How AI is Driving Data Center Growth in India

India is rapidly advancing its data center infrastructure to support the increasing demands of Artificial Intelligence (AI), especially as AI applications continue to grow across sectors like healthcare, finance, and logistics. NVIDIA CEO Jensen Huang recently projected that India’s computing power will increase nearly 20-fold within a year, underscoring the nation’s potential as a global AI powerhouse. This growth has catalyzed data center expansion, with hyperscalers like AWS and Microsoft Azure leading the charge alongside local providers focused on AI-driven workloads. With AI transforming how data centers operate and evolving infrastructure needs, India’s data center industry is expected to generate $25 billion by 2030, according to Avendus.

The Growing Need for Data Centers in India’s AI Ecosystem

As AI applications proliferate, data centers must handle increasingly complex AI workloads while also balancing energy efficiency and sustainability. India’s AI landscape, with over 1,300 AI companies, is pushing data centers to expand their capacity to accommodate higher-density workloads and advanced AI models. To meet this demand, data center operators are implementing advanced cloud computing capabilities and edge computing solutions, enabling efficient data processing closer to data sources.

In addition to expanding infrastructure in major cities, data center operators are establishing micro data centers in smaller cities. These compact facilities support AI applications in real-time and enhance smart city solutions across India’s Tier II and Tier III cities.

Major Players in India’s Data Center Expansion

Key players are making significant investments to expand India’s data center capacity, meeting the needs of hyperscalers and enterprises:

• Reliance Industries (RIL): Partnering with NVIDIA, RIL is focusing on building robust AI infrastructure across India to support AI-driven services and applications.
• CtrlS: This Hyderabad-based data center provider is investing $2 billion over the next five years to scale its infrastructure for high-density AI workloads. CtrlS plans to add over 300 MW of capacity and integrate renewable energy solutions to support carbon neutrality by 2040.
• E2E Networks: With a focus on cloud GPUs for AI, E2E Networks is collaborating with decentralized micro data centers to deliver scalable computing power for startups and enterprises. The company is also actively involved in the IndiaAI Mission, deploying 1,500 GPUs and expanding further.

Micro Data Centers: Bringing AI Closer to Users

India’s demand for distributed computing is driving the growth of micro data centers in smaller urban areas, supporting AI-driven applications in smart cities and industries like manufacturing, retail, and healthcare. According to Sangeeta Gupta, Senior VP at NASSCOM, “Micro data centers present a promising solution with their modular and energy-efficient designs, ideal for Tier II and Tier III cities.” These facilities help optimize real-time data access, reduce latency, and support Internet of Things (IoT) applications, making advanced AI technology accessible across India.

Evolving Infrastructure for High-Density AI Workloads

AI models like large language models (LLMs) and transformers require substantial computing power, which challenges existing infrastructure in terms of energy consumption and thermal management. Companies are investing in high-performance GPUs, such as NVIDIA’s H-100, to accommodate these demanding AI workloads.

• SiMa.ai: This company offers the MLSoC Modalix platform, which enables edge AI processing on devices close to data sources, reducing the need for centralized data processing. This approach is crucial for industries requiring real-time intelligence, such as autonomous vehicles and smart cities.
• E2E Networks: Focused on delivering AI-first cloud infrastructure, E2E Networks provides high-density cloud GPUs for training complex AI models and large-scale image generation. This infrastructure is essential for sectors like education, healthcare, and media, where advanced AI applications demand substantial computational power.

The Impact of Data Localization and Regulatory Policies

India’s push for data sovereignty has led to stricter data localization regulations, driving the need for localized data centers to store and process information within national borders. Local regulators are enforcing policies that mandate data be stored domestically, which benefits the Indian data center market as companies increase capacity to meet compliance requirements. Prateek Jhawar, MD at Avendus Capital, notes that these regulatory requirements are creating substantial growth opportunities for developers, operators, and investors focused on Indian data centers.

Energy Efficiency and Sustainability Challenges

While AI enables data centers to operate more efficiently, it also increases energy demand. Training models like ChatGPT requires up to ten times the energy of a typical Google search. As a result, data center operators in India are adopting sustainable solutions:

• CtrlS: Aiming for carbon neutrality by 2040, CtrlS plans to achieve 80% green energy usage within the next four months. Investments in solar energy and water recycling technologies reflect its commitment to sustainable data center operations.
• SiMa.ai: By using single-chip AI solutions, SiMa.ai’s Modalix platform reduces energy consumption by over 10X compared to traditional methods, supporting high-performance AI with lower power requirements.

With AI workloads increasing power density in data centers, innovative cooling and energy solutions are essential to minimize environmental impact. Advanced cooling technologies, such as liquid cooling, improve efficiency by up to 40%, reducing operational costs and enhancing energy sustainability.

Future Outlook for Data Centers and AI in India

The outlook for data center growth in India remains robust as AI continues to expand across industries. By 2030, India’s data center sector is projected to reach $25 billion, with global hyperscalers and local providers alike expanding capacity to support AI and cloud-based services. Key factors driving this growth include:

• Government support: India’s AI and digital economy initiatives, such as the IndiaAI Mission and data localization laws, are attracting long-term investments in data center infrastructure.
• Demand for sovereign cloud infrastructure: The need for data centers within India’s borders supports compliance and strengthens security, creating a boost for domestic data center capacity.
• Sustainable innovation: As AI models consume more energy, data center providers are adopting green solutions to balance growth with environmental responsibility. Innovations in cooling, energy sourcing, and edge computing solutions will be key to future growth.
• Expanding micro data centers: Distributed micro data centers across smaller cities enable faster processing and broader AI adoption, particularly in sectors like healthcare, manufacturing, and education.

With AI transforming the digital landscape, India’s data center industry is positioned to support diverse, high-performance applications that fuel the nation’s ambitions as an AI leader. Hyperscalers and local providers must adapt to accommodate the complexities of AI, maintaining efficiency and sustainability in an increasingly AI-driven ecosystem.

For more insights on how AI is reshaping data infrastructure, explore our latest reports on data center innovations and AI-driven growth strategies.