India’s semiconductor ambitions, AI-capable devices and telecom automation could reinforce one another—but the changes described by industry leaders are expectations, not outcomes already in place. MediaTek India Managing Director Anku Jain sees AI moving onto smartphones and laptops, while Accenture India communications, media and technology lead Berjesh Chawla sees telecom operators gaining opportunities in network automation and enterprise services. Government chip targets and industry recommendations provide context for those possibilities, but do not establish when they will arrive.
What industry leaders expect to change
In comments reported by The Economic Times on October 8, 2026, Jain and Chawla describe a possible chain of change: domestic semiconductor design and manufacturing could support more capable connected devices; those devices could run more AI locally; and telecom operators could automate parts of their businesses while adding AI-related services for enterprise customers.
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That is an industry outlook, not a report of measured AI-agent adoption, deployed autonomous networks or available operator products. The article supplies no deployment schedule or performance data for these uses.
Could AI agents run directly on smartphones?
Jain says consumers are increasingly using AI agents to delegate tasks on smartphones and laptops, and expects devices to handle larger language models at the edge. In this context, edge means processing on the device rather than relying entirely on a remote cloud service. The potential benefit is more local processing; the actual capabilities will depend on a device’s hardware, software, supported models and which functions still require cloud access.
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Jain points to MediaTek’s Dimensity 9600 Pro, which he says features a dual neural processing unit (NPU), as an example of the company’s focus on accelerating on-device AI. That example does not identify a retail handset using the chip or establish how well it performs. It is not a basis for recommending a particular smartphone.
For buyers evaluating claims about on-device AI, useful questions include whether the feature runs locally or needs an internet connection, which models and languages it supports, and how long the manufacturer will provide software updates. A chipset’s AI hardware alone does not confirm that a specific feature is available on every phone using it.
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What India’s semiconductor roadmap says—and does not say
India’s chip ambitions include established process nodes as well as targets for more advanced manufacturing. In a January 2026 release, the Press Information Bureau reported that Minister Ashwini Vaishnaw said nearly 75 percent of global chip volume lies in the 28nm–90nm range. He cited uses including electric vehicles, automobiles, railways, defence, telecom equipment and consumer electronics, and said India should master this range before progressing to advanced nodes.
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Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →The same release describes a government-stated roadmap of 28nm to 7nm by 2030 and 3nm by 2032. These are targets, not evidence that India is already producing chips at those nodes or that the schedule is assured.
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A 2026 NITI Aayog report estimates that a globally competitive semiconductor ecosystem would require USD 135–180 billion in cumulative investment over the next decade. This is an estimate of investment needed, not funding already committed. The report recommends public funding to de-risk projects and build investor confidence; it also identifies telecom as a sector that could anchor early deployments of India-designed semiconductors.
NITI Aayog further proposes an “AI-Enabled Semiconductor Engineering Mission,” using agentic and AI-assisted systems across chip design and packaging. This is a recommendation, not a launched programme or a demonstrated result. Together, the policy context and executive outlook suggest where domestic capability might connect to demand; they do not guarantee that locally designed chips will appear in particular phones or telecom equipment.
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How telecom operators could use agentic AI
Chawla sees potential for AI agents to make network operations, IT operations and customer service increasingly autonomous. In principle, agents could help monitor systems, handle routine workflows or respond to service issues. The report does not specify which tasks operators have automated, how much human oversight would remain, or what reliability and safety measures would be used.
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For an operator considering such services, the practical questions are what systems the AI can access, how it integrates with a customer’s existing tools, what security and authentication functions are included, and where data is controlled. The source does not provide evidence to compare vendors or judge performance on those criteria.
Why 6G sensing remains a possibility, not a deployment plan
Looking further ahead, Chawla suggests that 6G base stations could potentially serve as sensing centres as well as communications infrastructure. He argues that India should help define technology priorities and promote open technologies. The report gives no 6G deployment timetable or confirmed sensing implementation, so this is best understood as a future possibility rather than a near-term feature of Indian networks.
What to watch next
- Domestic capability: whether India progresses from its stated focus on 28nm–90nm chips toward the roadmap’s advanced-node targets.
- Device support: whether specific smartphones document on-device AI features, supported models and languages, and which tasks still depend on cloud services.
- Operator deployments: whether proposed network, IT and customer-service automation becomes a named, available service with clear human oversight and security arrangements.
- Enterprise offers: whether connectivity providers publish concrete details on authentication, cybersecurity, data control and customer integration.
The link between chips, device AI and telecom is plausible as an industry direction, but its pace will depend on whether policy targets turn into manufacturing capability and whether proposed AI uses become dependable, clearly specified products.
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