses do?

The good news is the study does not expect companies to overhaul their operations overnight. The approach is meant to be proportional. As a first step, businesses should evaluate their algorithms for potential competition risks at the design stage and continuously monitor them at the deployment stage, calibrating the depth of the self-audit. Safeguards ultimately need to be in place at both these stages.

From there, companies can take stock of the documentation they already have, including system architecture records, any existing competition risk assessments, and records of decision-making processes and oversight mechanisms. Cross-functional teams, bringing together management, legal and engineering, can be deployed to map out the objectives behind the company’s algorithms and scrutinise design choices for any unintended anticompetitive effects. One area that warrants particular attention is the use of third-party tools or integrations that could facilitate access to a competitor’s commercially sensitive information, potentially leading to collusive outcomes. Business teams should also walk through the study’s self-audit checklist to assess whether their current internal controls are robust enough to address identified risks.

Early AI self-audits cut risk

In the age of disruptive technologies, regulation is evolving to keep pace. Timely self-audits will help companies demonstrate responsible AI use and reduce enforcement risk as the CCI sharpens its focus on AI-driven competition issues. Regulatory approaches are converging. As a socio-technical development, AI has far-reaching implications across human rights, privacy, competition and intellectual property, calling for a proactive framework for risk assessment and mitigation. Companies that act early and do an AI self-audit will be better positioned when the regulatory spotlight intensifies.

Ram Kumar Poornachandran is a senior partner and Anjali Kumar is a senior associate at AZB & Partners. Pavan Kalyan and Palak Jagetia, both associates, contributed to the article