For organizations, your cloud maturity is tied to your AI maturity

You’re a busy person, so let’s get straight to the point. If you come away with nothing else from this article, remember this: big AI projects rely on high cloud maturity. 

(Of course, I can’t just leave it at that. You want to know the reason, and see proper evidence and statistics. That’s why this article won’t end at 32 words.)

That said, being in a busy rush—and not asking enough questions—is very emblematic of the current state of AI adoption. According to IBM research, 64% of CEOs say their fear of falling behind drove AI investment before actually understanding the value it offered.

Fast and frantic adoption, followed by predictable failure. 

There’s a very famous statistic from MIT that only 5% of AI pilots move into production with measurable value. And while there’s a lot of forces at play here—like poor governance and unclear ownership—lack of cloud maturity in your organization is sure to make your AI ambitions dead on arrival.

AI pilots are often designed to succeed, but not at scale

AI agents can be deployed in various environments, and there are many cases where you don’t want to use public cloud providers like AWS, Azure, or GCP for this. Here are some examples:

• Lightweight operations and models: You might be running a single AI agent, and having that running with autoscalers, load balancers, and all the other bells and whistles is just burning your money. That’s overengineering, and one of the ten cloud anti-patterns you should rightly avoid.

• Internal agents: Running AI locally offers increased privacy and latency, which might be important for the problem you’re trying to solve.

• AI R&D: Your teams just want to test things out locally to keep dev costs down. Iteration is faster locally because you’re not waiting on things like cloud cold starts.

For your customer-facing AI solutions, the demands and expectations are significantly greater. They typically need to do the following:

• Scale with unpredictable spikes in user demand (or scale down appropriately)

• Offer high availability to avoid service interruptions

• Run in a compliant, consistent way for the entire AI lifecycle

• Not chew up staff time with ongoing, hands-on maintenance

• Run on the right high-performance hardware that is kept up to date

This is why successful enterprise AI pilots typically run on cloud foundations, because this is the value proposition that cloud offers. In fact, executive leaders are increasingly realizing that cloud and AI success are linked. 

According to a recent NTT Data study:

• 61% of CAIOs and 50% of CIO/CTOs say the rise of AI and agentic AI has enhanced their need for investment in the cloud

• Nearly 9 in 10 orgs (88%) say their current cloud investment levels put cloud native, AI, and modernization initiatives at risk

• 99% say the rise of AI, including agentic AI, has increased their need for cloud investment 

All of this focus on increased cloud maturity is great! However, there’s a catch…

Few companies use cloud correctly to capture regular ROI, let alone AI ROI

According to Forrester research, only 8% of organizations qualify as highly cloud mature. The rest fail to leverage techniques that provide cloud value like automation, autoscaling, managed services, and more. 

It’s not that the cloud doesn’t offer clear value, rather that it’s elusive. Of those organizations that achieve high cloud maturity, 86% achieve their overall business goals.

In short, this means most organizations are rushing to increase their investment in an area they’re not currently mature enough to deliver ROI with. Building your AI solutions in the public cloud when you’re not even extracting regular value from it is like trying to run before learning to walk.

Conclusion: Before you tackle AI, think about cloud maturity

When it comes to getting a return on your AI and cloud investments, it all comes down to people—giving them the knowledge to properly create the right processes and lay the proper foundation to deliver on AI projects. As a leader, you can enable this by upskilling your workforce appropriately.

Building your cloud and AI maturity doesn’t need to be hard

Raising your organization’s cloud maturity can sound like an overwhelming, insurmountable task, but it doesn’t need to be. Give your teams immediate access to a vetted, hands-on cloud and AI curriculum that fits their workday, building the skills needed for optimization and an AI-first future.

Pluralsight Cloud Ready is an end-to-end program combining courses, skill assessments, and best-in-class learning experiences that empowers teams to: 

• Hit deadlines. Accelerate cloud migrations and modernizations with structured, self-paced learning and real-world practice.

• Unlock cloud ROI. Achieve real value on your cloud investments with best-practice architecture, better cost management, and tighter business alignment.

• Modernize infrastructure. Build AI- and cloud-native platforms that perform more efficiently and unlock valuable data for AI.

Cloud Ready gives you a clear path to assess your organization, upskill efficiently, and evolve your team to meet your business goals. Learn more about Pluralsight Cloud Ready.