Unleashing AI's Transformative Impact on Data Center Evolution

The data center is a vital organ of the technological infrastructure that powers our modern world. These resources are necessary to store, process, and transfer large amounts of data, from streaming services to cloud computing and everything in between. However the traditional data center model faces many challenges as data demands increase and technology evolves. We introduce artificial intelligence (AI), a transformative technology that is changing the way data centers operate and thrive.

The transformative impact of AI on data centers is multifaceted, touching on various aspects from efficiency and optimization to security and predictive maintenance. Let's take a look at how AI is reshaping the evolving data center landscape

Below, we've gathered a few quotes from various experts in the field.

Ashish Arora – CEO, Nxtra By Airtel- “At Nxtra, we are at the forefront of building digitized, future-ready data centers. The integration of Artificial Intelligence (AI) in data centers is crucial toward creating smarter, more efficient, and resilient infrastructure. Through AI-driven tools, we aim to enhance operational and energy efficiency, build predictive maintenance capabilities, streamline automation of operations, automate security measures, and optimise capex utilization.

Through leveraging QR-based AI, we have remarkably boosted security accuracy by 100%, automating tracking and reducing manual efforts by 65%. Our AI-powered PAN India dashboard serves as an intelligent command center, proactively identifying risks, optimizing maintenance schedules, and achieving an impressive 30% reduction in man-hours. It facilitates predictive maintenance, enhances operational efficiency, improves report accuracy, and lowers corrective maintenance costs by 10%, contributing to the cost-effectiveness of our data centers.

With sustainability at the core of our data center operations, we are also harnessing the power of AI to optimise energy efficiency. AI plays a pivotal role in identifying high Power Usage Effectiveness (PUE) factors, resulting in a significant reduction in CO2 emissions through a 1% PUE decrease. Heat balancing techniques have further led to a 10% reduction in cooling loads, saving 3-4% on energy costs.”

These achievements spotlight our commitment to operational excellence, with AI shaping our data center capabilities in profound, quantifiable ways.

Vipin Jain, President, Datacenter Operations, CtrlS Datacenters- AI is not merely a technological progression; it's a paradigm shift with profound implications for the architecture and functionality of data centers. This integration has initiated a strategic revolution in server and processor design. Research forecasts a staggering growth in the global AI infrastructure market, projected to reach $422.55 billion by 2029, with a remarkable 44% CAGR by 2028. As we stride into the era of generative AI, the imperative for high-performance computing clusters becomes undeniable, with a change in design to accommodate the evolving landscape of AI applications.

Before advent of AI, the real-time monitoring and adjustment of power and cooling systems in data centers posed significant challenge. The integration of AI in cooling operations has empowered teams to efficiently regulate the thermal equilibrium of individual units, aligning them with specific workloads. In the space of medium to large-scale data centers, this dynamic balancing act becomes crucial for continuous efficiency optimization.

The early adoption of AI in data centers has proven advantageous for operators and clients alike. Proficient AI implementation not only optimizes real-time equipment efficiency but also enhances future planning precision. These operational enhancements lead to downstream benefits for clients, offering potential improvements in performance, reduced downtime risks, and the prospect of lower overall operational costs. Furthermore, with the increasing adoption of generative AI, the data center landscape is experiencing a significant change with anticipated expenditures expected to surpass $76 billion by 2028. Generative AI applications demand substantial computing and storage resources, prompting data centers to expand and invest in infrastructure. This trajectory of AI is not just transforming data centers; it's redefining the boundaries of technological possibilities.

Rajesh Kaushal, Vice President, Delta Electronics India- Over the past few years, AI has emerged as a game-changer in various industries, and the world of data centers is no exception. AI has revolutionized how data centers operate, making them more efficient, secure, and responsive than ever before.

One of the key benefits of AI in data centers is its ability to optimize resource allocation. With AI algorithms constantly analyzing data center operations, they can identify bottlenecks and inefficiencies and suggest improvements. By automatically adjusting workloads, AI ensures that resources are allocated most optimally, maximizing performance and minimizing costs.

Another crucial role that AI plays in data centers is in predictive maintenance. Traditional data center maintenance practices rely on scheduled inspections and routine replacements, which can be costly and time-consuming. However, with AI, data centers can proactively detect and address potential issues before they become critical. By analyzing real-time data from various sensors, AI algorithms can predict failures, schedule maintenance activities, and even suggest the most efficient ways to fix problems.

