Anbu Shanmugam
COO, Digital Connexion

India’s data economy is growing rapidly, driven by a mobile-first population and a steadily increasing number of internet users. With over 950 million active users and average monthly data consumption crossing 20.27 GB in 2024, the country is on track to become a global leader in data consumption. At the core of this transformation are data centers, the essential infrastructure supporting everything from e-commerce and cloud services to AI workloads—quietly powering the country’s digital economy.

As businesses invest more in AI, the amount and complexity of data they handle is growing quickly. Training large language models, running deep learning algorithms, and processing massive datasets in real time require high-performance computing resources that go far beyond the capabilities of traditional infrastructure.

To meet these escalating demands for power, speed, and precision, colocation solutions have emerged as a practical, high-impact solution—bridging the gap between cloud scalability and on-premises control. Today’s high-density deployments are purpose-built for AI, enabling significantly more computing equipment to be packed into the same physical footprint—measured in ‘racks,’ standardized frames that house servers and other hardware. These AI-driven operations rely on GPUs and specialized accelerators that consume far more power per rack than legacy systems, often stretching the capabilities of conventional data centers. In just two years, average power densities have jumped from 8 kilowatts (kW) per rack to 17 kW, with projections hitting 30 kW by 2027.

What sets these environments apart is their modularity. This allows businesses to grow their computing power as their AI needs increase, without overbuilding or incurring unnecessary costs. Advanced cooling technologies, including liquid and air-assisted systems, keep high-density setups efficient and reliable. With pre-engineered configurations and faster time to market, colocation providers help businesses stay agile in a fast-moving AI landscape. 

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