Over the past 18 months, AI has been improving at a breakneck pace, and businesses globally are itching to take advantage of the most transformational new technology in decades. But, the harsh reality is that not all businesses are running on modern cloud infrastructure. Critically, their data estate requires significant evolution to even begin taking advantage of AI. They’re starting the race from the parking lot.

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before.

But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck. They're encumbered by legacy, and the internal friction around moving to public cloud is real. Security concerns, compliance questions, technical debt, cost control anxiety — these aren't trivial objections. They're legitimate concerns that slow everything down while the opportunity cost keeps growing.

What's Actually Holding Companies Back

The Flexera 2025 State of the Cloud Report nails the two biggest blockers: 77% of organizations cite security as a top cloud challenge, and 84% struggle with cost control. These aren't just survey numbers — they're the reasons why cloud initiatives stall in committee meetings and budget reviews.

If you're a CTO or infrastructure leader, you're being asked to move faster on AI while simultaneously being told to lock down security and control costs. That's a tough position. And when you're dealing with legacy systems that have been running business-critical workloads for years, the risk of a botched migration feels very real.

The problem is that waiting doesn't make it easier. Technical debt compounds. The gap between what your business needs and what your infrastructure can deliver just keeps widening. And critically, you're missing the window to build AI capabilities while your competitors are already experimenting and learning.

AI as the Accelerator

Here's some good news: the same AI technology creating urgency can also help solve the migration challenge. Business Insider recently covered how organizations are using AI tools to actually accelerate and de-risk migrations — mapping dependencies, estimating costs, identifying risks, and automating steps that used to require weeks of manual analysis.

This matters because it addresses both sides of the equation. You can move faster (which you need to do to unlock AI capabilities) while also reducing risk (which addresses those security and governance concerns that are keeping stakeholders up at night). AI-assisted migrations can catch configuration issues, predict cost impacts, and identify security gaps before they become problems.

But — and this is important — tools alone don't solve organizational readiness issues. You still need clear objectives, cross-functional alignment, and a realistic understanding of what you're trying to achieve. The migrations that fail usually fail because of people and process issues, not technology.

Migration Is Just Step One

The other thing I want to emphasize: getting to the cloud isn't the finish line. It's the starting line.

I see companies treat cloud migration like a project with a beginning, middle, and end. They move workloads, declare victory, and move on. Then six months later, they're shocked by their cloud bill or discovering that they're not actually more agile than before.

Cloud requires continuous optimization. You need ongoing governance, regular cost reviews, performance tuning, security monitoring, and constant alignment with best practices. The cloud providers are releasing new services and capabilities constantly. The companies that win are the ones that treat cloud as a continuous practice, not a one-time project.

This is where working with an expert partner can make a huge difference, especially if your organization is in the middle of this internal shift to public cloud. A good partner doesn't just help you migrate — they help you operationalize cloud management so you're constantly optimizing, governing, and evolving your cloud estate as your business needs change.

The Bottom Line

If your organization isn't fully committed to public cloud yet, I understand the hesitancy. But AI isn't waiting for anyone. Companies that can iterate quickly on AI capabilities are going to have a significant advantage, and that requires modern cloud infrastructure.

The question isn't whether to migrate. It's whether you have the right strategy, the right approach to risk management, and the right support to do it well. Because done wrong, cloud migration is expensive and disruptive. Done right, it's the foundation for everything you're going to need to build over the next decade.

The companies that move with discipline and a clear-eyed focus on continuous improvement will be positioned to capitalize on AI and whatever comes next. The ones that keep waiting are not reducing risk — they're accumulating it.