Even with CI/CD pipelines and IaC, deployments still stall at key handoffs.
Teams have never had more automation in their toolkit. CI/CD pipelines run on every commit. Infrastructure-as-Code spins up environments in seconds.
You’re promised instant delivery.
But actual deployments still stall.
Our AI + DevOps Report shows the disconnect. Only 29% of teams say they can deploy on demand. Yet 42% report lead times to change takes longer than a week.
In other words, many “modern” setups look fast on paper, but still feel slow in practice. And speed is a top priority when it comes to DevOps , if you look at the top two performance indicators below.
Where the Delays Creep In
Automation handles the mechanics, but people and processes block the flow:
- Approvals: Nearly half of teams (47%) cite manual approvals as a major bottleneck. Security and compliance gates are still built for a ticket-driven world.
- Context switching: Engineers waste time jumping between dashboards, logs, and tickets. Three in five respondents said fragmented tools increase time-to-resolution.
- Siloed troubleshooting: Each system shows only part of the picture, leaving teams to stitch together root cause manually. 31% said troubleshooting delays are a top source of deployment lag.
The result: Pipelines that technically run in minutes with changes that take days to hit production.
Why AI Agents Matter
Speed isn’t just about pipelines. It’s about collapsing the gaps between them.
AI agents can watch across the entire stack, interpret issues, and recommend or even trigger safe fixes.
Instead of waiting on a long approval chain, an AI-powered help desk can enforce policies in real time.
Instead of passing tickets across silos, agents can connect logs, configs, and code to surface the root cause.
The result is fewer blockers, faster deployments, and shorter lead times to change.
Fast in Theory vs. Fast in Reality
Too many DevOps setups look fast in theory. They boast automated pipelines, cloud-native tools, and modern practices. But our report makes one thing clear: nearly 40% of teams admit their lead time to change has barely improved in the last two years.
The real test of speed isn’t how quickly a pipeline executes. It’s how quickly a team can move from commit to production with confidence.
That’s why integrated, AI-powered platforms like DuploCloud are gaining traction.
We don’t just automate the pipeline, but we also remove the friction around it.
Why it Matters
Automation alone doesn’t guarantee speed. The future of DevOps will belong to teams that pair pipelines with AI teammates.
These are your agents that collapse handoffs, streamline troubleshooting, and enforce policy automatically.
See the full findings in our AI + DevOps Report. 135+ engineers, platform leads, and CTOs share what really slows deployments and how they’re rethinking what “fast” means.
