Building trust starts with governed execution
When NetBrain polled network teams at a recent webinar on what keeps them from trusting AI agents on their network, about 75% stated it comes down to either: they can’t see the AI’s reasoning, or the guardrails aren’t there.
That’s a fair bar for any agentic platform to clear before it touches production. You should be able to set what each agent can access, read the evidence behind every conclusion, and find every action in an audit trail. In NetBrain, those controls live in Agent Studio. Every agent shows its plan and evidence, and every change is tagged in the audit trail.
There are guardrails built in, too. The Change Agent can’t push a change on its own – an engineer must approve it and hit execute, which is a feature that can’t be turned off. Agents can only reason about the parts of your network NetBrain can see, so coverage matters. Since AI usage isn’t free, the new Adoption and Usage Dashboard shows AI Usage and Cost through prompts, sessions, users, and token spend alongside the value you get.
What Agentic NetOps looks like in action
Take a recent case study where a payment application started failing. The Diagnosis Agent traced the live path and found a policy denying the traffic in under two minutes. One click handed that root cause to the Change Agent, which wrote the remediation runbook with pre- and post-change checks.
Before a risky change reaches your change advisory board (CAB), the Change Agent can run a what-if analysis against live configs, paths, and neighbors, then give you a go or no-go with the evidence. In a lab rebuild of the 2021 Akamai outage, it flagged a BGP prefix limit set below what the peer was already sending.
With a CVE plug-in, the agents can also show you which devices at a site are exposed and which application paths run through them. Each of these examples is the kind of work Forrester measured when it put a dollar figure on network operations.
Where Forrester found the payoff, and you can, too
NetBrain commissioned Forrester Consulting to run a Total Economic Impact™ study, and Forrester interviewed five customers. Forrester combined their answers into one hypothetical company. The composite organization saw a 241% ROI over three years.
For a business use case, the more useful finding is where that return came from. Nearly 70% of the quantified benefits came from shortening significant outages – which was more than troubleshooting time, change automation, and team productivity combined.
That tells you where to point the agents first: the incidents that cost your business the most. Forrester’s model also assumes the value builds over three years as automation and shared knowledge accumulate, which is the part your team controls.
How to build the Agentic NetOps case for your organization
The Forrester study works best as a template, and its outage model runs on numbers you already track:
- Your downtime baseline, which is how many significant outages you have a year and how long each one lasts.
- Your savings, by applying the study’s 70% reduction in downtime to the share of the business each outage touches.
- Your dollar figure, which comes from multiplying those hours by revenue per hour and operating margin.
Forrester spread revenue across every hour of the year, which lowers the hourly rate, then trimmed 20% for risk. Do the same, and you’ll have a stronger internal argument.
Forrester’s Andre Kindness estimates that, “about 80% of deploying a platform like this is gathering what your team knows.” So start with one workflow you can measure before and after.
For information on how much value you’re getting out of your current setup, use this calculator to see what Agentic NetOps could return for your network.
