Data Center

Partnering for the AI Ascent: Critical role of Colocation Providers in the AI Infrastructure Boom

As the global race to adopt and scale artificial intelligence (AI) accelerates from generative AI applications to machine learning-powered analytics, organisations are pushing the boundaries of innovation. But while algorithms and data often take center stage, there’s another crucial component that enables this technological leap: infrastructure. More specifically, the role of colocation providers is emerging as pivotal in AI driven transformation.

According to Dell’Oro Group, global spending on AI infrastructure including servers, networking, and data center hardware is expected to reach $150 billion annually by 2027, growing at a compound annual growth rate (CAGR) of over 40%. Meanwhile, Synergy Research Group reports that over 60% of enterprises deploying AI workloads are actively leveraging colocation facilities due to the need for high-density, scalable environments and proximity to data ecosystems. AI’s potential cannot be unlocked without the right physical and digital infrastructure and colocation providers are stepping in as strategic enablers of this transformation.

The Infrastructure Strain of AI

Unlike traditional IT workloads, AI applications require massive computational resources, dense GPU clusters, ultra-fast data throughput, and uninterrupted uptime. Traditional enterprise data centers, originally designed for more moderate workloads, are increasingly unable to meet the demands of modern AI deployments. Limitations in power delivery, cooling capabilities, space, and network latency become significant bottlenecks. Enterprises that attempt to scale AI on-premises often face long lead times for infrastructure expansion, high capital expenditures, and operational inefficiencies. This is where colocation data centers offer a compelling, scalable and efficient alternative.

Why Colocation is the Backbone of AI Deployment

1. Rapid Scalability: AI projects often require rapid scaling of compute power due to the high computational demands of training models or running inference tasks. Traditional data center builds, or infrastructure procurement, can take months, but with colocation, companies can quickly expand their capacity. Colocation providers offer pre-built, ready-to-use data center space with the required power and connectivity. Organisations can scale up or down as their AI needs evolve without waiting for the lengthy construction or procurement cycles that are often associated with in-house data centers.

2. High-Density Capabilities: AI workloads, particularly those involving machine learning (ML) and deep learning (DL), require specialised hardware such as Graphics Processing Units (GPUs). These GPUs can consume significant power, with some racks filled with GPUs requiring 30kW or more of power. Colocation facilities are designed to handle such high-density infrastructure. Many leading colocation providers have invested in advanced cooling systems, such as liquid cooling, to manage the extreme heat generated by these high-performance computing setups. Additionally, custom rack designs allow for optimal airflow and power distribution, ensuring that these systems run efficiently without overheating or consuming excessive power.

3. Proximity to AI Ecosystems: AI systems rely on diverse data sources like large datasets, edge devices, cloud services, and data lakes. Colocation centers are strategically located to provide low-latency interconnects, meaning that data can flow seamlessly between devices and services without delays. Many colocation facilities also offer cloud on ramps, which are direct connections to cloud providers, making it easier for organisations to integrate AI applications with public or hybrid cloud services. Additionally, peering exchanges allow for fast, high-volume data transfers between different networks, creating a rich digital ecosystem that supports the complex and dynamic workflows of AI.

4. Cost Optimisation: Building and maintaining a private data center can be prohibitively expensive for many organisations, especially startups and smaller enterprises. Colocation allows these companies to share infrastructure costs with other tenants, benefiting from the economies of scale. Instead of investing in land, physical infrastructure, cooling, power, and network management, businesses can rent space, power, and connectivity from colocation providers. This makes it much more affordable for companies to deploy AI solutions without the large capital expenditures associated with traditional data center ownership.

5. Security & Compliance: AI applications often involve handling sensitive data, such as personal information, proprietary algorithms, or research data. Colocation providers offer enterprise-grade physical security (such as biometric access controls, surveillance, and on-site security personnel) to ensure that only authorised personnel have access to the hardware. They also provide cybersecurity measures such as firewalls, DDoS protection, and intrusion detection systems to protect against external threats. Moreover, many colocation facilities are compliant with various regulatory standards (e.g., DPDP, GDPR, HIPAA, SOC 2), which is crucial for organisations that need to meet legal and industry-specific requirements regarding data privacy and security.

Yotta: Leading the Charge in AI-Ready Infrastructure

While many colocation providers are only beginning to adapt to AI-centric demands, Yotta is already several steps ahead.

1. Purpose-Built for the AI Era: Yotta’s data centers are designed with AI workloads in mind. From ultra-high rack densities to advanced cooling solutions like direct-to-chip liquid cooling, Yotta is ready to host the most demanding AI infrastructure. Their facilities can support multi-megawatt deployments of GPUs, enabling customers to scale seamlessly.

2. Hyperconnectivity at Core: Yotta’s hyperscale data center parks are strategically designed with hyperconnectivity at the heart of their architecture. As Asia’s largest hyperscale data center infrastructure, Yotta offers seamless and direct connectivity to all major cloud service providers, internet exchanges, telcos, and content delivery networks (CDNs). This rich interconnection fabric is crucial, especially for data-intensive workloads like Artificial Intelligence (AI), Machine Learning (ML), real-time analytics, and IoT. We also actively implement efficient networking protocols and software-defined networking (SDN) to optimise bandwidth allocation, reduce congestion, and support the enormous east-west traffic typical in AI training clusters. The result is greater throughput, lower latency, and improved AI training times.

3. Integrated AI Infrastructure & Services: Yotta is more than just a space provider — it delivers a vertically integrated AI infrastructure ecosystem. At the heart of this is Shakti Cloud, India’s fastest and largest AI-HPC supercomputer, which offers access to high-performance GPU clusters, AI endpoints, and serverless GPUs on demand. This model allows developers and enterprises to build, test, and deploy AI models without upfront infrastructure commitments. With Shakti Cloud:

– Serverless GPUs eliminate provisioning delays enabling instant, usage-based access to compute resources.

– AI endpoints offer pre-configured environments for training, fine-tuning, and inferencing AI models.

– GPU clusters enable parallel processing and distributed training for large-scale AI and LLM projects.

Additionally, Yotta provides hybrid and multi-cloud management services, allowing enterprises to nify deployments across private, public, and colocation infrastructure. This is critical as many AI pipelines span multiple environments and demand consistent performance and governance. From infrastructure provisioning to managed services, Yotta empowers businesses to focus on building and deploying AI models not managing underlying infrastructure.

4. Strategic Geographic Advantage: Yotta’s data center parks are strategically located across key economic and digital hubs in India including Navi Mumbai, Greater Noida, and Gujarat ensuring proximity to major business centers, cloud zones, and network exchanges. This geographic distribution minimises latency and enhances data sovereignty for businesses operating in regulated environments. Additionally, this pan-India presence supports edge AI deployments and ensures business continuity with multi-region failover and disaster recovery capabilities.

The Future of AI is Built Together

As organisations race to capitalise on AI, the importance of choosing the right infrastructure partner cannot be overstated. Colocation providers offer the agility, scale, and reliability needed to fuel this transformation. And among them, Yotta stands out as a future-ready pioneer, empowering businesses to embrace AI without compromise. Whether you’re a startup building your first model or a global enterprise training LLMs, Yotta ensures your infrastructure grows with your ambitions.