Future-Proofing Data Centers for the AI Era

AI adoption is straining data centers with soaring power, cooling, and efficiency needs. U.S. energy use may triple by 2030 as GPU-heavy workloads expand. Many firms are shifting AI from cloud to on-premises to reduce latency, costs, and regulatory risks. Outdated servers, limited rack density, and inefficient cooling add challenges. Solutions like liquid cooling, GPU-optimized systems, and scalable infrastructure from Supermicro and NVIDIA help enterprises modernize for today’s AI demands while preparing for future growth.

AI workloads driving massive power growth.
Energy use may triple by 2030.
Shift from cloud to on-premises.
Liquid cooling boosts efficiency by 40%.
Supermicro + NVIDIA enable scalable AI data centers.

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Has the company allocated budget for more computing power? *

Yes
No

How would you describe your role in the IT Decision-Making process? *

Main Decision Maker
Buyer
Influencer
Evaluator/Recommended
Part of a committee or team

Do your applications scale and benefit from more cores with in each CPU? *

Yes
No

Do you need more CPU work performed per watt of electricity consumed? *

Yes
No

Is there a need for wide range of servers and storage systems that contain the latest CPU? *

Yes
No

When do you estimate the need for new servers? *

Less than 1 Month
1-3 Months
4-6 Months
7-12 Months

If yes, what is an estimate?

$1M – 10M
$10M to $50M
$50M to $100M
$100M to $250M
$250M to $500M
Over $500M

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