India’s data centre industry is entering a defining phase as artificial intelligence moves from experimentation to enterprise-scale deployment. In 2026, AI is no longer just an application layer innovation—it is reshaping the very foundations of digital infrastructure. From hyperscale cloud campuses to distributed edge nodes, data centres are being redesigned to support GPU-dense workloads, advanced cooling technologies, high-speed interconnects, and AI-driven automation. What was once considered backend infrastructure has now become the backbone of India’s digital economy.
The Union Budget’s continued emphasis on digital infrastructure, tax certainty, and investment-friendly policies has strengthened India’s position as a preferred destination for hyperscale and AI-ready facilities. Safe harbour norms and long-term incentives for cloud and infrastructure providers are accelerating capital inflows, while data localisation and sovereign AI initiatives are driving domestic capacity expansion. As generative AI, 5G, fintech platforms, digital public infrastructure, and real-time analytics gain scale, the demand for low-latency, high-availability and regulation-aligned environments is rising sharply.
AI workloads are fundamentally different from traditional enterprise computing. Model training requires concentrated, power-intensive compute clusters, while inference demands distributed architectures closer to end users. This shift is pushing operators toward hybrid designs that integrate hyperscale cores with intelligent edge infrastructure. High rack densities, liquid cooling, renewable energy sourcing, fibre- rich ecosystems, and automated workload orchestration are no longer optional—they are central to competitiveness. At the same time, sustainability has become a strategic imperative. As energy consumption rises with AI intensity, operators are prioritising PUE optimisation, renewable integration, and water-efficient cooling systems to balance growth with environmental responsibility.
India’s expanding digital footprint, deep engineering talent, and strategic geographic location are positioning it as more than a consumption market. The country is steadily emerging as a vital node in the global AI and data centre value chain, serving domestic demand while attracting international workloads across APAC, the Middle East, and Africa. Collaboration among hyperscalers, OEMs, telecom operators, cloud service providers, system integrators, and policymakers will determine how effectively this opportunity is realised.
In this evolving landscape, VARINDIA talked to leading data centre operators, infrastructure providers, OEMs, storage innovators, cybersecurity leaders, and network specialists to understand how they are preparing for the next phase of AI-led growth. From architecture redesign and GPU-ready environments to hybrid cloud strategies, renewable integration, sovereign AI frameworks, edge acceleration, high-density cooling innovations, intelligent workload orchestration, and prevention-first security models, their insights reveal how India is engineering a resilient, scalable and sustainable foundation for its AI-driven future. Collectively, these perspectives underscore a larger transformation underway—one that goes beyond incremental capacity expansion to fundamentally reimagining how power, performance, connectivity, data protection, and environmental responsibility converge to create globally competitive, future-ready digital infrastructure at national scale.
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Building India’s AI future through resilient infrastructure and sustainable edge computing
MANOJ PAUL
MANAGING DIRECTOR, EQUINIX INDIA
“AI workloads today span model training, inference, and data in motion, each requiring distinct performance characteristics, network architectures, and power densities. Architectures are being engineered to support higher rack power densities, advanced cooling configurations, and dense fiber interconnection to enable GPU clusters to operate efficiently and securely. In India, our data centers in Mumbai and Chennai are being developed as AI-ready environments with liquid cooling capability, where centralized training workloads can run alongside latency-sensitive inference closer to enterprise users through rich interconnection ecosystems. This ensures that enterprises can leverage high- performance computing while maintaining secure, low-latency access for mission-critical applications, enabling both scale and reliability.
