Is your data center AI-ready? Ask these five questions.
julio 23, 2026 / Unisys Corporation
Short on time? Read the key takeaways
- Before investing in AI, your data center needs to be ready for it. Start by considering your infrastructure.
- You need sufficient power and comprehensive security so your efforts don’t stall and your data remains protected.
- Another important question is where you stand on costs. Some organizations require consistency in spending, while others are more adaptable.
- Your future plans direct the action your organization takes for a smoother path forward.
Eagerness to implement AI initiatives is a start. But then come the practicalities: is your data center truly ready to support the full potential of AI?
Infrastructure limitations, data challenges, operational complexity, and security concerns could become barriers to scaling AI. Before investing in new AI models and applications, IT leaders should assess whether their data center and operating environment are ready
Asking five questions can identify areas of your data center that need attention or improvement to support your AI ambitions.
Do you have the necessary infrastructure?
Your infrastructure lays the foundation for technology innovation, and it's as important as a house’s foundation. AI workloads require an environment made for agility, scalability, and seamless integration, and capable of handling AI’s intense data flows. Without the proper infrastructure, even the most advanced AI capabilities can sit idle, unable to deliver on their promise.
AI’s power hinges on robust, scalable hardware, and your data center must support the unique compute, storage, and network demands AI workloads require. That means considering the performance and capabilities of all your systems and hardware, including your servers, storage, networking, and cooling. For best results, make sure your systems are integrated end-to-end.
Manual processes often become bottlenecks for AI initiatives. Automation and intelligent operations can accelerate deployment of infrastructure resources, improve efficiency, and reduce operational complexity.
Does your data center have sufficient power?
Implementing AI initiatives requires attention to your organization’s GPU power density. Legacy racks built for 5 kilowatts can't support the 20-kilowatt demands of modern AI infrastructure. Without enough power, your AI ambitions risk stalling before they start. To gain a holistic view of your data center’s AI-readiness, consider:
- The amount of power your current setup can reliably supply
- The ability of cooling systems to efficiently manage the extra heat
- Whether these elements can work harmoniously to sustain continuous, intensive AI processes.
Your data center requires a careful reassessment of power capacity and cooling infrastructure to support the heavy lifting AI workloads bring.
Is your cybersecurity comprehensive?
AI often handles sensitive customer information and proprietary corporate data, and your data center cybersecurity must be strong enough to protect it. A multi-layered security approach featuring physical safeguards, robust network defenses, and strict access controls can keep your intellectual property secure and your AI innovations safe.
Organizations also should consider regulatory compliance requirements for AI usage and risks like unauthorized access to data, model manipulation, and data leakage. Comprehensive security strategy protects infrastructure and the AI ecosystem it supports.
How much do you value cost consistency?
Maintaining consistent costs each year is a business strategy for some businesses, with predictable budgeting allowing them to plan confidently without surprises derailing progress. They appreciate the control and visibility into data center controls, especially given the possibility of shifting cloud pricing.
In contrast, other organizations have the capacity to embrace variable investments and prefer to roll with shifts to seize new opportunities.
Understanding your company’s tolerance and aligning your data center strategy accordingly gives you an advantage as you ready your data center for increased AI use. Applying FInOps principles can help balance innovation with cost control as AI adoption scales.
Have you planned for future growth?
The “perfect house” changes over the years because of job and commuting shifts, new additions to the family, children leaving for college, downsizing, and aging. In the same way, data center demands change over time. Especially because AI isn’t static. Workload demands grow, sometimes exponentially.
You need the ability to easily scale your data center to handle new workloads and AI initiatives. From scaling processing power and storage to expanding network capacity and cooling systems, flexibility is key. Whether your AI footprint expands organically or through strategic moves like acquisitions, your data center will adapt swiftly and seamlessly if you design infrastructure with built-in agility.
Ensure your data center is AI ready
Increasing your data center’s reliability, resilience, and issue-resolution speed can optimize performance. Unisys helps organizations build AI-ready environments through infrastructure modernization, hybrid cloud management, AIOps, cybersecurity field services, and service desk support.
