Ramakrishna P, chief executive of the India Mobile Congress, has argued that telecom operators have no realistic option but to deploy artificial intelligence across their networks, despite an unproven revenue case. The position, reported by The Economic Times under the headline "Telcos can't skip AI, even as returns remain uncertain," captures a tension now visible across operator boardrooms in India and abroad.

What the message signals

The India Mobile Congress is the country's flagship telecom industry gathering, drawing carriers, equipment vendors, hyperscalers and regulators each year. Statements from the IMC's chief carry weight because the forum helps set the agenda for the Indian market, which remains the world's second-largest by subscriber count.

By framing AI as non-optional, Ramakrishna aligns with the message senior executives have taken at recent Mobile World Congress events in Barcelona, where operators and vendors have consistently pitched AI as a cost-control and network-optimisation tool rather than a direct revenue line.

How operators have deployed AI so far

Major carriers have moved AI workloads from pilot into production across several recurring domains. Radio access network optimisation and energy savings have become standard deployments at tier-one operators worldwide. Customer service automation, including agent-assist and conversational interfaces, is now routine at large carriers. Fraud detection, revenue assurance and predictive maintenance for fibre and core infrastructure round out the most cited use cases.

The deployment story is well advanced. The monetisation story is not.

Why returns trail deployment

Three structural pressures limit near-term revenue capture:

• Slim margins. Telecom operators typically run single-digit EBITDA margins, leaving limited room for speculative investment.
• Billing constraints. Legacy BSS stacks were not designed to meter AI features as discrete products.
• Consumer pricing tolerance. Customers rarely pay a premium for AI-enhanced service quality.

These dynamics explain why operators continue to fund AI programmes while openly questioning when the spend will appear on the income statement.

Regulatory and standards backdrop

The Telecom Regulatory Authority of India has run consultations on AI governance in communications networks, though no binding rules have issued. India is an active participant in ITU and 3GPP work on AI and machine-learning lifecycle management in 5G-Advanced and 6G specifications, giving operators a standards-based route to deploying auditable network AI rather than proprietary black-box systems.

Vendor positioning

Equipment makers including Ericsson, Nokia, Huawei and Samsung Networks have marketed AI-RAN and self-optimising network features as headline items of their 5G-Advanced roadmaps. Hyperscalers supply the compute and model platforms behind most production AI workloads through operator partnerships.

What the source does — and does not — disclose

The Economic Times headline supplies the framing but no specific verbatim quote, contract figure or named operator beyond the speaker. Carriers, regulators and vendors are not tied to specific AI spend in the published headline.

Outlook

Whether AI-driven savings will surface in operator quarterly results through 2026 is the open question. Indian carriers are mid-way through a 5G capex cycle that also covers fibre expansion and the early stages of 6G research. The IMC platform will likely return to AI economics at its next annual edition, where operators may be pressed for measured financial outcomes rather than pilot counts.