Beyond core architecture, the next phase of AI growth in India will be shaped by ecosystem proximity and distributed intelligence. Distributed digital infrastructure, hybrid multicloud integration, and AI-optimized interconnection are expected to play a central role, as enterprises increasingly seek architectures that bring compute closer to users while maintaining seamless access to public and private cloud environments. Hybrid approaches are being adopted to balance regulatory requirements, data sovereignty considerations, and performance objectives. Interconnected data centers are positioned as neutral hubs where enterprises, networks, and cloud providers converge. As AI inference becomes more embedded across financial services, healthcare, and manufacturing, edge deployments are strengthened to support low-latency processing and real-time decision-making. This model is viewed not only as a technology shift but also as a strategic enabler of India’s digital economy, supporting emerging applications across 5G, generative AI, and advanced analytics.
As capacity scales to meet AI demand, growth must align with environmental responsibility. Rapid expansion is being pursued alongside a focus on sustainability and operational efficiency, as energy intensity rises with high-density computing. Energy-efficient cooling systems, automation, and renewable power procurement strategies are integrated to reduce carbon emissions and optimize resource utilization. Industry recognition, including leadership in global sustainability assessments, reinforces the importance of transparent environmental targets and measurable progress. Over the next three years, advancements in liquid cooling, AI-driven workload orchestration, edge acceleration, and early-stage quantum-adjacent infrastructure exploration are expected to influence performance and competitiveness. Operators that combine scalable architecture, dense interconnection ecosystems, and disciplined sustainability execution will be best positioned to lead India’s next phase of AI-enabled digital growth.”
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India’s AI future built on resilient infrastructure, edge intelligence, and sustainable data centers
ROOPESH KUMAR
HEAD - DATA CENTER PROJECTS, SIFY TECHNOLOGIES
“Our data centers are built to support a wide range of workloads, including AI, high-density computing, and specialized processing. The Rabale Data Center campus is equipped to handle AI workloads of up to 130 kV using direct-to-chip technology. We are also investing in advanced facilities for AI and high-density computing, supported by reliable network connections and diverse carrier options. To manage the heat from densely packed AI clusters, we are adopting advanced cooling technologies such as liquid cooling, rear door heat exchangers (RDHx), and immersion cooling, moving beyond traditional air cooling. These upgrades ensure our infrastructure can efficiently and securely handle modern compute-intensive workloads at scale.
Edge computing, hybrid cloud, and AI-optimized infrastructure play a central role in our growth strategy in India. Our in-house cloud platform operates the data center infrastructure, enabling effective hybrid cloud deployment that combines on-premises systems with cloud-based environments. Data centers in Airoli and Bengaluru are designed to support public and hybrid cloud hosting, catering to enterprise digital transformation. AI significantly enhances data center efficiency, particularly in energy management, cooling, and resource allocation. Through scalable infrastructure and flexible pricing, we aim to advance domestic innovation and establish India as a global hub for AI transformation. Our plans to establish and expand an Edge footprint across the country are detailed in our DRHP, reflecting the importance of bringing compute closer to users while maintaining robust interconnection and low- latency performance.
Sustainability is embedded in our infrastructure strategy as we balance rapid capacity expansion with energy efficiency and renewable integration. India’s total electricity generation capacity has reached 452.69 GW, with renewables accounting for over 46% of installed capacity. Our data centers use substantial energy, so improving efficiency and reducing environmental impact is a priority. We are increasingly adopting renewable sources such as solar, wind, and bioenergy. Across all 14 data centers, renewable power absorption exceeds 38%, while our largest campus operates at nearly 60%. Over the next three years, rapid adoption of high-density GPUs and specialized AI chips, along with AI- powered cooling systems, will reshape infrastructure requirements, manage thermal loads, and improve energy consumption. India’s initiative to set up 18,000 advanced GPU-based facilities under the IndiaAI Mission, expected in early Q4 of Fiscal 2025, will significantly influence power consumption and competitiveness, ensuring operational efficiency for India’s AI-driven digital economy.”
