On 30 October 2026 the Telecom Regulatory Authority of India (TRAI) released draft Guidelines on Responsible Use of AI in Telecommunication Networks and Provision of Telecommunication Services for consultation. It said the aim is to apply the national India AI Governance Guidelines consistently in the telecoms sector.
Key proposals
According to the consultation paper, as reported by PTI in The Hindu:
- Accountability for outcomes. Operators would be accountable for the results of AI systems in their networks and services, whether the systems were built in-house, bought from a third party or a mix of both.
- Risk classification. AI systems would be classed as high, medium or low risk, based on their importance to network operations, financial and operational outcomes, and possible effects on consumers.
- Board-approved AI policy. Each entity would need an internal AI policy approved by its board, covering risk classification, deployment approvals, incident management, human oversight, data governance and consumer complaints.
- Governance committees. Operators would set up dedicated AI governance and safety committees.
- Incident reporting. AI incidents would be graded critical, high, moderate or low, and critical and high-severity incidents would have to be reported to TRAI.
- Records. Operators would keep central databases of AI incidents and of consumer complaints about AI-related harm.
All AI systems would be subject to "appropriate human oversight". In the same week, India's IT ministry also published a draft framework for privacy-preserving access to data for AI training.
Wider significance
This is one of the first attempts by a telecoms regulator anywhere to write sector-specific AI governance rules. It could be a model for other national regulators.
Why it matters financially
India has one of the world's largest mobile markets, and its operators are rolling out AI in network management, fraud detection and customer service. Board-level policies, new committees, incident registers and reporting duties would all add compliance costs, and the outcome-based accountability shifts risk on to operators and their AI suppliers. TRAI has not published cost estimates.