Modernizing Your Data Center Will Prepare You for the Next Phase of AI

Artificial intelligence (AI) may be in its early stages of maturity, but one thing is clear: high-performing organizations who have chosen to invest in it are pulling away from the rest of the pack.

Organizations attributing at least 20% of their profitability to AI use it to create new products, optimize development and expand revenue streams.

AI has offered significant business value, but it has also changed how you should manage data. AI-driven analyses and insights require a considerable amount of data. Organizations must look beyond the old adage of “sizing for five years.” This data sprawl will demand scalable storage, robust security, strong governance and careful planning.

It will also require organizations to completely rethink data center strategy. The ability to power and cool the data center is about to be disrupted drastically by the AI workloads coming on-premises.

While most organizations have managed increasing power and cooling needs in their data centers, AI will force you to completely rethink these aspects

AI is about to change how you approach the data center. If you don’t begin modernizing your infrastructure into something more energy efficient and compact, you won’t be able to bring in an AI engine because you’ve already maxed out your infrastructure.

Your team must ask:

• Can our data center handle power and cooling for an AI engine right now?
• What will the incorporation of an AI engine mean for our business strategy?
• What data will we need to bring back on-premises so we can properly use an AI engine?
• Can we handle housing that data on-premises or will we need to refresh our storage infrastructure?
• Will we need to rearchitect our data center floor?

What we’re seeing with several organizations is that AI hasn’t affected the normal IT budget just yet. For most of these businesses, it’s the line of business justifying a particular AI application or use-case and securing investment from the board directly.

AI will find its way into the IT budget, and when it does, you’ll have to ask yourself: do we modernize or do we focus on AI?

It’s a delicate dance because the answer is that you’ll have to do both. You don’t really have a choice. If you don’t modernize your infrastructure to create cleaner, more useable data, then all of a sudden, you’ve just made your AI engine worthless because the data isn’t there to support it.

Thankfully, infrastructure modernization and AI don’t have to share a contentious relationship. Many actions you’ll take to modernize — such as upgrading to a lower latency network, refreshing your storage architecture, and upgrading your power and cooling capabilities — will ultimately benefit your organization as a whole.

As you make room for AI engines on the data center floor — bringing back your data from the cloud to effectively run those engines — you’ll be looking to free up space elsewhere.

Reevaluate your workloads by asking:

• What workloads can we move up into the cloud?
• Are there other Software as a Service (SaaS) applications we should look at?
• Should we move our workloads from VMWare onto a Kubernetes container or something like Amazon EC2? 

Organizations will likely need to shift more enterprise applications to the cloud to free up floor space and power and cooling for AI workloads. It may pose an interesting dilemma for businesses. If those systems are currently generating a lot of your data currently and they’ve moved to the cloud, you will have an egress of data coming back to your data center and the fees associated with that.

You can’t afford not to modernize. Your data center infrastructure is what’s driving the data into your AI engine.

At the same time, it’s important to recognize that the investment required to make this engine work will be significant. You’re restricted to what’s within your budget. A sound strategy is crucial to ensuring your modernization efforts are a success.

We’ve observed that many organizations are not considering the full picture, and that’s because the AI conversations aren’t happening in the data center. They’re happening at the lines of business.

IT departments and their budget don’t line up with what the lines of business want from AI because the left hand doesn’t know what the right is doing.

Someone will need to raise the red flag and point out the amount of work that needs to be done in the data center before purchasing an AI engine.

The industry is still in the proof of concept phase with AI. This means your organization still has a small window of time — about two years — to prepare your data center.

You need a partner who can help you develop a forward-thinking strategy that takes into account your unique growth opportunities and challenges. Our hybrid infrastructure experts have experience designing world-class programs and orchestrating new technology for our customers.

Done correctly, infrastructure modernization will streamline processes, automate tasks, optimize resources and integrate legacy architecture. You can create a data center that will support your current and future goals, and be ready for the next phase of AI.