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India’s path to sovereign AI depends on infrastructure resilience and sustainability
AMIT AGRAWAL
PRESIDENT, TECHNO DIGITAL
“If India wants sovereign AI, it must first build robust infrastructure and enable a local ecosystem. Large language models may process tokens, but tokens translate into IT power, thermal load, electrical stability, robust network, and geographical spread. If those fundamentals are weak, no amount of GPU procurement will make a data center AI-ready. We are redesigning architecture around this reality. AI workloads demand predictable power paths, higher-density tolerance, liquid cooling readiness, and modular scaling blocks that evolve without structural redesign every cycle. The real design question is no longer ‘How many racks?’ but ‘How stable is the energy-to-compute conversion under sustained load?’ Our 36 MW Chennai facility reflects this approach. Hybrid cooling using high- efficiency centrifugal chillers with adiabatic cooling towers delivers a PUE of 1.35 while reducing water consumption by up to 75%, demonstrating that density and sustainability can coexist when engineered correctly.
AI is also reshaping topology. Training belongs in concentrated, resilient core environments, while inference belongs closer to users. A distributed model is therefore not optional. Our strategy combines hyperscale campuses with a 102-city pan-India edge footprint to address latency, governance, and data gravity. Core and edge are interdependent layers of the same compute fabric, orchestrated through hybrid cloud models. The harder challenge is balance. Rapid expansion without energy discipline becomes fragile; high density without thermal maturity becomes inefficient; renewable ambition without storage becomes unreliable. Sustainability cannot live in ESG reports-it must live inside the electrical room. Water-efficient cooling, storage- backed renewable integration, and disciplined PUE targets are engineered at inception, not retrofitted.
Over the next three years, competitiveness will be defined by smarter power systems, advanced liquid and immersion cooling technologies, direct liquid cooling (DLC), AI-driven infrastructure management, dynamic workload orchestration across core and edge, and deeper integration of renewables with energy storage. More GPUs alone will not create advantage. The real risk ahead is not underinvestment, it is overconfidence. Building rigid, one-dimensional AI capacity based on current density assumptions can create stranded assets. Infrastructure must remain adaptable because AI workloads will evolve faster than real estate cycles. India’s sovereign AI future will not be determined by who builds the largest campuses, but by who builds infrastructure that absorbs volatility, converts energy efficiently into compute, and sustains reliability at national scale.”
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Scaling AI workloads with smart, sustainable, and sovereign data centre design
ROHAN SHETH
HEAD - COLOCATION, DATA CENTER BUILD AND GLOBAL EXPANSION, YOTTA DATA SERVICES
“AI workloads are fundamentally reshaping data centre design, with GPU clusters pushing rack densities from the traditional 6–10 kW range to 40–50 kW and beyond. At Yotta, we have redesigned our campuses to be AI-native from day one. Our hyperscale facilities in Navi Mumbai and Greater Noida are purpose-built for high-density GPU environments, featuring direct liquid-to-chip cooling, rear-door heat exchangers, and contained airflow to efficiently manage heat. The electrical backbone has been strengthened with captive power, high-capacity transformers, and modular distribution to scale rapidly as GPU demand grows. Networking is equally critical, as AI training requires ultra-low latency and high throughput. High-speed fiber and optimized spine-leaf architectures ensure future- ready, sovereign infrastructure that can scale reliably to thousands of GPUs without compromising efficiency or uptime.
India’s digital future will be distributed, not centralized, and edge, hybrid cloud, and AI-optimized infrastructure are central to this vision. As AI, 5G, fintech, and manufacturing workloads grow, latency becomes critical, making edge infrastructure essential to process data closer to where it is generated, while also meeting regulatory and sovereignty requirements. Enterprises are increasingly moving toward hybrid cloud models, seeking the agility of public cloud alongside the control and compliance of private infrastructure. Through our hyperscale campuses and AI- HPC cloud platforms, customers can seamlessly shift between colocation, private cloud, and GPU-as-a-Service depending on workload needs. AI-optimized infrastructure sits at the core: India needs domestic, scalable compute capacity to power its AI ambitions, and our focus is on building that backbone locally so growth remains sovereign, secure, and sustainable.
