Reliance Industries Ltd. chairman Mukesh Ambani on Thursday announced that Reliance and its telecom arm Jio will deploy ₹10 lakh crore over the next seven years to build AI infrastructure and applications in India, a sweeping commitment the company framed as a push to create affordable, widely accessible AI services and sovereign compute capacity. The pledge, one of the largest corporate AI investment announcements in India’s history, was disclosed at the India AI Impact Summit in New Delhi.
What was announced
Reliance said the investment will be directed at AI-ready data centres, compute infrastructure, and applications aimed at broad adoption across sectors. Ambani told the summit that the cost of computing is currently a bottleneck for many AI use cases and positioned the investment as a response to that constraint, with the goal of making AI “as ubiquitous and affordable as mobile data” in India.
The company’s figure, often reported in media at roughly $110 billion when converted at contemporaneous exchange rates, places the commitment in the same order of magnitude as other large infrastructure pledges announced at the AI impact summit, including a separate $100 billion plan from the Adani group for renewable-powered AI data centres.
The Reliance pledge arrived amid a cluster of announcements by global and Indian firms at the summit: Microsoft reiterated plans to invest about $50 billion in AI infrastructure and capacity for the Global South (including prior commitments to India), and Indian players such as data-centre firm Yotta said it would build an AI computing hub with more than $2 billion of investment using Nvidia’s latest chips. Those announcements together have been read by analysts as signalling the emergence of a larger AI infrastructure ecosystem in India.
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Reliance at the heart of India’s AI push
This investment positions Reliance at the center of India’s AI push for one simple reason: it targets every layer of the AI value chain, not just a single segment. Let me break that down clearly.
First, AI is fundamentally infrastructure-driven. Before applications, before startups, before enterprise tools, you need compute, data centers, energy capacity, fiber connectivity, and distribution platforms. A ₹10 lakh crore commitment directed largely at AI infrastructure places Reliance in control of the backbone layer. In technology markets, the entity that owns the backbone often shapes the ecosystem.
Reliance already controls India’s largest telecom network through Jio. It operates fiber infrastructure, mobile connectivity, cloud services, enterprise platforms, and has strong balance-sheet capacity. By expanding aggressively into AI compute and data centers, it extends that existing network advantage upward into the AI stack.
Second, scale matters disproportionately in AI. Advanced AI workloads are capital intensive, GPUs, cooling systems, power density, land, and renewable energy sourcing. Very few Indian companies can deploy tens of billions of dollars without external dependency. Reliance can. That alone changes the competitive equation. It reduces dependence on foreign hyperscalers for sovereign workloads and allows India to host large-scale training and inference domestically.
Third, distribution is often more powerful than invention. India’s digital ecosystem, UPI, Aadhaar, telecom penetration, scaled rapidly because infrastructure was paired with mass distribution. Reliance has over 450 million telecom users via Jio. If AI services are layered onto that base, enterprise automation, consumer AI assistants, sector-specific models, Reliance becomes not just a builder of infrastructure, but a gateway.
This is what places it at the “heart” of the AI push: control of compute + connectivity + consumer reach.
Fourth, industrial policy alignment. India’s AI ambition is not just technological, it is strategic. It is about sovereign data processing, local value creation, semiconductor supply diversification, and reducing reliance on overseas compute. A domestic conglomerate committing multi-year capital aligns tightly with policy priorities around self-reliance and digital infrastructure. That alignment typically accelerates regulatory support and ecosystem partnerships.
But strategically speaking, the reason this positions Reliance at the heart of India’s AI push is simple: AI transformation requires infrastructure muscle, balance-sheet depth, and nationwide distribution scale. Very few companies in India possess all three simultaneously. Reliance does.
In technology transitions, telecom, broadband, cloud, the companies that built foundational infrastructure ended up shaping the entire ecosystem. If this capital is executed as stated, Reliance is attempting to do the same for AI.
How investors and the industry should think about the pledge
From a market standpoint, the announcement is important for three reasons:
1. Scale and signalling. A corporate pledge of this scale signals long-term demand for AI compute, data-centre capacity, networking and software services, segments that feed into capital expenditure cycles for cloud and hardware suppliers, as well as for domestic providers of power and real-estate for data centres. The announcement therefore tends to be read positively by suppliers and infrastructure plays that stand to benefit from multi-year orders and capacity expansion.
2. Execution and monetisation risk. Large headline numbers do not automatically turn into near-term revenue. Analysts covering the summit have repeatedly warned that conversion of pledged capital into productive assets, and then into profitable services, depends on permitting, land and power availability, supply-chain access to advanced chips, and credible timelines for commercial service launches.
3. Macroeconomic and regulatory knock-on effects. If realized, such investments could spur demand for skilled labour, raise imports of specialised hardware (unless local manufacturing scales up), and attract complementary foreign capital and partnerships. Regulators’ approach to data sovereignty, taxation and incentives will materially affect the cost and pace of rollout, factors investors will watch closely.
Bottom line
Reliance’s ₹10 lakh crore commitment places the company at the centre of India’s public narrative about building sovereign AI infrastructure. For markets and technologists, the announcement is a major positive signal of intent and potential scale, but one that carries typical execution and monetisation caveats. Over the next 12–24 months, investors and industry observers should therefore focus less on the headline number and more on concrete follow-through: site acquisitions, procurement contracts, regulatory clearances, and first-wave commercial deployments that translate promise into cash flows.
