For 20 years, IT Operations teams have responded to the challenges of growing network complexity with point-in-time fixes: adding bandwidth for performance issues, deploying new firewalls for security gaps, and hiring more engineers to handle the growing number of tickets. Yet the fundamental problem remains unsolved.
This isn’t a temporary issue; it’s a degenerative condition we’ve allowed to worsen through every technological advancement from client-server to cloud-native architectures. According to Gartner, this persistent failure now costs enterprises over $500,000 per hour during major network outages, creating a cycle of mounting costs and operational fragility that can no longer be addressed by simply adding more resources.
The Endless Cycle
Manual operations have created an almost permanent state of rigid reactivity. Let’s look at the reasons:
- Teams are constantly reactive, fixing one problem after another over and over in a continual negative habit loop.
- Teams troubleshoot manually, chasing down err-disabled ports and misconfigured ACLs through a maze of CLIs.
- Teams execute changes manually, where a single typo can trigger a catastrophic chain reaction.
- Teams lack end-to-end visibility, making every incident a game of blindfolded chess.
The result? Sky-high MTTR, unsustainable business risk, and teams stuck in a loop of firefighting, unable to focus on strategy or prevention. The overall technology portfolio advanced, but the operator was left behind, transforming even the most experienced architect into a perpetual first responder.
Why Has the High MTTR Problem Not Been Solved Yet?
Network automation all too often operates in a context vacuum. Automation alone, without a complete picture of the hybrid network’s devices and intents, fails because it executes commands without understanding context, diagnoses without reasoning, and accelerates tasks without judgment—leaving the cognitive work of troubleshooting, correlation, and decision-making entirely manual. Network automation alone lacks diagnostic reasoning. It can reset an interface, but it cannot determine why the interface failed in the first place.
Similarly, the AI within Agentic NetOps alone fails because it reasons without business context, diagnoses without historical lessons learned, and optimizes without accountability—leaving the critical work of judgment, responsibility, and strategic alignment entirely human.
AI in networking remains a powerful tool—not a replacement. The answer isn’t choosing between human expertise and AI intelligence—it’s connecting them through shared context and clear intent. This powerful combination unlocks networks that are more than simply automated, but truly intelligent. Networks that don’t just follow commands but understand the unique designs and intent that drive its overall purpose. Networks that finally deliver on the promise of self-healing—guided by human intelligence, enabled by machine speed.
The Law of Modern NetOps: MTTR Halves, Every Year
This agentic model leads to a new, powerful expectation: In the age of AI and automation, enterprise network MTTR will halve every 12-18 months.
This isn’t aspirational, but a reality for our enterprise clients. One recent example showcases what’s possible when a team is unburdened by unpredictable outages and 1-2 hours of daily manual checks. Once they implemented an agentic approach, on top of NetBrain’s live digital twin. they embedded senior-engineer logic into AI-driven automations. The result?
- Accelerated MTTR through standardized, AI-assisted troubleshooting
- A shift from reactive monitoring to proactive prevention
The engineer’s role transformed from performing checks to governing them, from typing commands to approving intelligent recommendations.
Will Human-Led AI finally break the cycle of reactive firefighting? The solution isn’t more tools or more people. It’s a smarter partnership between human expertise and artificial intelligence. That’s the power of 20 years of innovation pioneering the future of Agentic NetOps and empowering network heroes.
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