Balancing rapid capacity expansion with sustainability is critical, as AI significantly increases power consumption. Our Greater Noida campus operates on 100% renewable energy at current load, and Navi Mumbai is around 80%, with a clear roadmap toward full green alignment. Optimized cooling systems-including adiabatic chillers, direct-to-chip liquid cooling, closed-loop systems, and efficient airflow management—deliver a PUE of <1.4 on air-cooled CPU workloads and <1.2 on liquid-cooled GPU workloads, reducing both energy and water usage while maintaining optimal operating temperatures. Over the next three years, competitiveness will be defined by next-generation GPUs, large-scale liquid cooling, AI-led operations with predictive maintenance, automated orchestration, real-time energy optimization, and modular builds beyond metro cities. Ultimately, success will not be measured by megawatts alone, but by smarter, greener, sovereign infrastructure that scales with India’s AI ambitions.”
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Scaling AI-ready infrastructure to position India as a global AI and data centre hub
AMIT LUTHRA
MANAGING DIRECTOR - INDIA, LENOVO ISG
“As India’s data centre industry gears up to expand fivefold by 2030, fuelled by AI, cloud adoption, rising data volumes, and data localisation requirements, Lenovo is strengthening the nation’s digital backbone through local manufacturing, advanced engineering, and hybrid production-ready solutions. We have commenced production of AI-optimised servers at our Puducherry facility and operate an Infrastructure R&D lab in Bengaluru to design, validate, and customise data centre systems for India’s operational, security, and scale requirements. Our latest Think Systems and Think Edge inferencing servers are purpose-built for every inferencing workload and vertical, featuring advanced memory, networking, and 5x GPU performance. In addition, our Hybrid AI Advantage and Hybrid AI Factory frameworks enable organisations to deploy pre-validated AI platforms that integrate infrastructure, software, orchestration, and services, accelerating outcomes while reducing deployment risk and ensuring AI-ready hyperscale capacity.
India is steadily positioning itself as a strategic force in the global AI infrastructure landscape as enterprises move from experimentation to large-scale, real-world inferencing. This shift is increasing demand for scalable, secure, and energy-efficient compute platforms across industries. With the global AI inference infrastructure market projected to grow from $5 billion in 2024 to approximately $48.8 billion by 2030, India’s deep engineering talent, supportive policy environment, and rising hyperscale investments position it to play a larger role in global infrastructure development and solution innovation. Energy-optimised technologies such as Lenovo’s 6th-generation Neptune liquid-cooling systems can reduce data centre energy consumption by up to 40% while enabling high-density AI workloads, which is critical as AI moves into mass deployment. With these capabilities, India can emerge as a hub for building scalable and secure AI computing platforms and exporting infrastructure expertise and digital solutions to global markets.
Building a globally competitive, AI-ready data centre ecosystem will require strong collaboration among cloud service providers, technology companies, system integrators, and software innovators. Initiatives such as AI Innovators and Hybrid AI Factory partnerships, including pre-validated platforms with Nutanix, demonstrate how integrated stacks can help organisations transition rapidly from pilot AI projects to production inferencing environments. Sovereign AI data centre frameworks developed with strategic partners further support secure, regulation-aligned digital infrastructure, while collaboration with government bodies, academia, and sustainability partners will remain essential for talent development, energy efficiency, and greener data centre operations at scale.”
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Enabling scalable AI infrastructure to advance India’s global digital ambitions
DARSSHAN SOMAIYA
HEAD - STRATEGIC PARTNERS & ALLIANCES, INDIA AND SAARC, HITACHI VANTARA
“At Hitachi Vantara, we are deeply committed to building the infrastructure that enterprises need to scale AI at speed and with confidence. Our focus is on delivering integrated platforms that combine high-performance storage, accelerated compute, and unified data services so organisations can power generative AI, analytics, and mission-critical applications reliably and efficiently. Our Hitachi iQ portfolio, including the modular M Series, enables scalable AI-ready infrastructure that addresses evolving business requirements and future demands. These solutions are designed to simplify and accelerate enterprise AI adoption while ensuring data governance and compliance within existing data centre environments. Our engagement with partners and customers in India reflects our belief that modern, reliable data foundations are essential to unlocking measurable value from AI and supporting hyperscale-ready capacity as demand continues to grow.
