Some AI tools unfairly impacting online prices, shows a CCI report: Can regulators rein in the algorithm?

On Monday, CCI published a market study on AI.

A market study released by the Competition Commission of India (CCI) earlier this week has brought to focus what could be a challenging impact of Artificial Intelligence (AI) from a competition standpoint.

The CCI report observed that AI-driven price discovery is now being used as a strategic tool by some businesses to drive revenue optimization. However, these AI strategies introduce regulatory risks such as a lack of transparency. The report cautioned that AI could be used to implement predatory strategies by targetting below-cost pricing aimed at price-sensitive customers or those at risk of switching, while keeping prices unchanged for other consumers.

Retail sellers, including quick commerce and e-commerce platforms, and even ride hailing apps have been deploying AI tools to adopt various strategies such as dynamic pricing, or targetted and personalized pricing.

The study was conducted by the Management Development Institute, Gurgaon.

“AI-driven dynamic, targeted, and personalised pricing can serve as powerful tools for efficiency, innovation, and consumer benefit, while also introducing potential competition and consumer protection risks. Pricing algorithms pose competition risks through algorithmic collusion and algorithmic unilateral conduct, enabling precise price discrimination and highly targeted predatory pricing. The market study released by the CCI on October 6, 2025 also recognises this,” said Aparna Mehra, partner, Trilegal.

Competition experts have warned that unchecked AI pricing models pose a significant antitrust risk such as human cartels. These advanced algorithms could also learn to collude with rivals' systems, leading to predatory pricing and market manipulation.

For example, if e-commerce Site A's AI raises the price of an LED TV due to high demand, Site B's AI might mirror that price instead of undercutting it. This algorithmic synchronisation artificially inflates costs, harming consumers and over-riding genuine competition. Regulators face the challenges in proving such subtle, automated coordination.

“From a competition-law standpoint, the forward-looking risk is algorithmic coordination—systems that ‘learn’ market responses and, over time, align prices or other competitive parameters without human agreement or a classic “meeting of minds.” That can mimic collusion or predatory strategies and produce exclusionary effects, even where individual firms intended only to optimise revenues. The legal inquiry will increasingly turn on effects and governance, not just intent.” Said Hardeep Sachdeva, Senior Partner, AZB & Partners.

Globally, regulators have started to bring in safeguards to ensure AI-led price collusion doesn’t happen. There have already been instances such as David Topkins case in the US, E-Turas case in Europe, where regulators have acted against AI determined pricing models.

"The rise of AI is reshaping industries and consumer behavior, bringing both opportunities and regulatory challenges. The CCI’s AI market study is a crucial step, offering a roadmap to balance innovation with fair competition, and it expects businesses to embed transparency, accountability, and compliance into their AI strategies from the outset," said Vaibhav Choukse, Partner--Competition Law, JSA.

Self-regulation is key to mitigate these AI related risks, competition experts have said, as it will be near to impossible for regulators such as CCI to analyse each AI being deployed by various companies. Also, these AIs are key tools for price optimization for e-commerce sites.

Hence, the regulators may be required to develop a self-regulation mechanism, allowing the platforms to take a call instead of creating blanket regulations for all, experts said.

Even the CCI report has recommended a self-audit mechanism. “The introduction of a self-audit framework for enterprises deploying AI systems, particularly those with market power or wide consumer reach, will help assess and align their algorithms with competition norms," the study said.