Adel Al-Ansari, Senior Director of Pre-Sales for Egypt, the Levant, and Turkey at Nutanix, confirmed that the rapid expansion in adopting artificial intelligence applications imposes new operational and technical challenges on data centers, stressing that infrastructure utilization efficiency has become the decisive standard for the success of these projects.
Infrastructure Challenges in the AI Era
During his participation in the Cairo ICT 2026 exhibition, Al-Ansari explained that modern data centers require massive investments, making resource utilization efficiency an economic and technical necessity. He pointed out that the challenge is no longer limited to providing servers, but has shifted to how to achieve maximum benefit from Graphics Processing Units (GPU), which are the most expensive component, in addition to managing the significant increase in energy consumption associated with AI workloads.
What is Practically Changing in Data Center Management?
Performance measurement standards in data centers are witnessing a radical shift, as the focus has begun to move from mere capacity provision to monitoring precise indicators such as:
- Power Usage Effectiveness (PUE).
- The cost of generating "Tokens" in artificial intelligence models.
- GPU utilization rates to reduce the need for continuous expansion in purchasing expensive hardware.
Nutanix Optimization Strategy
Al-Ansari revealed that the company is working on developing specialized solutions to improve infrastructure efficiency, based on its acquisition of the French company Ryax Technologies, which specializes in optimizing GPU performance. He also pointed to the pivotal role of container technology, as about 75% of modern artificial intelligence applications rely on this technology to ensure flexibility in managing and moving workloads.
Nutanix's current strategy relies on two pillars: the first is improving the efficiency of physical resources (GPU and energy), and the second is providing flexible platforms such as Nutanix Kubernetes Platform to manage artificial intelligence applications, which helps organizations expand in these technologies while maintaining control over operational expenses.