India is rapidly emerging as a strategic hub in the global AI and digital infrastructure ecosystem. With increasing demand for low-latency services, local data residency, and hybrid cloud capabilities, the country is well positioned to support both domestic and international workloads. AI-capable data centres are becoming critical infrastructure, enabling secure, resilient, and sovereign digital services across industries. Over the next decade, India’s role will extend beyond capacity expansion to deeper participation across the AI value chain, including modernising data infrastructure, enabling industry-specific AI use cases, and strengthening ecosystem partnerships across technology providers, hyperscalers, and system integrators. By building scalable and energy-efficient environments, India can anchor regional AI growth while accelerating digital transformation across sectors, aligning with our vision of helping enterprises convert growing data complexity into measurable business value.
Strategic partnerships are foundational to building a robust, AI-ready data centre ecosystem. At Hitachi Vantara, we collaborate with technology leaders such as Supermicro and NVIDIA to integrate advanced compute, storage, and AI-oriented architectures that enhance performance, scalability, and efficiency. These alliances enable customers to adopt unified platforms that bring compute and data closer together, reducing operational complexity and accelerating innovation. Collaboration with cloud providers, system integrators, hyperscalers, and local implementation partners will remain essential to bridge capability gaps and tailor solutions to industry and regional requirements. Through these multi-layered partnerships, we are supporting India’s continued emergence as a globally competitive AI and data centre hub.”
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Securing India’s hyperscale AI growth with prevention-first, AI-driven cyber security
MANISH ALSHI
SENIOR DIRECTOR, CHANNELS & ALLIANCES, INDIA & SOUTH ASIA, CHECK POINT SOFTWARE TECHNOLOGIES
“India’s rapid AI adoption and hyperscale cloud growth are fundamentally expanding the attack surface across data centres. According to JLL India’s 2024 report, India’s data centre capacity is expected to cross 1,800 MW by 2026, nearly doubling from 2023 levels. This hyperscale growth requires a shift from perimeter-based protection to AI-driven, prevention-first security. At Check Point, we are scaling AI-ready security for India’s hyperscale data centre environments through our Hybrid Mesh Network Security pillar, delivering unified enforcement across on-premises data centres, hybrid cloud, SASE, and branch environments. Our AI-powered control plane ensures consistent policy enforcement and real-time threat prevention at hyperscale performance levels. Check Point ThreatCloud AI, which analyses data from over 2 billion websites, emails, and sources daily, provides hyperscale-grade threat intelligence to detect zero-day and AI-driven attacks in real time. As AI workloads increase east- west traffic inside data centres, we are strengthening our Exposure Management solutions, enabling continuous threat exposure management to prioritise vulnerabilities and accelerate secure remediation across AI-powered infrastructure environments.
India is positioned to become one of the most strategic AI and hyperscale infrastructure hubs globally. With strong government backing under initiatives such as the IndiaAI Mission and rapid cloud adoption across BFSI, manufacturing, telecom, and digital public infrastructure, India is evolving from a consumption market to an innovation and AI deployment powerhouse. IDC projects AI spending will grow at 2.2 times the rate of overall digital technology spending over the next three years, generating more than $115 billion in economic impact by 2027. Combined with expanding data centre capacity and a digital-first economy, India will play a pivotal role in hosting AI workloads, training models, and delivering digital services across APAC, the Middle East, and Africa, while strengthening its role in the global AI value chain.
