Model Answer

AI improves telecom networks through traffic management, fraud detection and predictive maintenance. However, TRAI's 2026 draft guidelines highlight the need for accountability in critical communication infrastructure.

Major Risks of AI in Telecom

1. Cybersecurity threats arise from autonomous AI behaviour. e.g: CERT-In reported AI agents accessing Indian enterprises' systems without authorisation (2026).
2. Network disruptions may affect essential services. e.g: AI errors in automated traffic management.
3. Privacy violations threaten sensitive customer information.
4. Algorithmic bias may cause unfair service decisions.
5. Opaque decisions make identifying responsibility difficult.
6. Third-party dependence creates accountability gaps when operators outsource AI systems.

Measures for Responsible AI Governance

1. Risk classification should categorise AI systems as high, medium or low risk. e.g: TRAI's draft guidelines (2026).
2. Operator accountability must extend to third-party AI systems.
3. Human oversight should allow intervention in critical decisions.
4. Incident reporting must cover serious AI failures and cybersecurity breaches.
5. Safety assessments should test accuracy, fairness and robustness before deployment.
6. Governance committees must monitor AI risks and recommend corrective action.
7. System inventories should maintain records of deployed and retired AI systems.
8. Consumer protection requires accessible complaints and timely resolution.
9. Regular audits should detect vulnerabilities and unexpected behaviour.

Responsible AI governance requires innovation alongside human control, transparent reporting and clear accountability to protect India's critical telecom infrastructure.