From syntax to sense: Large Reasoning Models rewire telecom AI

The world is witnessing a remarkable surge in the capabilities of Large Language Models (LLMs)—systems that can compose, converse, and code with near-human fluency. Yet, even as these models reshape industries, they stand on the cusp of a far more transformative era—that of Large Reasoning Models (LRMs).

If LLMs gave the industry intelligent language, LRMs are equipped to provide intelligent logic. They mark the next evolution of artificial intelligence—moving from the ability to generate text to the ability to reason, infer, and decide. For India’s telecom and digital communications sector, this transition could be as consequential as the leap from 4G to 5G—redefining how their networks, systems, and institutions think, learn, and act.

How Reasoning Models Differ from LLMs

LLMs have been trained on vast datasets to predict the next word—mastering language but not necessarily logic. LRMs, by contrast, combine language understanding with structured reasoning. They can interpret cause and effect, evaluate multiple variables, and apply logical constraints to arrive at solutions that make sense both statistically and contextually.

This also means they can explain their thinking, adapt to complex environments, and handle multi-step decision processes—from policy interpretation to network optimisation. They move AI from “talking smart” to “thinking smart.”

Transforming Telecom and Communication Networks

The telecom sector on India is the nervous system of the country’s digital economy—powering initiatives such as Digital India, BharatNet, UPI, and ONDC. As India moves towards AI-native 6G networks and the vision of Viksit Bharat 2047, the introduction of LRMs can revolutionise every layer of the telecom stack—from infrastructure to customer interface.

Smarter network operations: Telecom networks generate vast amounts of real-time data. Today’s AI tools can analyse this data, but LRMs will go further—they can reason across performance metrics, interference patterns, and energy use to suggest or even implement optimised configurations. They can also infer why a fault might occur and pre-empt it before it affects service.

This could move operators towards truly autonomous, self-healing networks, improving uptime, reducing costs and enhancing customer experience.

Cybersecurity and fraud prevention: Telecom is increasingly at the front line of cybersecurity—from financial fraud to deepfake misuse. LRMs can reason through sequences of events, detect anomalous signalling behaviours and connect seemingly unrelated data points to flag coordinated attacks.

Their ability to simulate threat scenarios and generate logical defence strategies could help secure not just networks but the entire digital ecosystem—complementing initiatives such as the Financial Fraud Risk Indicator (FRI) and the Chakshu fraud-reporting platform.

Regulatory and compliance co-pilots: India’s regulatory architecture, spanning the Telecommunications Act 2023, TRAI directions, and the DPDP Rules 2025, is complex and dynamic. LRMs can act as intelligent assistants, reasoning through clauses, identifying overlaps or gaps, and cross-referencing compliance obligations.

Reimagining customer experience: While LLM-powered chatbots have improved customer interaction, LRMs can reason about customer intent and context. They can dynamically adapt service plans, resolve complaints by tracing root causes, or guide users toward optimal data use. All of this while remaining aligned with frameworks such as the TCCCPR 2018. This deeper, contextual intelligence will redefine digital trust and satisfaction for millions of consumers.

Accelerating Innovation and R&D: As India drives initiatives in ubiquitous connectivity, direct-to-mobile (D2M) broadcasting, in-device coexistence, and Quantum-resilient networks, LRMs can dramatically speed up innovation. By analysing experimental data, they can simulate how different parameters affect performance, thereby reducing the time from research to deployment.

This is particularly vital for India’s 6G research agenda, where design iteration and systems optimisation depend heavily on complex reasoning.

From Digital to Cognitive Transformation

The leap from LLMs to LRMs reflects a larger evolution in India’s digital journey — from enabling connectivity to embedding cognition. Telecom networks of the future will not just carry information; they will understand it. They will self-analyse, self-optimise, and self-secure.

This transformation is not about replacing humans but augmenting them. Engineers, analysts, and policymakers will be empowered to focus on higher-order judgment, strategy, and ethics, while LRMs handle the intricate reasoning behind routine or data-intensive decisions. The synergy of human oversight and machine reasoning will define the next phase of digital governance and service excellence.

India’s LRM Opportunity and Global Edge

India’s digital ecosystem—with its scale, linguistic diversity, and policy maturity—offers a unique testbed for developing telecom-specific reasoning models. Indigenous LRMs, trained on local data, network topologies, and policy frameworks, could become strategic assets for both industry and national security.

To realise this potential, collaboration across academia, startups, and industry is essential. Facilitating such partnerships—aligning with national missions such as Digital India, Bharat 6G Vision, and Aatmanirbhar Bharat—would ensure responsible, explainable, and interoperable AI systems that serve both business efficiency and societal trust.

The next decade in telecom will not just be about faster connectivity; it will be about smarter connectivity. Large Reasoning Models will move us from data-driven networks to reason-driven networks capable of anticipating needs, defending themselves, and evolving intelligently.

For India’s telecom industry, this is the moment to lead globally and to turn these networks into intelligent ecosystems that embody the nation’s ambition for Viksit Bharat 2047. While LLMs enabled communication, LRMs will enable comprehension—together shaping the cognitive evolution of connectivity.

The author is a decorated military veteran who retired as the Signal Officer-in-Chief, the head of the Indian Army’s ICT division. He was also the first CEO of the Telecom Sector Skill Council and is the Director General of the Cellular Operators Association of India (COAI).