Security is another area where AI has proven to be indispensable in data centers. With cyber threats becoming increasingly sophisticated, traditional security measures are no longer sufficient. AI-powered security systems can analyze massive amounts of data, identify patterns, and detect anomalies in real-time. This helps data centers prevent and mitigate potential security breaches, ensuring the safety and integrity of critical data.

Moreover, AI has also made data centers more environmentally friendly. By analyzing data on energy consumption and workloads, AI algorithms can optimize power usage and cooling systems, reducing energy waste and carbon emissions. This contributes to a greener environment and helps data centers save on operational costs.

Sumit Mukhija, Executive Director & Chief Executive Officer, STT GDC India- Datacenter deployment technology choices have always dovetailed changes in the compute, storage, and network deployments. From 2-3KW per rack just about a decade ago to 10-15KW per rack in recent years, we have already seen almost a 5X increase in power densities, largely due to increasingly powerful CPUs that consume more power and server footprints becoming more and more compact. And now with AI infrastructure that uses high-end GPUs can go considerably higher to even 50 to 70 KW per rack. The good part is that all of our data centers are AI ready both technically and operationally. We can support densities ranging from 3KW to even 30KW per rack within the same facility with Air cooling and for customer-specific and even higher density requirements like 50-70KW per rack, we have the capability of deploying Liquid cooled setups in dedicated halls and floors within the same facility. Reliability, scalability, flexibility, and sustainability remain at the core of our Design philosophy and this together with operational excellence allows us to deliver on the most stringent of SLAs and enable Cloud and AI deployments at scale.

Vimal Kaw -  Senior Director - Products and Services, NTT Global Data Centers and Cloud Infrastructure, India- "As we endeavor to build future-ready data centers capable of handling the digital transformation needs of enterprises in a sustainable manner, AI is playing a significant role in this evolution. It is increasingly integrated into almost all aspects of data center operations and design. Many work processes in data centers are of a repetitive nature, and these are being automated through AI. This has helped us overcome a shortage of skilled human resources and optimize existing resources towards more specialized tasks.

AI has also optimized data center technologies in a significant way. AI-powered building automation systems take care of various strategic tasks, such as maintaining temperature at required levels, enhancing the implementation of the liquid cooling technology, conserving energy and water wastage by improving system efficiency. Additionally, it is being used to monitor human activity inside the data centers. Apart from this, AI-driven data analytics and machine learning algorithms enable better monitoring of equipment performance, predict downtime, and facilitate proactive maintenance to ensure the desired uptime, which is the benchmark for any data center’s success.

AI is also playing a highly impactful role in ensuring cybersecurity in data centers. It can continuously monitor digital assets, identify unusual activities, and ensure strict compliance with all security practices and protocols in real-time, 24x7. Thus, from a holistic perspective, AI is going to be a major enabler of efficiency, sustainability, cost-effectiveness, and security in the data centers of the future."

Sunil Gupta, Co-founder and CEO, Yotta- Artificial intelligence has been a transformative force in various industries, restructuring operations and enhancing performance over an extended period. Data holds immense significance for organizations, and effective data management is equally crucial. Once collected and analysed, this data has proven essential for strategic business decisions. Consequently, companies are directing investments towards advanced automation tools for data processing and transitioning to hyperscale data centers to modernize their IT infrastructure. The recent surge in data volume has given rise to hyperscale, high-performance facilities to innovate and integrate AI technologies, enabling autonomous task handling within their operations.

This however requires a remodeling of existing data centers. Generative AI models require a larger neural network—necessitating more hardware, more compute power, and subsequently, more cooling – resulting in the deployment of GPU clusters. Consequently, traditional setups are evolving towards denser server racks and advanced cooling mechanisms, including liquid cooling. There’s also a need for high-speed, low latency connectivity, allowing for faster, seamless data transfer.

With investments to the tune of $2 billion, our strategic collaboration with NVIDIA allows us to provide cutting-edge GPU solutions through Shakti Cloud, India's fastest & largest AI-HPC supercomputer. We have also worked consciously to go beyond conventional data center offerings and provide GPU-as-a-service to our end customers – an industry first. We also aim to scale up to 16,384 GPUs by June 2024, with the ultimate goal of reaching 32,768 GPUs by late 2025. Not only are these chips able to handle significantly higher workloads, but also allow connectivity through its proprietary Infiniband network, bringing high-speed, low-latency, scalable solutions to AI and cloud data centers.

As the adoption of AI and GenAI models becomes more widespread, Yotta will already be at the forefront of cutting-edge cloud services, enabling faster deployment of AI-based models, and significantly contributing to the Prime Minister’s Digital India mission.”