At Davos 2026, a sweeping $25 billion commitment to build a 1-gigawatt AI compute hub in Greater Noida signaled India’s most ambitious leap yet into global artificial intelligence infrastructure. This project, powered entirely by 24/7 carbon-free energy, could redefine how the world builds and deploys large-scale AI systems.
Transformative Project at Heart of AI Era
In January 2026 at the World Economic Forum in Davos, an initiative quietly emerged that may prove as consequential for the future of artificial intelligence as any product launch or startup valuation: a $25 billion investment to build a 1-gigawatt AI compute hub in Greater Noida, India, one of the largest private technology infrastructure commitments in Indian history. AM Group, the energy-tech platform backed by founders of the Greenko Group, signed a memorandum of understanding (MoU) with the Government of Uttar Pradesh to launch the facility, which aims to support global AI workloads with sustainable, carbon-free energy and advanced high-performance compute capabilities.
This is more than another data center. It’s a statement: India wants not only to be a major AI market but also a foundational provider of the global computing backbone on which frontier AI systems will run. The implications, for national competitiveness, energy policy, jobs, climate commitments, and digital sovereignty, are vast.
AI Compute at Global Scale
AI models have grown exponentially in size and energy demand. Training leading deep learning systems now requires access to petaflops to exaflops of computing, often spread across tens of thousands of GPUs or specialized accelerators. Hyperscalers such as Google, Microsoft, Amazon, and NVIDIA have invested heavily in massive AI compute clusters in the US and Europe, but until now, India has lacked comparable compute infrastructure at scale.
The planned 1-gigawatt (GW) facility, roughly equivalent to the total electrical draw of a small city — would be among the largest AI compute hubs in existence. It is designed for high-performance computing (HPC) and AI workloads serving global hyperscalers, frontier research labs, large enterprises, and sovereign AI initiatives, all at competitive scale and green energy backing.
By housing around 500,000 advanced high-performance chipsets and scaling to full capacity by 2030, the hub aims to provide computing resources that have historically been concentrated in Western and Chinese markets. This opens opportunities for research, startups, and sovereign AI projects to operate with lower latency and greater control over data, a significant step toward digital sovereignty.
A Seamless Fusion of AI and Renewable Energy
What sets this project apart from most other global compute infrastructure is its commitment to sustainability. AM Group will leverage its leadership in renewable energy, including solar, wind, and pumped storage, to power the entire hub around the clock with carbon-free energy. The hub’s 24/7 green energy promise aims to sidestep the chronic climate tension between data center growth and carbon emissions, which has drawn scrutiny in markets like the U.S. and Europe.
This aligns with India’s broader net-zero commitments and with global corporate sustainability goals. It resonates with multinational companies that seek to reduce not just financial but environmental costs of AI computing, a growing requirement in corporate and government procurement. By embedding renewable energy into the core compute strategy, the hub sets a new sustainability benchmark in AI infrastructure.
Economic Impact: Jobs, Investments, and Digital Ecosystems
The scale of investment, $25 billion, is itself transformative. Beyond the physical infrastructure, the hub is expected to catalyze:
1. High-Skill Employment
Thousands of high-skilled jobs in data engineering, system architecture, AI research, software development, cooling and power systems, and AI hardware maintenance will center around Greater Noida and the broader National Capital Region.
2. Foreign Direct Investment (FDI)
The project’s global ambition is likely to attract multinational technology firms that require local AI compute capacity and low-carbon operations for Europe, Asia, and Africa. This can boost foreign capital inflows into India’s technology sector.
3. Local Ecosystem Growth
Hardware manufacturing, software R&D, data center support services, and specialized cooling and power tech firms may cluster around the hub, fostering an AI-focused industrial ecosystem that rivals established tech corridors.
4. Digital Inclusion
By providing access to high-end compute for Indian developers and researchers, the hub could help democratize AI development, enabling local startups and academic institutions to build and test models without prohibitive cloud costs.
Strategic Drivers Behind Investment
A. India’s Ambition in AI Leadership
India’s policymakers have repeatedly articulated AI as a national priority, integrating it into initiatives such as the Digital India mission and long-term frameworks like Viksit Bharat 2047 — the country’s 25-year vision for economic growth and technological sovereignty. The compute hub aligns with these goals by ensuring that India’s AI capabilities are not reliant on external cloud providers.
B. Renewable Energy Synergies
Greenko Group, one of India’s major renewable energy conglomerates, has been expanding its footprint into digital infrastructure. AM Group, backed by Greenko founders Anil Kumar Chalamalasetty and Mahesh Kolli, is extending this strategy by integrating power generation with compute demand, a model increasingly seen as essential for carbon-intensive data centers.
C. Competitive AI Computation
Global players such as Google have already announced AI hubs in India (e.g., a $15 billion center in Visakhapatnam) that signal India as a rising node for data and AI infrastructure. Large private investments like the AM Group’s hub complement these efforts and diversify the country’s digital base.
Innovation Landscape: A Full-Stack Vision
AM Group’s vision extends beyond hardware racks and power supplies. The company is promoting an AI ecosystem anchored in an “electron-to-token” architecture, a description suggesting a full-stack approach that connects the physical compute layer with advanced software infrastructure and AI application stacks. This could give Indian developers a platform both to innovate and commercialize domain-specific AI solutions across sectors like healthcare, manufacturing, automotive, gaming, media, and sovereign cloud services.
This is not merely a data center, it is intended to be a computing platform and innovation ecosystem, potentially reducing dependence on global cloud imports and empowering domestic AI development.
Geopolitical and Strategic Significance
The compute hub also has geopolitical implications. As the U.S. and China vie for AI leadership through investments in AI research and chip supply chains, India’s emergence as a third major node, combining democratic governance, renewable energy, and low-carbon compute, gives it strategic leverage. It positions India to:
- Participate in global AI supply chains;
- Offer an alternative to Western and Chinese cloud infrastructures;
- Support regional digital autonomy for neighboring markets.
This diversification of global compute infrastructure can reshape how organizations think about sovereign AI capabilities and data localization.
Challenges and Considerations
Despite its promise, the project faces challenges:
Power and Cooling Solutions
Designing and maintaining efficient cooling for high-density compute at 1 GW scale remains a technical and logistical hurdle. The use of renewable energy must be uncompromising to preserve sustainability claims.
Chip Supply and Hardware Dependencies
India currently depends on imported HPC chips and accelerators. Procuring 500,000 high-performance chipsets and integrating them at scale may face bottlenecks or geopolitical supply constraints.
Talent Shortage
Operating and innovating around frontier AI infrastructure requires a deep pool of specialized engineers, data scientists, and HPC experts, a talent ecosystem India continues to develop.
Despite these challenges, the hub’s phased rollout, with initial capacity targeted for 2028 and full deployment by 2030, suggests a measured, strategic approach to scaling.
Conclusion: A Template for Sustainable AI Infrastructure
India’s $25 billion AI compute hub in Greater Noida is a landmark in the global AI landscape. It reflects India’s aspirations not just to consume AI technology but to host and power a significant part of its computational backbone. With sustainability at its core, high performance at scale, and integration with local development ecosystems, this project is poised to influence where and how the next generation of AI systems are trained, tested, and deployed.
As nations compete to shape the future of AI, India’s gamble on renewable-powered compute infrastructure could become a defining chapter in the evolution of global digital infrastructure.
