Data centers are the backbone of every application, web, and IT services these days, serving the needs of the end-user, SMBs, and enterprises alike. The evolving digital landscape, in particular, has had a tremendous effect on the growth trajectory and development of data center facilities worldwide. After all, changes in IT service delivery models—from on-premise to cloud—and the exponential growth of data have increased the demand for specialized facilities that can provide secure 24x7x365 access. This data deluge has been attributed to various sources, including smartphone penetration, the Internet of Things (IoT), rapid digital transformation, cloud adoption, and AI technologies.
Generative AI is changing the way we work, create, and live. Businesses and individuals are all trying to figure out what it means for the economy and our species but struggle as we don’t know what AI will be capable of or the costs and benefits of applying it. This transformation will require vast changes in computer architectures, networking topologies, and data center design.
The adoption of AI applications across industries has increased the demand for data centers capable of handling AI workloads. These are based on the Large Language Models (LLMs) fed with massive data sets for training purposes. More data leads to better training of the models, resulting in more accurate outcomes. This requires high-performance computing resources found only in data centers.
Generative AI is expected to accelerate this demand for computing power in data centers. Such facilities leverage specialized hardware, such as GPUs (Graphics Processing Units) and TPUs (Tensor Processing Units), to accelerate AI computations. Low-latency networks and high-bandwidth connections usually support this, ensuring seamless and rapid data transfer for near real-time delivery. It's still new as to how it plays out in the data center industry, but there's definitely going to be large-scale demand resulting in bigger data centers and hotter racks.
Moving forward, we might require specialized buildings supporting these AI models in their data center campus. Alternatively, companies are packing a lot of computation power into a single rack, and they are now trying to build infrastructure that is scalable and deployable across multiple regions and is as power-efficient as possible to support the dynamic nature of the AI applications.
Energy efficiency & sustainability
Generative AI can also play a vital role in driving energy efficiency by analyzing power usage patterns and dynamically optimizing energy consumption. AI-enabled data centers can significantly reduce energy wastage and environmental impact by optimizing cooling systems, power distribution, and workload allocation. Generative AI algorithms can be leveraged to design energy-efficient data centers by considering factors like location, weather prediction, temperature, airflow, and layout for better thermal management. This can reduce construction time and result in more efficient data centers with reduced operational costs.
AI-integrated Data Infrastructure
Artificial Intelligence (AI) is transforming data infrastructure, making it more intelligent and efficient. AI-driven data infrastructure automates tasks such as data cleansing, categorization, and anomaly detection, improving data accuracy and reducing manual efforts. AI-powered analytics tools also provide advanced insights, predictive modeling, and recommendations, enabling businesses to derive valuable insights from their data. This intelligent provisioning ensures that data centers operate at peak efficiency and prevents over-provisioning of resources.
Generate niche jobs
Even though ‘automation’ can help improve efficiencies in various sectors, including data centers, there is still a shortage of qualified data center engineers who can help tend to the daily needs of a massive facility. According to Uptime Institute, staffing requirements will reach nearly 2.3 million by 2025.
Every facility requires dedicated personnel skilled in cloud technologies, networking and cabling, expert knowledge about HVAC systems, familiarity with data center infrastructure management (DCIM) tools, and more. Data center operators will need a team of highly specialized individuals capable of monitoring, provisioning, providing customer support, mitigating untoward incidents, and troubleshooting various aspects of the facility.
These are some of the main aspects that have gained prominence with the uptick in data centers in India. And while data centers continue to grow rapidly, one must recognize the costs involved in setting up and managing one. All this includes acquiring land and construction work, equipping it with the right hardware to handle heavy AI workloads, highly specialized cooling systems, and hiring certified professionals to manage the facility. Leasing data center space to run Large Language Models and Generative AI workloads can also be a costly affair as they require additional power, which also requires efficient cooling solutions.
Despite this challenge, this symbiotic relationship between data centers and AI will continue to evolve along with advancements in computing and AI/ML technology. It will become increasingly vital, ushering in a new era of intelligent and sustainable data infrastructure. Embracing these transformative technologies will ensure that data centers can handle the demands of today but also future-proof their capacity to tackle the data challenges of tomorrow.
Ankit Saraiya is the Director and Head of the Data Center Vertical at Techno Electric & Engineering