India’s rise as a global data centre hub will depend on ecosystem collaboration across hyperscalers, telecom operators, cloud service providers, system integrators, managed security service providers, regulators, and compliance bodies. Secure-by-design hybrid cloud environments, Zero Trust Architecture, NIST-aligned frameworks, and alignment with the Digital Personal Data Protection Act will be critical. As a 100% channel-driven company, we see partners acting as trusted advisors, integrating AI-powered, prevention-first security into complex enterprise and hyperscale environments. Hyperscale without resilience is risk; hyperscale secured by design positions India as a global digital trust leader.”
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Advancing AI-ready storage infrastructure for India’s expanding data centre ecosystem
OWAIS MOHAMMED
SALES DIRECTOR - INDIA, THE MIDDLE EAST, AND AFRICA, WESTERN DIGITAL
“At our core, WD is focused on enabling infrastructure that keeps pace with the exploding scale of AI and cloud-driven data growth. Data centre capacity today is not just about raw compute; it is about delivering reliable, efficient storage at scale, fundamental to the AI ecosystem. This is reflected in our customer-centric roadmap, reoriented around technology innovations that deliver capacity, performance and efficiency across workloads. At our recent Innovation Day, we highlighted this strategy with the world’s highest capacity 40TB UltraSMR ePMR HDD, now in hyperscale qualification with ramp production planned later this year. We also outlined a clear path toward 60TB ePMR and ultimately 100TB+ HAMR capacities estimated by 2029. Offering both ePMR and HAMR in parallel allows data centre partners to anticipate capacity growth without disruptive redesigns, providing predictability in capacity planning and economics as AI workloads consume, generate and retain ever-larger data sets.
Beyond capacity scale, we are focused on performance- or power-optimised drives that improve efficiency and total cost of ownership, enabling operators to scale reliably while optimising bandwidth or energy efficiency depending on workload requirements.
We see India steadily evolving into a strategic node in the global AI and data centre ecosystem, supported by rapid growth in domestic data centre capacity and expanding adoption of cloud and AI-led workloads. As these workloads scale, they drive demand for infrastructure that supports compute intensity while enabling the ability to store, access and retain massive volumes of data over time. Approximately 80% of data in data centres is stored on HDDs, underscoring the importance of scalable, high-capacity storage across the AI lifecycle. India’s combination of engineering talent, market scale and an expanding data centre footprint positions it to support domestic digital growth and global data workflows, particularly in storage and long-term data retention at scale.
India’s emergence as a global data centre hub will be driven by deep partnerships across cloud, core and edge ecosystems. Collaboration with global and local cloud service providers and large data centre operators enables co-innovation around capacity density, performance and power efficiency, ensuring solutions align with real-world deployment needs and long-term scalability. Technology and platform partnerships that reduce integration complexity are equally important, extending hyperscale storage economics into broader enterprise environments without disruptive architectural changes. Together, these partnerships support scalable, resilient and AI-ready data centre infrastructure aligned with evolving AI workloads.”
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Building scalable, GPU-ready infrastructure for India’s AI-led data centre growth
PANKAJ MALIK
CEO AND WHOLE-TIME DIRECTOR, INVENIA-STL NETWORKS
“Invenia-STL Networks is positioning its network and data infrastructure strategy to meet the evolving demands of AI-driven and high-performance workloads. As enterprises scale GPU-dense environments, rapid parallel processing and ultra-low-latency data exchange, infrastructure design must move beyond traditional models. We are focused on enabling scalable, AI-ready architectures that support distributed, high-throughput compute environments. Our service portfolio builds on deep expertise across enterprise and on-premises data centres and supports the shift toward distributed digital infrastructure. As AI workloads expand, compute is increasingly shifting from centralised facilities to a core-to-edge architecture prioritising low latency, high availability and predictable performance. We integrate scalable data centre design, high-capacity fibre networks, automation-led operations and cybersecurity capabilities to support high-density, GPU-intensive environments. In parallel, we are expanding our managed services portfolio across data centres, networks, cloud and edge. Together, these capabilities position Invenia-STL Networks as a full-stack enabler of AI-ready infrastructure, delivering scalable, resilient and future-ready platforms for GPU-driven compute growth.
