A Competition Commission of India (CCI) report published on Monday highlighted concerns over restricted data access, dependencies on cloud vendors like AWS and Microsoft Azure, and unequal partnership terms.
“Hyperscalers have built layers of software on top of the hardware to make it easier for smaller businesses and startups to scale,” Srikanth V, cofounder of enterprise artificial intelligence firm Fractal Analytics, said. “Companies like Yotta, Neysa and E2E offer these services, but not at the same level. That’s why startups choose the big players’ services, even if they are more expensive,” he added.
India’s antitrust watchdog has stated that the concentration of data, compute resources and ownership of closed AI models by a few large players could create new monopolies.
CCI has recognised that AI poses the risk of collusion, price discrimination, and gatekeeping by large players.
As per the commission, 37% of surveyed startups flagged potential for AI-enabled collusion on algorithms. Price discrimination and predatory pricing risks were reported by 32% and 22%, respectively, the study showed.
Manav Garg, cofounder of AI-focused venture capital firm Together Fund, said what is required now is to provide startups architect independence from the start.
“You can’t afford to be locked into one cloud or model provider, because the pace of change in AI means today’s partner could become tomorrow’s competitor. The smartest founders are spreading their dependencies across multiple hyperscalers and even open-source systems to stay nimble,” he said.
Global watchdogs like the European Commission, the UK’s Competition and Markets Authority, and the US Federal Trade Commission have also raised concerns about AI-driven market dominance.
“AI, by nature, can be both disruptive and democratising,” said Devroop Dhar, cofounder and India CEO of investment advisory firm Primus Partners. He explained that the emergence of new players like OpenAI, Anthropic, Perplexity and Mistral show that AI is expanding competition, not contracting it.
“But the challenge lies in ensuring responsible development, ethical data use, and fair access to AI infrastructure. That’s where collaborative frameworks, open innovation ecosystems, and voluntary standards play a critical role,” Dhar said.
Unnati Agrawal, partner at law firm Induslaw, cautioned that large data firms like Google can use dominant position “to leverage sales of their other products, as well as create entry barriers for emerging startups (who would need such data to effectively compete in the market).”
Experts said regulators must mandate more than just self-audits.
These may include disclosure standards, audit frameworks, regulated access for datasets/models, and incentives or funding to build alternative infrastructure, said Vishal Maru, global processing head at bank-tech firm FSS.
The CCI report also provides guidelines for self-audit of AI systems and framework to improve transparency and reduce information asymmetry.
“The real test will lie in how effectively these frameworks translate into on-ground enforcement and cross-sector coordination,” said Gauri Chhabra, partner at law firm Trilegal.
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