The AI Boom Will Drive up Data Center Costs and the Need for Control

Data centers are the backbone of the digital economy, hosting the servers, networks, and software that power the internet and cloud services. Data centers consume a lot of electricity, accounting for about 1% of the global energy demand in 2019. As AI becomes more widespread and complex, data centers will need to upgrade their hardware and infrastructure to meet the growing demand for AI processing. This will increase the cost of operating data centers in several ways.

First, data centers will need to invest in more powerful and specialized processors, such as GPUs (graphics processing units), TPUs (tensor processing units), or FPGAs (field-programmable gate arrays), that can handle the massive parallel computations required by AI algorithms. These processors are more expensive than traditional CPUs (central processing units), and they also consume more energy and generate more heat. Data centers will need to buy more of these processors and install them into their servers, which will increase the capital expenditure and operational expenditure of data centers.

Second, data centers will need to expand their storage capacity and bandwidth to accommodate the large amounts of data that AI applications generate and consume. Data is the fuel of AI, and AI models need to access, process, and store huge volumes of data from various sources, such as images, videos, text, audio, sensors, etc. Data centers will need to add more hard drives, solid-state drives, or flash memory devices to their servers, as well as upgrade their network equipment and cables to support faster data transfer speeds. These upgrades will also increase the cost of data center hardware and maintenance.

Third, data centers will need to improve their cooling systems and energy efficiency to cope with the higher heat output and power consumption of AI processors. Cooling is one of the major challenges and expenses for data centers, as it accounts for about 40% of the total energy consumption of data centers. AI processors generate more heat than CPUs, which means that data centers will need to install more fans, air conditioners, liquid cooling systems, or other cooling solutions to prevent overheating and damage to the hardware. Data centers will also need to optimize their energy usage and source more renewable energy to reduce their carbon footprint and electricity bills.

To effectively manage these escalating costs, data centers need to leverage next-generation Data Center Infrastructure Management (DCIM) software. DCIM provides comprehensive oversight and control over data center operations, allowing administrators to monitor and manage power and cooling in real time. It can optimize energy consumption by identifying underutilized resources and improve cooling efficiency by detecting hotspots. By providing analytics about power usage, space, and cooling capacity, DCIM software can help data centers plan for future expansion or upgrades more accurately, potentially reducing capital and operational expenditures. Through real-time monitoring, predictive analytics, and resource optimization, DCIM software could be instrumental in controlling the increasing costs associated with running data centers.

In summary, AI is going to increase the cost of operating data centers by requiring more powerful processors, more storage capacity and bandwidth, and more cooling systems and energy efficiency. Data centers will have to invest heavily in upgrading their hardware and infrastructure to support the growing demand for AI services. However, this investment may also pay off in the long run, as AI coupled with management solutions like DCIM software can also help data centers improve their performance, reliability, security, and sustainability.

Find out how DCIM software can deliver a fast return on your investment. Schedule a free one-on-one demo of Hyperview today.