India is set to play a pivotal role in the global AI and data centre value chain, evolving from a consumption market into an innovation-driven and sovereign digital infrastructure hub. Its expanding digital economy, exponential data generation and growing AI adoption are accelerating demand for domestic compute capacity. We anticipate multi-gigawatt data centre parks and AI compute campuses built for hyperscale cloud, GPU-intensive workloads and high-performance computing. Growth will be reinforced by deeper partnerships with global cloud providers, technology OEMs and semiconductor ecosystems, positioning India as a preferred destination for next-generation infrastructure investment. Strengthened data protection frameworks, localisation priorities, renewable energy integration and energy-efficient design will further support sustainability-led expansion across the AI infrastructure lifecycle.
India’s ambition to become a global data centre hub will depend on coordinated partnerships across the digital infrastructure value chain, spanning AI-optimised compute, renewable energy and advanced cooling, sovereign cloud ecosystems, high-capacity fibre and subsea connectivity, and distributed edge infrastructure. Strategic alignment between hyperscalers, AI infrastructure providers, telecom operators, semiconductor players and energy developers will be critical to building scalable, GPU-ready environments. Through automation-led deployment models and integrated compute-network-cloud frameworks, we enable high-density, low-latency connectivity while accelerating capacity rollout and ensuring operational stability. Ultimately, ecosystem-led collaboration uniting compute, connectivity, energy and policy will define India’s rise as a cohesive AI-ready infrastructure platform.”
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Strengthening scalable, secure storage foundations for India’s AI and hyperscale expansion
SAMEER BHATIA
SENIOR REGIONAL DIRECTOR - INDIA, MIDDLE EAST, TURKEY AND AFRICA, SEAGATE
“As India accelerates AI adoption and hyperscale data centre expansion, Seagate is enabling this growth through sustained innovation in storage density, security and long-term data stewardship. AI workloads are fundamentally reshaping infrastructure requirements by driving exponential data creation, increasingly complex models and longer data lifecycles. This evolution demands massive, cost-efficient storage architectures that scale intelligently while preserving data as a durable, high-value asset.
To support this shift, we are advancing higher-density storage technologies, including next- generation innovations such as Heat-Assisted Magnetic Recording (HAMR) — now in volume production — paving the way for multi-terabyte capacity growth beyond 10TB per disk. By increasing capacity per disk and embedding data integrity and security at the foundation, we enable data centre operators, cloud providers and channel partners to support larger AI models and expanding data assets while addressing power, footprint and operational complexity. Integrating drive-level security and intelligent software allows enterprises and cloud providers to deploy AI-ready infrastructure that balances performance, capacity, resilience and economics, delivering superior value per terabyte across the data lifecycle as AI environments scale in sophistication and intensity.
India is well positioned to play an increasingly important role in the global AI and data centre value chain over the next decade. Rapid digital adoption, expanding cloud and edge footprints, and sustained investment momentum are moving the country beyond a consumption market toward becoming a strategic hub for innovation and engineering. Collaboration with cloud service providers, system integrators and policymakers enables the development of scalable architectures while supporting AI adoption across cloud, edge and enterprise environments. For the channel ecosystem, these partnerships create opportunities to deliver integrated AI-ready platforms tailored to diverse customer requirements, enabling faster response to rising demand and accelerating deployment across sectors.
Seagate remains committed to advancing innovation along a long-term roadmap that balances today’s operational priorities with the evolving requirements of future AI and hyperscale workloads. Through continued focus on high-density storage technologies, integrated security and sustainable infrastructure design, we empower enterprises and partners to unlock the intrinsic value of data while building resilient, scalable and economically viable AI-ready data centre ecosystems for sustained growth.”
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