TRAI Chairman Anil Kumar Lahoti has called for responsible AI deployment, human oversight and auditability as telecom networks become more autonomous.
Telecom Regulatory Authority of India (TRAI) Chairman Anil Kumar Lahoti has called for stronger safeguards and human oversight as artificial intelligence becomes increasingly integrated into telecom networks.
Speaking at an event organised by the Cellular Operators Association of India (COAI), Lahoti said AI can significantly improve network management and threat detection, but greater automation must be accompanied by accountability, risk assessment and mechanisms that allow humans to intervene when automated systems go wrong.
His comments come as telecom operators and technology companies increasingly use AI for network optimisation, fraud detection, anomaly identification and other operational tasks.
TRAI Chief Wants Human Oversight for High-Impact AI
Lahoti said telecom operators and technology companies need to adopt responsible AI practices as automated systems become more deeply embedded in communications networks.
He specifically highlighted human oversight for high-impact AI systems, along with auditability and the ability to intervene when necessary. He also called for risk assessments, maintaining logs of AI decisions and testing models before they are deployed.
The emphasis is significant for telecom networks because automated systems can increasingly influence operational decisions without requiring manual intervention for every individual event.
Lahoti’s position, however, should not be interpreted as a new TRAI regulation mandating a particular AI architecture or a specific human-review process. His comments were framed around responsible deployment, safeguards and governance rather than announcing a new binding compliance framework.
Why AI Oversight Matters in Telecom Networks
AI systems can process enormous volumes of network information much faster than conventional manual systems. Telecom operators can use such systems to identify unusual traffic patterns, detect potential fraud, optimise network resources and identify problems.
However, automated decisions can also produce incorrect results.
A system designed to identify suspicious activity, for example, could incorrectly classify legitimate activity as potentially harmful. This is why mechanisms for reviewing important decisions and intervening when necessary become relevant as networks become increasingly automated.
Lahoti’s comments put particular emphasis on maintaining accountability even as telecom infrastructure becomes more autonomous.
AI Is Already Being Used for Telecom Security
The telecom industry is already using AI and machine-learning systems for several security and network-management applications.
These include identifying anomalous traffic, detecting potential fraud, forecasting network demand and improving resource allocation. Lahoti acknowledged these potential benefits while stressing that responsible deployment needs to accompany the technology’s expansion.
This creates a balance between automation and human decision-making.
For routine network events, automated systems can process information and respond rapidly. For higher-impact decisions, maintaining a clear route for human review can help operators investigate potentially incorrect or unexpected AI decisions.
Decision Logs Could Become More Important
Another area highlighted by Lahoti was the need to maintain records of AI decisions.
Decision logging can help operators understand what an AI system did, why it produced a particular result and whether the system behaved as expected. It can also provide a basis for investigating incidents involving automated systems.
For telecom companies, such records could become increasingly relevant as AI moves from analytics and recommendations towards automated network operations.
Lahoti also called for AI models to be tested before deployment, particularly when they are being used in high-impact applications.
TRAI’s Message Comes as Telecom AI Adoption Grows
The comments come at a time when India’s telecom sector is dealing with increasingly complex networks and large volumes of digital traffic.
5G networks, cloud-based network functions, automated fraud detection and AI-assisted operations are increasing the number of decisions that can potentially be handled by software rather than manually.
AI can help operators respond to network issues faster and process information at a scale that would be difficult for human teams alone.
At the same time, the growing role of automated systems makes questions around accountability and intervention more important, particularly when an automated decision could affect customers or critical network services.
India-UK Telecom Cooperation Also Focuses on Responsible Technology
Lahoti’s comments came around an India-UK telecom cooperation initiative involving COAI and the UK government. The cooperation covers areas including AI, digital connectivity, digital trust and responsible technology-led innovation.
The broader discussion reflects the increasing overlap between telecom policy and AI governance.
Telecom networks are becoming more software-driven, while AI is being used for functions that traditionally relied on predefined rules or human intervention. This makes responsible AI practices increasingly relevant to telecom regulators and operators.
What This Means for Jio, Airtel and Vi
For India’s major telecom operators, the direction highlighted by Lahoti points towards greater attention to governance around AI-based systems.
Reliance Jio, Bharti Airtel and Vodafone Idea are all operating increasingly software-driven networks and using automation across different areas of their businesses. However, Lahoti’s comments do not impose a new specific compliance requirement on these three operators.
Instead, the regulator’s message is that automation should not remove accountability.
As AI systems take on more responsibility for network management and threat detection, operators will need to consider how decisions are monitored, recorded, tested and reviewed.
TRAI’s AI Message Is About Responsible Automation
Lahoti’s remarks do not amount to a new TRAI rule mandating specific AI threat thresholds or external audits for telecom operators.
The broader message is about ensuring that AI deployment remains accountable as telecom networks become more autonomous. Human oversight, risk assessment, decision logging, model testing, auditability and intervention mechanisms were highlighted as important safeguards for high-impact applications.
For India’s telecom industry, the issue will become increasingly important as AI moves beyond analytics and into systems capable of making or triggering operational decisions.
The challenge for operators will be to capture the speed and scale benefits of automation while maintaining clear responsibility when an AI system makes an incorrect or unexpected decision.
