Operations | Monitoring | ITSM | DevOps | Cloud

Organizations are increasingly using agentic AI applications powered by large language models (LLMs) to automate analysis, decision-making, and operational workflows. As these AI agents take on more responsibility, they gain access to internal tools and services and can interact with them in unintended ways.

It’s 2026, and developers have more tools at their disposal than at any point in the industry’s history: CI/CD platforms are richer; observability stacks are deeper; security, data, and AI tooling have exploded into crowded, competitive ecosystems. And yet, delivery is still slow, incidents are still noisy, workflows are still brittle. The problem is no longer tool scarcity or feature depth. It’s integration debt.

Gartner predicts that AI agents will be implemented in 60% of all IT operations tools by 2028, up from fewer than 5% at the end of 2024. This acceleration has sparked an explosion of AI SRE solutions, from enterprise platforms to open-source alternatives, all promising faster root cause analysis and reduced MTTR.

The infrastructure management landscape is undergoing a fundamental transformation. Infrastructure as Code has already revolutionized how we provision and manage cloud resources by treating infrastructure as software. The next evolutionary step involves intelligent automation that can understand, adapt, and optimize these configurations independently.

ITIL 5 launched in January 2026, and for the first time in the framework's 40-year history, AI governance is front and center. If you're running incident management, on-call rotations, or building operational tooling, this matters: the gap between AI adoption and AI governance is about to become a compliance and operational risk issue. I’m not usually a big ITIL fan, but this guidance has some genuinely useful framing and questions.

For much of the past decade, many of the most ambitious ideas in artificial intelligence lived primarily in research papers, labs, and long-term roadmaps. Agentic AI was no exception. The concept of AI systems capable of reasoning, planning, and acting autonomously was widely discussed but largely theoretical. But earlier this month, Gartner released its report The Future of NetOps Is Agentic, reflecting a growing consensus that this has changed. What was once conceptual is now becoming operational.