How will artificial intelligence impact the data center market?
Clearly, artificial intelligence is a significantly growing force in digital transformation and deserves continued attention from all industries.
As Fortune 500 companies look for the next frontier for business growth, artificial intelligence (AI) has taken center stage, and its growing popularity has far-reaching implications for the data center industry.
The growth in data center demand over the past 20 years has been driven by storage and compute needs and the migration from on-premises to cloud infrastructure. New advancements in software applications and IT have changed customer needs, prompting significant growth in data center inventory, as shown in the chart below.
Figure 1: Total primary market inventory (MW)
So, how will the rise of artificial intelligence affect the development and demand of data centers?
Currently, there are still many unknowns. How will artificial intelligence affect employment, infrastructure development, energy use and privacy? Can existing and under-construction data centers support the development of artificial intelligence? Will hyperscalers seek facility development in edge markets where lower-cost power supplies and cheaper land are available?
What is Artificial Intelligence?
ChatGPT is a chatbot that understands and responds to user input, putting AI in the spotlight again across the industry. And it quickly set off a wave of AI craze around the world. Moreover, ChatGPT is also the fastest application to reach 100 million users. So, looking back, what exactly is AI?
AI has two machine learning functions:
- Artificial intelligence training: building a model from the input of the data set
- Artificial intelligence inference: learning from the data set Generate predictions, solutions, and actionable results
These features don’t have to work in the same place at the same time. Each has its own unique storage, power and computing needs. In its most basic form, AI can help answer questions or draft emails, and advanced features will become more sophisticated in the future.
AI Application in Data Centers
At present, the cultural influence of artificial intelligence is at an all-time high. However, without the same popular awareness, data center operators have been leveraging AI in the following ways: improving energy efficiency by proactively managing power usage effectiveness (PUE) and monitoring the facility’s hardware by proactively detecting and remediating issues to extend its lifespan and assist in planning the physical space of the data center while also monitoring temperature and humidity limits.
The use cases for artificial intelligence are not limited to data center operators, but also apply to users. Customers can deploy AI software from the data center for service chatbots, marketing analytics, data visualization, lead generation for business development, streamlined HR recruiting and onboarding processes, self-driving vehicles, and insurance and fraud detection.
What does this mean for data centers?
The two basic elements of artificial intelligence machine learning require different data center requirements. AI training can take place in relatively isolated environments. High computing power is necessary, but does not require close proximity to end users or interconnection with other facilities. Data centers located in rural areas where land costs are lower are an example of such a facility. AI inference requires extremely high performance and low latency for end users and applications to interact with models in real time. An example of a similar facility is an edge data center in an urban environment.
In a survey by S&P Global, 84.6% of respondents said their organization’s AI/ML infrastructure spending will increase slightly or significantly. CBRE expects increased demand for data center development in tertiary markets such as Des Moines, Charlotte and Columbus.
Power constraints remain a challenge, and AI applications consume large amounts of power. On the hardware side, AI requires high-performance processors that require more power than traditional data center processors. In addition to consuming more power, improved cooling technology is needed to reduce downtime. Due to the limitations of traditional air-cooled chillers, liquid cooling is the first choice for high-performance chips.
In addition, markets that may be adversely affected by this demand for liquid cooling due to water shortages include Phoenix, Arizona and Southern California in the United States. Overall, there is an incentive to develop AI-specific data centers in markets with abundant power supply, low energy costs and low land prices to handle these complex and high-performance workloads.
Artificial intelligence not only consumes electricity, but also reduces electricity usage. IDC predicts that global revenue from AI will reach $154 billion by 2023 and exceed $300 billion by 2026. This represents a compound annual growth rate of 27%, which is more than four times the growth rate of total IT spending during the same period. The United States is expected to become the largest AI market, accounting for more than 50% of total global spending.
Clearly, artificial intelligence is a significantly growing force in digital transformation and deserves continued attention from all industries.
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