Key findings:
1. AI is changing what observability must deliver
The research shows that AI is already widely used in network observability, with organizations applying it to performance optimization, security threat identification, and operational efficiency. Expectations are high, and in most cases, AI is delivering measurable value.
Agentic AI, while still emerging, is gaining real traction. More than half of organizations report active use today, with broader adoption expected as teams look to simplify integrations, close skills gaps, and move toward more autonomous operations.
2. Observability is driving cross-team convergence
Network observability data is no longer confined to networking teams. The research highlights increasing collaboration between NetOps and SecOps, with observability insights shared to reduce risk, improve response times, and support coordinated decision-making.
This convergence reflects a broader shift toward integrated operational models, where networking, security, and cloud teams rely on shared visibility to manage complex environments.
3. Complexity remains the biggest barrier
Despite increased investment, most enterprises still rely on three or more network observability tools. Tool sprawl, data fragmentation, and integration challenges continue to limit the effectiveness of observability initiatives.
The research makes clear that success depends not just on collecting more data, but on correlating it effectively and delivering insights teams can act on.
Chart 1: Level of agreement with statements related to network environments.
As AI technologies move into broader adoption and deployment, nearly everyone agrees that networking is becoming more critical. Download report to read more.
Chart 2: Status of AI technologies within or in conjunction with network observability.
Network observability vendors have been working feverishly to add AI technologies into their products, while those using open source or building their own tools have increasingly ready access to AI componentry. Download report to read more.
What this means
The findings point to a future where network observability must:
- Provide comprehensive visibility across cloud, WAN, data center, and container environments
- Support AI-driven analysis and automation without increasing operational burden
- Enable collaboration across networking, security, and cloud teams
- Scale as AI workloads and digital dependencies grow
Organizations that treat observability as a foundational capability, rather than a set of disconnected tools, will be better positioned to support AI-driven operations.
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