×
GenAI Strains Data Centers, Highlights Urgent Need for Modernization
Written by
Published on
Join our daily newsletter for breaking news, product launches and deals, research breakdowns, and other industry-leading AI coverage
Join Now

The rapid rise of generative AI is straining data centers and driving urgent modernization efforts, while budgets remain tight. As CIOs rush to bring genAI capabilities online, they face the daunting challenge of providing the immense power, cooling, and processing required to support these demanding workloads.

The staggering energy demands of genAI: The scale of resources needed to support genAI is hard to comprehend, with ChatGPT alone estimated to consume enough daily energy to power 33,000 US homes.

  • Data centers accounted for 4% of US energy consumption in 2022, and this figure is projected to reach 6% by 2026, according to the International Energy Agency (IEA).
  • The decades-long scale-up for enterprise computing has already stretched global electrical supplies to the limit, and the new demands of AI data centers threaten to surpass current capacity.

Mounting pressures on CIOs to modernize: In addition to genAI, factors such as business models, licensing costs, and modern, highly demanding workloads are driving the need for data center modernization.

  • Older hardware requires more cores to deliver the desired performance, potentially leading to significant cost increases without major changes to the technology stack.
  • Power and cooling costs continue to rise, while aging data center infrastructure becomes less reliable and more expensive to maintain.
  • Data centers have limited unused space or power drops for deploying additional gear to handle increasing workload demands.

The role of AMD EPYC CPUs in achieving efficiency: AMD EPYC CPUs can help data centers become more efficient by enabling them to use fewer servers and less power to perform the same amount of work compared to the competition.

  • The AMD EPYC 9474F CPU allows data centers to use up to 47% less power and achieve up to a 42% reduction in software licensing costs when compared to legacy Intel Platinum 8280 CPU-based servers.
  • Upgrading to AMD EPYC CPUs can fully recoup the hardware investment cost in approximately two months, making older Intel servers prime targets for replacement due to their relative inefficiency and depreciation status.
  • AMD has strong technical relationships across the server ecosystem, ensuring a smooth transition for CIOs without compromising trusted suppliers.

Navigating the path forward: As CIOs grapple with the urgent need to modernize their data centers to support the rise of genAI and other demanding workloads, they must find ways to meet intense resource requirements without expanding their footprint or consuming additional power.

  • Embracing more efficient technologies, such as AMD EPYC CPUs, can help data centers reduce power consumption and costs while supporting the coming workload onslaught.
  • CIOs must strike a balance between rapid modernization efforts and budget constraints, prioritizing investments that deliver the greatest efficiency gains and long-term value.
  • Collaboration with trusted partners across the server ecosystem will be crucial in navigating this complex landscape and ensuring a smooth transition to more efficient, future-ready data center infrastructures.
The cost of (AI) business: Getting the most out your data center now - and in the future

Recent News

Deutsche Telekom unveils Magenta AI search tool with Perplexity integration

European telecom providers are integrating AI search tools into their apps as customer service demands shift beyond basic support functions.

AI-powered confessional debuts at Swiss church

Religious institutions explore AI-powered spiritual guidance as traditional churches face declining attendance and seek to bridge generational gaps in faith communities.

AI PDF’s rapid user growth demonstrates the power of thoughtful ‘AI wrappers’

Focused PDF analysis tool reaches half a million users, demonstrating market appetite for specialized AI solutions that tackle specific document processing needs.