Company boards must audit AI-led business practices for competition risks: CCI
Competition Commission of India Chairperson Ravneet Kaur said there is a likelihood that the use of AI may knowingly or unknowingly lead to breaching of fair market conduct rules, and company managements can act as a crucial first stage of assessment for the same.
Boards and management of companies using artificial intelligence tools for business growth must audit whether the deployment complies with fair market conduct rules, said Competition Commission of India Chairperson Ravneet Kaur.
Speaking at an event organised by CII, Kaur said there is a likelihood that the use of AI may knowingly or unknowingly lead to breaching of fair market conduct rules, and company managements can act as a crucial first stage of assessment for the same.
The first stage of intervention when adopting AI tools is to discuss self-audit, Kaur said, spelling out her expectations from the companies.
"Can the boards, the management of various industries that are adopting AI for business growth, also look at what can be the potential anti-competitive outcomes which may occur knowingly or unknowingly?" she requested.
Citing a study on AI and its challenges from a competition law perspective conducted by the panel a few months ago, Kaur said there are seven distinct risks that the use of AI portends.
These are algorithmic collusion, unilateral conduct, price discrimination, network effects, buying, and bundling strategic mergers and acquisitions, she said, adding that the Commission has only identified the risks and not come out with any prescriptions on the same as yet.
As per an official statement from the organisers, Kaur also said that the CCI aims to strike a balance, ensuring strong deterrence against anti-competitive conduct and an innovation-driven market environment.
Deal Value Threshold serves as a critical regulatory pillar, specifically designed to capture high-value digital acquisitions, she said.
She underlined the importance of dialogue in understanding market realities, ensuring regulatory clarity and promoting compliance, and added that the watchdog has been continuously refining its analytical tools and enforcement approaches.
India enters 2026 with an AI ecosystem shifting from demos to production-grade, domain-specific systems. The focus has moved to infrastructure that lowers compute barriers, edge and silicon initiatives suited for low-connectivity environments, and agentic platforms that solve business-critical problems.
Startups span areas such as semiconductor design (Maieutic), governed AI compute and private clouds (Neysa, Kluisz.ai), edge AI chips (Azimuth AI), and enterprise platforms that operationalise AI across workflows (UnifyApps, Revving.ai).
Others apply agentic AI to finance, analytics, cybersecurity, and sector-specific knowledge. Together, they signal a maturing ecosystem wherein AI success will depend less on novelty and more on integration, reliability, compliance, and control over infrastructure, models, and data.
(With inputs from PTI)