1. Headline & intro
Reliance’s new $110 billion artificial intelligence plan is not just another mega–data center announcement. It’s a bid to move India from being the world’s favorite outsourcing destination to becoming one of its core AI infrastructure hubs — on a scale that rivals nation‑state programs.
If it works, the cost and geography of AI compute could change for everyone: from European startups training models to global enterprises hunting for cheaper, greener GPU capacity. In this piece I’ll unpack what Reliance actually promised, why this is strategically important, how it fits into the global AI arms race, and what it means specifically for Europe and its tech ecosystem.
2. The news in brief
According to TechCrunch, Reliance Industries chair Mukesh Ambani announced a ₹10 trillion (around $110 billion) investment plan to build AI computing infrastructure in India over the next seven years. The announcement was made at the India AI Impact Summit in New Delhi.
The plan centers on gigawatt‑scale data centers, a nationwide edge computing network, and new AI services tightly integrated with Reliance’s telecom arm Jio. Construction has already started on multi‑gigawatt facilities in Jamnagar, Gujarat, with over 120 MW of capacity expected to go live in the second half of 2026.
This comes as other Indian conglomerates and the government ramp up AI spending. TechCrunch reports that Adani Group recently outlined a roughly $100 billion AI data center push, while New Delhi expects more than $200 billion in AI infrastructure investment nationwide over the next two years. Global firms are also involved: OpenAI is partnering with Tata Group on AI capacity, and Jio has a deal with Google to bundle Gemini AI access. Reliance says the build‑out will lean heavily on its surplus green energy and will support AI services in multiple Indian languages.
3. Why this matters
This is not just a big number to impress investors. Reliance is doing for AI compute what it previously did for mobile data: using scale, integration and cheap capital to distort the price curve in its favor.
Who benefits first?
- Indian startups and enterprises get local, theoretically cheaper AI compute, plus tight integration with a dominant mobile and fiber network (Jio). That’s a powerful distribution channel for AI products.
- Global AI players gain a massive, politically friendly region to host and run models, particularly those looking to diversify away from US‑ and China‑centric infrastructure.
- Chip and power ecosystems – from GPU vendors to power equipment manufacturers – gain a gigantic, long‑term customer willing to sign multi‑year, multi‑billion‑dollar contracts.
Who loses?
- Smaller Indian data center providers will struggle to match Reliance’s capital intensity and its ability to cross‑subsidize AI from telecom and retail cashflows.
- Regions betting on becoming AI compute hubs – including some EU countries – might find it harder to compete on pure price and scale when India can tie together cheap land, labor, solar energy and regulatory flexibility.
Strategically, Ambani’s message that India “cannot afford to rent intelligence” cuts to a global fault line. Countries are realising that whoever controls GPUs and data centers controls the tempo of innovation. The constraint in AI today really is compute, not vision.
Reliance is effectively arguing: let the Americans own the foundation models and the Chinese play behind their firewall; India will own a big chunk of the global infrastructure layer. If they deliver the promised gigawatts, this could structurally lower AI compute prices, just as Jio’s 4G rollout crashed mobile data prices and triggered a wave of digital adoption.
4. The bigger picture
Reliance’s announcement lands in the middle of an accelerating global race to build AI “power plants”. Three trends stand out.
1. From cloud regions to AI industrial zones
US hyperscalers — Microsoft (with OpenAI), Amazon and Google — are already spending tens of billions annually on AI‑optimised data centers. The Gulf states are pouring money into AI infrastructure as well, with players like G42 positioning the UAE as an AI super‑node. Reliance is now trying to put India in that same conversation: not just as a large user base, but as a source of capacity.
2. The rise of ‘sovereign AI’
Governments from France to the UAE are talking about sovereign AI: models, data and infrastructure aligned with national interests. India is adding a twist — sovereign compute at private‑sector scale. Instead of building everything through state programs, New Delhi is clearly happy to let conglomerates like Reliance and Adani act as its AI industrial champions, while it sets direction and dangles incentives.
3. Historical echoes: Jio and the 4G shock
We’ve seen this movie before. When Jio entered India’s mobile market, it spent tens of billions building a 4G‑only network, then undercut competitors on price, effectively resetting what Indians expected to pay for data. That triggered consolidation, but also unleashed a boom in local apps, fintech and e‑commerce.
