While artificial intelligence has reshaped industries, its impact on IT operations is especially pressing. Leaders now face rising complexity across tools and infrastructure while strategizing how to deliver outcomes. AgentOps, a new paradigm, aims to reduce friction, automate decision-making, and embed intelligence into operations.

Beyond a technical upgrade, AgentOps represents the reimagining of IT operations in an era of intelligent autonomy, according to Shailesh Manjrekar (left), chief AI and marketing officer of Fabrix.ai Inc.

“You’re dealing with time-sensitive data, you’re dealing with alerts, you’re dealing with incidents,” he said. “Many of the off-the-shelf agentic frameworks don’t apply to this kind of paradigm. The platform we have is actually built ground up to cater to operational use cases. And what AgentOps … also [being] known as AgenticOps means is really how you operationalize the entire agentic stack from getting to a prompt all the way to looking at the MCP tools, getting to the proper guardrails, experimenting and then eventually getting to the lifecycle management of these agents.”

Manjrekar, alongside Rached Blili (middle), distinguished engineer – office of the chief technology officer at Fabrix.ai, and Zeus Kerravala (right), founder and principal analyst at ZK Research, spoke with theCUBE’s Bob Laliberte at The Networking for AI Summit event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how the embedding of AI agents into the core of networking and operations creates a shift from reactive firefighting to proactive, autonomous IT — directly driving business outcomes. (* Disclosure below.)

The paradigm shift from AIOps to AgentOps

AI in operations isn’t new. Early AIOps platforms provided dashboards, correlations and recommendations — but left the “last mile” of action to human operators. That gap created bottlenecks because outcomes still depended on manual expertise, according to Manjrekar. AgentOps changes that equation. By embedding large language models into the decision-making process, enterprises can move from reactive monitoring to proactive, predictive and eventually autonomous operations.

“The second issue is, of course, the proliferation of the agentic applications,” Manjrekar said. “Now, you are dealing with agents and LLMs and shadow AI in addition to shadow IT, and how do you manage all of that? That is what we see as the promise of AgenticOps. You now have agents and agentic workflows being able to cater to those use cases.”

Networking remains the nervous system of modern enterprises — and increasingly, of AI itself, according to Blili. Yet, networks are growing more complex, spanning data centers, cloud, wireless, mobility and telco domains. Agentic AI is uniquely suited to this challenge because of its ability to reason, deliberate and break down problems into solvable tasks.

“In the areas of networking, that’s particularly important because some of the things that you’re trying to automate and improve require enormous amounts of data and understanding of relationships between entities,” Blili said. “Networking is all about understanding relationships, topologies and dependency flows. How are you going to leverage agents and agentic operations across an entire infrastructure? That requires some very careful tooling … and capabilities, so that when you present the agent with a high-level problem, they can help you solve it.”

The demand for AI-driven operations is clear. Recent findings show that 83% of organizations would switch vendors if offered better AI capabilities — a striking departure from past loyalty trends, according to Kerravala. Enterprises under pressure to “do more with less” see AI as a multiplier for their workforce, enabling them to reassign human engineers to more strategic tasks while agents handle operational load.

“In emerging markets, the highest [customer loyalty] number I ever saw was SD-WAN at 30%,” Kerravala said. “To have a number that high just shows the demand today for AI ops and AgentOps and how much customers are looking forward to it helping them with their operational issues.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of The Networking for AI Summit event:

(* Disclosure: TheCUBE is a paid media partner for The Networking for AI Summit event. Neither Fabrix.ai Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE