CCI flags AI-driven competition risks for digital marketplaces

CCI chairperson Ravneet Kaur said AI could amplify self-preferencing, discriminatory pricing and algorithmic collusion in India’s digital markets, urging compliance audits and greater transparency from platforms.

— Source publishedMon, 7 Sept, 2026, 22:28 IST·First seen Mon, 7 Sept, 2026, 22:32 IST·Source Inc42 · Buzz

What happened

Competition Commission of India (CCI) · CCI chairperson Ravneet Kaur warned that AI could intensify anti-competitive conduct in Indian digital markets,

Key facts

  • October 2025

Why this matters

Acquirers should add AI governance, algorithm transparency and competition-compliance diligence to evaluations of Indian marketplace targets.

What to watch

  • CCI publication of AI, algorithm, or digital-market compliance guidance.
  • CCI information requests, dawn raids, or investigations involving marketplace search, seller ranking, dynamic pricing, or private labels.
  • New seller-association or consumer complaints alleging suppressed visibility, discriminatory commissions, or price manipulation.
  • Evidence of correlated price changes among marketplace sellers using shared repricing tools.
  • Indian digital competition legislation or rules imposing ex ante obligations on large digital enterprises.
  • Platform changes requiring clearer labeling of ads, sponsored results, or personalized prices.
  • Map every AI system affecting price, search ranking, recommendations, ad placement, seller eligibility, and inventory allocation.
  • Create auditable logs showing model inputs, business rules, overrides, sponsored-content treatment, and outcomes across consumer and seller segments.
  • Review private-label and preferred-seller ranking treatment for disproportionate visibility, conversion, or fulfillment advantages.
  • Test personalized pricing and promotion systems for discriminatory outcomes and unintended competitor-price synchronization.
  • Establish board-level AI competition oversight with legal, product, marketplace, data science, and seller-policy owners.
  • Prepare a regulator-ready explanation of how ranking, pricing, and recommendations work without exposing unnecessary proprietary detail.

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