If Reliance applies the same playbook to AI, we should expect an aggressive push to commoditise inference (and maybe eventually training) for Indian users and businesses. The rest of the world, including Europe, may quietly arbitrage that pricing via partnerships and offshoring of workloads.
At a macro level, this confirms that AI is no longer a pure software race. It’s industrial policy plus energy policy plus telecom economics. The winners will be countries and companies that can line up all three.
5. The European / regional angle
For Europe, Reliance’s move is both a warning and an opportunity.
On the one hand, the EU has spent years talking about Gaia‑X, EuroHPC and the Chips Act to reduce dependence on US cloud and Asian manufacturing. Yet a single Indian conglomerate is now committing an AI capex envelope comparable to, or larger than, many national digital programs. That contrast is hard to ignore.
Europe’s regulatory stance — from GDPR to the Digital Services Act and the upcoming AI Act — preserves fundamental rights, but it also slows down and fragments infrastructure rollouts. Building a gigawatt of data center capacity in Europe means navigating multiple national planning regimes, high energy prices, local opposition, and tight environmental rules. India, by contrast, is signalling that large‑scale energy‑hungry infrastructure is a strategic priority and is backing that up with land, power and political support.
However, this is not a zero‑sum game. European companies could:
- Use India as an AI back‑end for some workloads that are not subject to strict data‑localisation requirements, especially model training on synthetic or non‑personal data.
- Partner with Reliance and others on domain‑specific models, using European data and governance frameworks but Indian compute.
- Align with India on standards – for example around openness, safety and auditing – as a counterweight to both US platform dominance and China’s closed model.
There are also cultural synergies. Indian IT firms have decades of experience serving European enterprises. Adding AI infrastructure to that mix simply deepens an existing relationship.
The key challenge will be regulatory: ensuring that any EU–India AI cooperation respects GDPR, the AI Act’s risk classifications, and emerging rules around cross‑border data flows. Europe will have to decide whether it wants to be a fortress of compliance, or an active shaper of a multi‑polar AI infrastructure world that now clearly includes India.
6. Looking ahead
Several big questions will determine whether Reliance’s $110 billion vision becomes reality or remains an ambitious slide deck.
1. Can the hardware actually be delivered?
The global shortage of advanced GPUs and AI accelerators is real. Nvidia and its rivals are already oversubscribed by US hyperscalers and Chinese buyers (within the limits of export controls). Reliance will need long‑term, preferential supply deals, plus domestic and international political goodwill, to secure enough chips at the right price.
2. Energy, water and climate constraints
Gigawatt‑scale data centers are effectively power plants that run in reverse. Reliance plans to lean on its green energy portfolio, which is smart, but grid stability, water usage and local environmental impact could still become flashpoints — especially as Indian cities already struggle with heat and infrastructure stress.
3. Talent and ecosystem depth
India has the engineers, but running AI super‑clusters at scale is a specialised skill set still concentrated in a few US, Chinese and European tech hubs. Reliance will have to import know‑how, either by hiring globally or partnering deeply with established cloud providers and AI labs.
4. Business model clarity
Will this be a mostly internal asset (powering Jio, retail, finance), or a truly open platform competing directly with AWS, Azure and Google Cloud? The answer determines pricing, partner interest and regulatory scrutiny.
My bet: by 2030, India will be firmly established as one of the top three or four AI compute regions globally, alongside the US, parts of East Asia and the Gulf. Prices for AI inference, in particular, will be driven down, with India acting as a key benchmark just as it did for mobile data.
For European founders and CIOs, the homework over the next 24–36 months is clear: map which AI workloads must stay under EU jurisdiction, and which could benefit from tapping into a cheaper, Indian‑backed compute layer — assuming legal pathways and trustworthy partners exist.
7. The bottom line
Reliance’s $110 billion AI investment plan is a declaration that the next phase of the AI race will be won as much in power grids and data halls as in research labs. It sharply raises the odds that India becomes a global price‑setter for AI compute, not just a consumer of Western models.
For Europe, this is both competitive pressure and a chance to build a deeper, more balanced tech partnership with India. The real question is whether policymakers and companies here are prepared to treat AI infrastructure with the same strategic urgency that Ambani clearly does.
