AIOps is moving beyond monitoring and alert management toward more automated IT operations. Recent industry developments are increasingly focused on using AI to help identify issues, support incident response, and eventually take action within IT environments.

But does adopting AIOps mean an organization needs to transform its entire IT operations model at once?

A more practical approach may be to start with one clearly defined operational problem, such as:

• Reducing alert noise

• Improving incident prioritization

• Identifying recurring infrastructure issues

• Predicting capacity problems

• Automating specific repetitive operational tasks

Starting small can make it easier to measure whether AIOps is actually improving operations before expanding it across a wider environment. Ciena's recent guidance similarly recommends beginning with a focused use case that can demonstrate measurable value and build confidence for broader adoption.

At the same time, organizations need to consider whether their existing monitoring data, integrations, processes, and governance are mature enough to support AIOps effectively.

What is the better approach for enterprise IT teams today: start with one high value AIOps use case, or build a broader AIOps strategy from the beginning?