Everywhere I go, I hear CIOs and DevOps leaders all asking the same question:
“Are we ready for AI?”
(Come to think of it, pretty much every executive in any division is asking that question.)
After talking to hundreds of cloud teams over the past year, I had a strong hunch about the answer.But I wanted numbers. So, ControlMonkey surveyed 300 cloud and infra leaders across industries,
and the results are clear:
Most teams aren’t ready for the coming AI surge… at all.
The AI Wave Is Bigger Than Even Cloud Leaders Realize
Workloads aren’t just growing, they’re exploding. Teams expect a 50% increase in AI-driven workloads in the next 12–24 months, with almost 40% predicting exponential growth.
Think about what that means: substantially more clusters, pipelines, policies…and more risk. Because AI doesn’t just add scale. It accelerates the pace of change, magnifying every weakness in your infrastructure.
So if your cloud infra or team is already stretched thin, AI could very well break you.
The Numbers Confirm It
According to our latest report:
- Only 46% say they’re fully prepared to automate at AI scale.
- Average IaC coverage? 51%. That means fully half of infra is still manual.
- 98% admit they face blockers to scaling and resilience
- 1 in 4 (27%) already see costs rising due to AI
Even “ready” orgs have holes. Performance, cost, compliance, skills…
every gap surveyed hit at least a third of companies. Point is: there’s no such thing as “safe.”
Infra Will Decide Who Wins AI
AI will expose infra maturity more brutally than anything before it. The companies that thrive won’t only be the ones with the biggest AI labs or the best data scientists. They’ll be the ones whose cloud teams can:
- Reconcile infra continuously, no drift, no blind spots.
- Automate everything: provisioning, scaling, rollback, compliance.
- Give developers speed and keep the business secure.
These arent’ nice-to-haves. They are critical.Because here’s the truth: If infra lags, AI fails.
What’s Really Blocking Scale
The biggest barriers cloud leaders name aren’t GPUs or budgets. They’re the basics: security, governance, and visibility. Nearly every team (98%) admits they’re hitting blockers to both scale and resilience. AI only amplifies them. If you don’t have automated compliance checks, real-time drift detection, and policy-driven scaling, you’re building on sand. Until those gaps close, total automation isn’t optional—it’s survival.
What Cloud Leaders Say They Need Most
When asked what would actually move the needle, cloud leaders were clear: more training (23%) and better visibility into infra and AI workloads (22%). In other words—skills and sightlines. The fix isn’t a magic platform; it’s frameworks, playbooks, and automated provisioning that make readiness real. The clock’s ticking—those gaps won’t close themselves.
What Needs to Change Right Now
If you’re a CIO or CTO facing down the incoming AI wave, the takeaway isn’t “buy more GPUs.” It’s:
- Expand IaC coverage until manual infra is gone.
- Put guardrails in place so console changes can’t bypass policy.
- Invest in skills and visibility, not just cost cutting.
- Free your DevOps teams from firefighting so they can build-less manual approvals and automating repetitive tasks.
Bottom line: AI is coming whether you’re ready or not. The difference between scaling and drowning is what you do with your infra. And these numbers prove it.
The wave is here. The question is: will your infra ride it, or break under it?
Author
