Cisco Live 2026 Signals the Shift from AI Experimentation to Agentic Operations
At Cisco Live 2026, one theme stood above all others: AI is moving beyond experimentation and productivity assistance into operational deployment. In a conversation with Jeff Schultz, Senior Vice President of Portfolio Strategy at Cisco, it became clear that Cisco views the industry as entering the next phase of AI adoption, one driven by autonomous agents, distributed intelligence, and increasingly complex infrastructure requirements. See full video below
From Chatbots to Agents
Much of the industry’s early AI focus centered on chatbots and human-driven interactions. According to Schultz, the transition to agentic AI fundamentally changes the infrastructure equation.
“We are moving into this agentic era, and agents are very, very different from chatbots,” Schultz explained. Unlike chatbots, which generate intermittent workloads, agents operate continuously, collaborating with other agents and executing tasks autonomously.
Cisco cited data indicating that agentic workflows can generate up to 450% more network traffic than equivalent human-driven processes. As Schultz noted, “Humans click, agents swarm.” The result is a significant increase in both the volume and distribution of AI-driven traffic across enterprise environments.
This shift elevates the network from a connectivity layer to a strategic enabler of AI outcomes.
Cisco Cloud Control: A Foundation for Agentic Operations
One of Cisco’s most significant announcements at the event was Cisco Cloud Control. While the platform unifies management across Cisco’s portfolio, its broader significance lies in its role as an operational framework for agentic environments.
Schultz repeatedly emphasized the importance of what he described as a “harness” for AI adoption. “Have a harness,” he advised. “Security is built in, observability is built in, and you as an enterprise or builder don’t have to think about adding it.” For Cisco, that harness is their agentic operations platform, Cloud Control.
That’s why Jeff repeatedly came back to the idea that enterprises shouldn’t have to remember to add security or observability later. The harness provides those capabilities by default.
Cisco Cloud Control brings together the management, security, and observability domains, enabling organizations to monitor agent behavior, manage costs, and maintain governance as AI-driven operations scale. The approach reflects a growing industry reality: enterprises need more than AI models; they need operational platforms capable of safely and efficiently deploying and governing autonomous systems.
Business Transformation Beyond Productivity
Schultz also sees AI as a broader opportunity for organizations. “What I am most excited about when it comes to AI is tackling those audacious tasks on your to-do list that you just wouldn’t even go to,” he said. Rather than simply accelerating existing processes, AI creates opportunities to address challenges that were previously impractical due to resource constraints, complexity, or time limitations.
This distinction is important to note. While productivity improvements deliver incremental value, business transformation occurs when AI enables entirely new workflows, operational models, and business outcomes.
A New Class of Builders
Another trend highlighted during the discussion is the democratization of development. AI-assisted tools are lowering barriers to innovation and creating a new generation of builders across the enterprise.
Schultz believes this shift extends well beyond traditional development teams. Employees with limited technical backgrounds can increasingly build solutions tailored to their own business needs, accelerating innovation across departments and industries.
Organizations that successfully leverage these capabilities may gain an advantage not because they employ more developers, but because they empower more employees to innovate.
Why Networking for AI Matters
One of the most compelling aspects of the discussion centered on the growing importance of “networking for AI.” As agentic workloads become pervasive, network architectures must evolve to support new traffic patterns.
Historically, enterprise networks were optimized primarily for downloads. Agentic AI changes that equation. Agents frequently communicate with cloud-based models and services, generating substantial upstream traffic while increasing demands on latency, resiliency, and security.
As Schultz observed, “We have to be thinking about the upload, because as an agent sitting at a desk needs to interpret a skill, it’s going to an LLM that may sit in a cloud.”
For enterprise leaders, this reinforces a key point: AI success will depend not only on models and applications but also on the readiness of the underlying infrastructure.
The Bottom Line
Cisco Live 2026 demonstrated that the industry conversation is rapidly shifting from AI experimentation to operational deployment. As organizations embrace agentic AI, they will face new challenges around scale, governance, security, observability, and network performance.
Cisco’s approach. centered on Cisco Cloud Control, integrated operations, and AI-enabled infrastructure. positions the company to play a broader role in helping enterprises navigate this transition. Whether organizations are pursuing productivity gains or broader business transformation, the message from Cisco Live resonated with attendees: agentic AI is reshaping enterprise requirements, and the network will be foundational to its success.
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