Presented by Cisco
AI agents are disrupting traditional IT operating models, adding complexity, data silos, and fragmented workflows. DJ Sampath, SVP of AI software and platforms at Cisco, believes AgenticOps is the solution: a new operational paradigm where humans and AI collaborate in real-time to create efficiencies, boost security, and allow innovative technology applications.
In a recent conversation with VentureBeat, Sampath explained why current enterprise IT management is fundamentally broken and what makes AgenticOps not only useful, but essential for IT operations going forward.
breaking point of traditional IT operations
The main problem plaguing enterprise IT today is fragmentation, Sampath said.
"Many times inside these enterprises, data is stored in many different silos," he explained. "For an operator to come in and start troubleshooting a problem, they have to go through many different dashboards, many different products, and that results in an increased amount of time to figure out what a problem is before they get to the root cause."
This challenge is about to intensify dramatically. As AI agents become ubiquitous within enterprises, complexity will increase exponentially.
"Each person will have at least 10 or more agents performing a variety of tasks on their behalf," Sampath said. "When you start to think about what the agents involved are actually doing, this problem becomes ten times, if not a hundred times, worse."
The three main principles of AgenticOps
To address these challenges, Cisco has developed its AgenticOps capabilities based on three fundamental design principles that Sampath believes must be true for this new operating model to be successful.
First, unified data access across silos. The platform must bring together disparate data sources: network data, security data, application data, and infrastructure data.
"It will be incredibly important to bring all of those things together so that the agents you are deploying to work on your behalf can seamlessly connect the dots across the board," Sampath said.
Second, multiplayer-first design. AgenticOps must be collaborative at the core, from the ground up, enabling IT operations, security operations, network operations teams – and agents – to work together seamlessly.
"When you bring the IT Ops person, the SecOps person, the NetOps person all together, you can troubleshoot and debug problems much faster than if you’re working in silos and copy-pasting things back and forth," he explained. "This is humans and agents working together in a synchronous environment."
Third, purpose-built AI models. While general-purpose AI models excel at broad tasks, specialized operations require models trained for specific domains.
"When you start to go into specialization, it becomes really important for these models to understand very specific things like network configuration or thread models that you care about and you need to be able to reason about," He said.
How Cisco operationalizes AgenticOps across the enterprise stack
Cisco’s approach combines telemetry, intelligence, and collaboration into one cohesive platform. Cisco AI Canvas is an operations workspace that replaces multiple dashboards with a generative UI and unified collaborative experience. Within the AI Canvas, operators can use natural language to delegate actions to agents while maintaining human-in-the-loop control – pulling telemetry, correlating signals, testing hypotheses, and executing changes.
The reasoning capabilities come from Cisco’s deep network model, trained on over 40 years of operational data, including CCIE expertise, production telemetry, Cisco’s Technical Assistance Center (TAC), and customer experience (CX) insights. This purpose-built model provides domain-specific intelligence that general-purpose models cannot match.
Cisco’s platform spans on-premises, branch, cloud, and edge environments, allowing agents to consume telemetry at machine speed across the entire ecosystem, including Meraki, ThousandEyes, and Splunk. With MCP Server implemented in Cisco products, agents get standardized access to tools and data without custom integration work.
How fragmented reporting data undermines IT troubleshooting
The traditional approach to IT troubleshooting involves raising tickets and piecing together fragmented information across multiple systems.
"People take screenshots. Sometimes it’s in post-it notes," Sampath said. "All this information lives in completely different channels, so it becomes really hard for someone to start collecting them together."
Cisco AI Canvas solves this by giving teams a shared, real-time workspace to work in – so the context isn’t scattered across chats, tickets, and screen shares. Teams can collaborate live, collaborate instantly, and contribute context (like screenshots and notes) along with agent-generated charts and graphs. But the real power emerges when AI agents engage in these collaborative sessions.
"Machines are constantly learning from these human-to-machine interactions," Sampath explained. "When you see that the same problem happens again, you are much faster to react because the machines can help you."
This creates a virtuous cycle of continuous improvement, where the agent asks if you want to continue using the same approach as last time, for example, and you’re able to delegate more work to the agent. And time spent debugging is compressed as the system learns and accelerates future responses.
Security as an AI Accelerator
Security has historically been considered a barrier to adoption and even innovation. But with the right guardrails, organizations can confidently deploy AI at scale, and even accelerate.
Employees have already experienced the productivity benefits of tools like ChatGPT and want similar capabilities in their enterprise environments. When organizations can trace personally identifiable information, prevent rapid injection attacks, and maintain proper data governance, they can unlock and unleash AI adoption inside the enterprise in a fundamentally different way.
The essential identity layer for cross-domain AgenticOps
Cross-domain data access presents one of the most complex challenges in AgenticOps implementation. Cisco’s strategic acquisitions, particularly Splunk, position the company to address this by unifying data across traditionally disconnected systems. But bringing data together is only half the battle, as who has access to which data becomes extremely important.
Cisco is evolving its Duo platform beyond multi-factor authentication to serve as a comprehensive identity provider, incorporating strong identity and access management from the beginning, not implemented as an afterthought.
"“We are investing in identity as a core pillar of how these agents will be able to pull data from different data sources while keeping the right authorization in mind,” explains Sampath. Should this agent have access to this type of data? Should you correlate these types of data together to be able to solve a problem?"
Humans are in the loop, but at a higher level
As AI agents become more autonomous, the role of humans will evolve rather than disappear.
"We will always keep humans in the loop," Sampath said. "What you are going to see is that there will be a lot of complexity involved in the tasks that are being performed."
Take coding, for example, which can be completely agentic today. The human role has shifted from manual coding, or even tab completion, to asking an agent to create code in bulk, and then verifying that it meets requirements before merging it into the codebase. This pattern will be repeated across all IT operations, with humans focusing on high-level decision making while agents handle execution. Importantly, rollback capabilities ensure that autonomous actions can also be reversed if needed.
Why is waiting for AI to ‘settle’ is the wrong move?
For CIOs and CTOs, the message is clear: Don’t wait.
"Many people are in this mode of wait and see," Sampath said. "They are waiting for the AI to settle down before making some of their decisions. And I think that’s the wrong way to think about it. Partnering with the right group of people, with the right group of vendors, will help you move forward much faster than just trying to be on the fence, figuring out what’s right and what’s wrong."
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