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India’s semiconductor ambitions and the growth of agentic AI could reinforce each other: locally designed chips may support smarter connected devices, while telecom networks could gain new automated operations and enterprise services. Those are opportunities described by industry leaders, not changes already demonstrated at scale. Their timing—and the extent of India’s future chip-manufacturing capability—remains uncertain.
What industry leaders expect to change
In an October 8, 2026 report by The Economic Times, Anku Jain, managing director of MediaTek India, described AI as a major technology trend, including agents that can carry out tasks for users on smartphones and laptops. Berjesh Chawla, Accenture India managing director and Communications, Media and Technology lead, outlined ways AI agents might change telecom operations and enterprise services.
The two views connect three layers: semiconductor design and manufacturing, AI features in devices, and telecom networks that connect those devices and businesses. They are executive expectations, not evidence of measured consumer adoption, deployed autonomous telecom systems, or a confirmed timetable for the proposed changes.
How agentic AI could reach smartphones and connected devices
From answering prompts to handling tasks
An AI agent is intended to do more than respond to a single prompt: it can be asked to carry out a task or a sequence of steps. Jain said consumers are increasingly using agents on smartphones and laptops. The report provides no adoption figures, so this describes his industry view rather than a quantified trend.
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Some AI processing may happen on a device rather than relying entirely on a remote service. Running larger language models at the edge—the device or another nearby computing resource—could reduce dependence on sending every request to the cloud. The report does not specify which models, tasks, languages, or handset functions will run locally, or how much processing future devices can handle.
What the Dimensity 9600 Pro example does—and does not—show
Jain cited MediaTek’s Dimensity 9600 Pro, which he said features a dual neural processing unit (NPU), as an example of the company’s focus on accelerating on-device AI. An NPU is a processor designed to handle AI workloads. The cited example does not establish that a particular retail phone contains this chipset, nor does the report supply independent performance tests or a list of supported AI features.
For readers comparing AI-capable smartphones, the useful questions are whether a feature runs on-device or needs cloud access, which chipset and AI capabilities the phone documents, which models and languages it supports, and whether the feature is available in India and maintained through software updates. A chipset name alone cannot answer those questions for a specific handset.
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What India’s semiconductor roadmap means for the ambition
Start with chips used across many sectors
India’s stated approach includes building capability in established chip nodes before moving toward more advanced ones. In a January 2026 release, the Press Information Bureau (PIB) reported that Minister Ashwini Vaishnaw said nearly 75 percent of global chip volume lies in the 28nm–90nm range. He pointed to uses in electric vehicles, automobiles, railways, defence, telecom equipment, and consumer electronics, and said India should master this range before advancing.
The same PIB release attributed a roadmap to Vaishnaw of moving from 28nm to 7nm by 2030 and reaching 3nm by 2032. These are government-stated targets, not verified production capabilities or a guarantee that the milestones will be met.
Investment and design are part of the picture
Manufacturing is only one component of a semiconductor ecosystem. NITI Aayog’s 2026 report, India’s Semiconductor Sector: An Action Plan, estimates that a globally competitive ecosystem would require USD 135–180 billion in cumulative investment over the next decade. That is an estimate of future need, not funding already committed. The report recommends public funding to reduce project risk and encourage investor confidence.
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NITI Aayog identifies telecom as one sector that could help anchor early deployments of India-designed semiconductors. It also proposes an “AI-Enabled Semiconductor Engineering Mission,” using agentic and AI-assisted systems across chip design and packaging. These are policy recommendations; the report does not establish that the mission or those deployments are already in operation.
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How telecom operators could use agentic AI
Automating network, IT, and customer-service work
Chawla said AI agents could make network operations, IT operations, and customer service increasingly autonomous. In principle, agents could help monitor systems, identify routine issues, and carry out approved responses. The report does not name a deployed system, describe its safeguards, or provide performance results, so these should be understood as potential uses rather than current operator capabilities.
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Greater automation would also make oversight important: operators would need to define which actions an agent may take independently, when human approval is required, and how failures or security incidents are handled. The report does not set out a specific implementation model.
Adding enterprise services to connectivity
Chawla also described an opportunity for operators to combine connectivity with services such as authentication and cybersecurity for enterprises and micro, small and medium enterprises (MSMEs). This could expand an operator’s role beyond supplying network access, but the report does not identify products, providers, prices, service-level commitments, or comparative results.
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He linked “sovereign AI” opportunities to local data residency, control, and AI applications focused on national needs. That is a description of potential priorities, not a statement about a particular legal requirement or guarantee that data will remain within a given jurisdiction.
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Why 6G sensing remains a future possibility
Chawla suggested that future 6G base stations could potentially serve as sensing centres as well as communications infrastructure. In that concept, network signals might support sensing functions in addition to carrying data. The report offers no deployment date, technical specification, or confirmed service, so the idea should not be read as a feature of current networks or a settled 6G plan.
Chawla also argued that India should help define technology priorities and promote open technologies. That aspiration sits alongside the broader semiconductor and telecom ambitions, but the sources do not establish what role India will hold in future standards or when any sensing capability might be deployed.
Quick Recap
What to watch next
- Chip capability: whether India progresses from the established 28nm–90nm range toward the government-stated advanced-node targets.
- Investment and execution: whether the ecosystem attracts the long-term investment NITI Aayog estimates is needed and advances beyond recommendations into funded projects.
- Device evidence: which retail devices document local AI processing, supported models, languages, and features—not just an AI-capable chipset.
- Telecom deployment: whether operators announce concrete AI automation or enterprise services, with clear scope, safeguards, and service commitments.
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