Riverbed has embedded artificial intelligence (AI) agents into its observability portfolio as part of an effort to make it simpler to troubleshoot issues and incidents.

The Riverbed Network 360 AI agents are designed to invoke Riverbed IQ analytics using a Q AI chat interface embedded in the AppResponse and NetProfiler observability platforms.

Riverbed CTO Richard Tworek said, in effect, that AI agents are able to leverage AI skills embedded in those platforms to spin up dashboards in response to a natural language query. That on-demand capability makes it possible to more granularly troubleshoot incidents versus having to rely only on a set of static dashboards, he added.

However, AI agents will not eliminate the need for existing dashboards that provide a richer graphical method for observing IT environments, noted Tworek. Instead, IT teams will employ a mix of on-demand and static dashboards to more flexibly manage their IT environments, he said. The overall goal is to enable IT teams to more proactively identify and resolve issues long before there is an actual incident, said Tworek.

It’s not clear yet to what degree the rise of generative AI is transforming the way IT is managed, but the days of relying solely on static dashboards to monitor events are starting to rapidly fade away. In its place will be a set of AI technologies that make it possible for IT teams to launch natural language queries that surface issues affecting, for example, a specific router, noted Tworek. That capability enables IT teams, as a result, to more proactively investigate and resolve issues before there is an actual outage, he added.

In theory, those AI capabilities should significantly reduce the overall amount of stress the average IT team has historically experienced when trying to find the root cause of a specific issue. Less clear, however, is what impact those capabilities might have on IT staffing. On the one hand, the number of issues that were never previously addressed were significant, so there is no shortage of work to be done. The issue is that many organizations are still trying to justify a return on investment in AI that includes reductions in headcount, especially among specialists that might no longer be needed as it becomes simpler for the average IT administrator to resolve a wider range of issues.

There is, of course, at this juncture no going back, and many organizations have already discovered that after adopting AI they wind up rehiring IT personnel to essentially manage what can quickly become hundreds of agents that are performing a multitude of tasks asynchronously. At the same time, the overall size of the IT environment only increases as it becomes simpler to build and deploy a wider range of applications in the AI era.

No one can say with absolute certainty what the future may hold for the management of IT, but as AI continues to evolve roles within IT organizations will undoubtedly evolve in ways that are likely to go well beyond what many today might expect.