The rapid adoption of artificial intelligence is redefining the role of the data center around the world. Workloads associated with artificial intelligence can multiply by five or even ten the energy consumption of servers within a data center, compared to traditional environments, which forces us to rethink the physical and operational architecture of these facilities.
Over the years, the data center has evolved to support relatively stable cloud services and enterprise applications. However, the rise of artificial intelligence requires each data center to manage increased demands for power, cooling and operational complexity, surpassing traditional planning models.
Added to this technical pressure is an increasingly demanding regulatory environment in terms of energy efficiency and sustainability. Adapting each data center is no longer a strategic option, but a necessity to ensure resilience, cost control and long-term growth.
Starting from this context, FNT Software, a leading provider of solutions for the integrated management of IT, telecommunications and data center infrastructures, has identified five key steps to successfully adapt a traditional data center to the demands of artificial intelligence.
Five steps to prepare your data center for the AI era
Data center transformation cannot be addressed through isolated expansions or one-off investments. It requires a structured strategy that combines technical analysis, operational optimization and long-term vision.
According to FNT Software, organizations should consider the following factors to modernize their data center:
- Assess the actual level of readiness, through comprehensive audits of power, cooling, physical occupancy, and network capacity within the data center. Without an accurate view of the current state, it is impossible to correctly size the impact of new AI loads.
- Ensure comprehensive visibility of the data center infrastructure, eliminating silos between IT teams and facilities. Unified documentation and real-time monitoring help identify critical dependencies and reduce operational risks.
- Optimize before expanding the data center, reviewing rack densities, electrical distribution and cooling efficiency. Many organizations can free up capacity without immediately resorting to large investments.
- Design the data center with scalability and flexibility, adopting modular architectures and systems prepared for higher energy densities. Simulation-based planning helps anticipate future scenarios.
- Integrate sustainability as a strategic axis in the data center, incorporating renewable energies, emissions control and transparent energy and water consumption metrics.
“Artificial intelligence is testing infrastructures that were not designed for this level of demand. The key is not only to add capacity, but to have complete visibility and structured planning to adapt the data center efficiently and sustainably,” highlights Stefan Kühn, computer documentation specialist at FNT Software.
Technological challenge and strategic decision
Through the FNT Command Platform solution, complex IT, telecommunications and data center infrastructures can be documented using a unified data model, allowing the creation of a digital twin that spans from physical elements to business services, regardless of the manufacturer.
Using this “digitized infrastructure”, companies can plan and manage their data center, as well as their IT and telecommunications environments, more easily, reduce incidents and execute changes more efficiently.
Workloads associated with AI can multiply the energy consumption of servers by five or ten
In addition, through a standardized set of tools and methods, it is possible to integrate information from other systems, generate advanced analyzes and optimize processes within the data center, as well as deploy new digital services in an automated manner. The software is also available in a SaaS model, ready for use in cloud environments and pre-configured for different scenarios, allowing rapid deployment in any data center.
In short, the adaptation of the data center to artificial intelligence is not only a technological challenge, but a strategic decision that directly impacts the efficiency, sustainability and growth capacity of organizations. Those companies that approach this data center transformation with a comprehensive vision and supported by advanced solutions will be better prepared to lead the next stage of digital transformation.
