TRAI Proposes Strict AI Guidelines for Telecom Sector with Board-Approved Policies and Risk Classification

TRAI Introduces Comprehensive AI Governance Framework for Telecom Sector

The Telecom Regulatory Authority of India (TRAI) has released draft guidelines for the responsible use of AI in telecommunication networks and services, marking a significant regulatory intervention in how telecom operators deploy artificial intelligence1

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. Released on October 30, 2026, these draft guidelines for AI establish a structured accountability framework that applies to all entities holding telecom service licenses or authorizations who use or intend to use AI systems. The framework builds on the India AI Governance Guidelines released by the government in February 2026, which are anchored in seven guiding principles: Trust is the Foundation, People First, Innovation over Restraint, Fairness & Equity, Accountability, Understandable by Design, and Safety, Resilience & Sustainability2

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. Industry stakeholders and interested parties can submit their written comments and suggestions by November 27, 20262

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Board-Approved AI Policies and Risk Classification Requirements

Under the proposed AI governance framework, telecom operators must adopt board-approved AI policies governing AI use and classify each AI system according to risk level1

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. Each entity must classify its AI systems as high, medium or low risk based on their significance to network operations and service delivery, their impact on financial and operational outcomes, and potential implications for consumers1

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. The use of any AI system requires approval from a designated officer, with the level of approval potentially varying according to its AI risk classification1

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. Internal AI policies and subsequent amendments must be filed with TRAI within seven working days of coming into effect1

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. Each operator must review its AI policy at least once a year to ensure continued compliance and relevance3

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Mandatory Incident Reporting and AI System Inventory

The draft guidelines establish a formal mechanism for incident reporting requiring telecom entities to maintain a central database of AI-related incidents, classify them by severity, and follow predefined standard operating procedures to address disruptions1

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. Critical and high-severity incidents, including material malfunctions and recurring failures, must be reported to TRAI in a prescribed format and timeframe1

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. Operators must classify AI-related incidents into four severity levels and record every one systematically3

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. TRAI may use these reports for sector-wide learning, risk assessment, advisories, preventive measures, and other lawful regulatory purposes3

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. Telecom entities are required to maintain an up-to-date inventory of all active, inactive and decommissioned AI systems, recording their source, purpose and risk classification, with no AI system permitted for use unless included in this inventory1

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Accountability for AI Systems Including Vendor AI

In a significant provision regarding accountability for AI systems, the draft makes telecom operators accountable for the outcomes of all AI systems they use, whether developed in-house or procured from third parties1

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. This includes vendor AI systems bought from outside suppliers. Before acquiring an AI system, operators must check the credibility of the supplier, soundness of the AI system and its limitations, and the suitability and quality of data used for training3

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. Operators must write enforceable terms into supplier contracts covering regulatory compliance, audit and inspection rights, incident management, risk allocation and accountability3

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. This accountability extends to AI that TRAI already requires, such as AI-based spam filters for calls and SMS mandated in 2023, meaning operators would be accountable when these filters make mistakes3

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Human Oversight and Impact Assessment Requirements

The internal policy framework must provide for human oversight, data governance, consumer protection and grievance redressal1

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. People must supervise every AI system to ensure fairness and transparency3

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. Before deploying a new AI system or modifying an existing one, companies must undertake validation, conformity and impact assessments covering parameters such as accuracy, robustness, explainability, fairness and resilience to model drift1

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. Robustness means the system keeps working reliably in different conditions, while explainability means people can understand why it produced a result3

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. Operators must also check for drift, where a system's performance worsens over time as real-world data changes3

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. AI-related harms reported by users must be addressed within a reasonable timeframe through a predefined mechanism for consumer protection1

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AI Governance Committee and Strategic Importance

To oversee compliance, each entity must establish an AI Governance and Safety Committee with board approval1

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. The committee must include representation from network operations, service delivery, information technology, data management, regulatory affairs and consumer affairs, headed by a senior executive designated as the AI Governance and Safety Officer1

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. The committee will review AI system performance at least once every financial year and identify vulnerabilities, weaknesses in oversight, fairness concerns and emerging risks, with corrective action potentially including modifying or decommissioning an AI system1

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. The Ministry of Communications emphasized that the telecom sector forms a key part of India's digital infrastructure, supporting public connectivity, essential government services, trade and commerce, and the functioning of critical information infrastructure, while also playing a crucial role in national security and emergency response2

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. This makes responsible AI deployment particularly important in the sector as AI is increasingly being integrated into telecommunication networks and provision of telecommunication services2

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. The draft consultation paper is available on TRAI's official website for stakeholder feedback2

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