As AI-powered applications move into production, the network has become a critical dependency, and a growing risk. At the same time, hybrid, multi-cloud, and containerized environments have made visibility more fragmented and harder to manage.
Traditional monitoring tools are no longer enough. Organizations are turning to network observability, enhanced by AI and emerging agentic architectures, to deliver the context, intelligence, and automation required to keep digital operations running.
This research explores how enterprises are responding—and where gaps still remain. The research highlights strong engagement from Security Operations, Cloud Operations, DevOps, and Platform Engineering, reinforcing observability as a shared foundation for cross-team collaboration. Many organizations now view network observability as a key pillar of broader NetSecOps initiatives,supporting faster incident response and improved security posture.
Download the report for a deeper dive into:
expect increased network observability
spending over the next two years
say AI is meeting or exceeding
expectations in observability use cases
say sharing observability data between
NetOps and SecOps is essential
Networking and observability are now viewed as mission-critical foundations for AI-driven operations.
More than half of organizations are already using agentic AI for network observability, with broader adoption
expected.
Network observability data is increasingly shared across security and operations teams to reduce risk and
improve response.
Most enterprises rely on three or more observability tools, driving integration and data challenges.
Download the report to understand how AI-and agentic AI in particular – is redefining what network observability must deliver.
This report is based on a quantitative survey of 385 networking professionals from midmarket and enterprise organizations across North America, spanning industries including financial services, manufacturing,technology, and retail.
