AI Agents Don’t Open Tickets. They Fix The Problem

Cisco’s biggest announcement at Cisco Live was Cisco Cloud Control, a unified platform for managing networking, security, observability, and collaboration for both human administrators and AI agents.

Technology leaders are familiar with this scenario: a device cannot connect, the help desk opens a ticket, and troubleshooting begins. At Cisco Live, this scenario was addressed differently.

A technical engineer used Cisco Cloud Control to enter a natural-language prompt about a device not connecting to the network. The platform dispatched an agent that traversed multiple domains, identified a mismatched routing configuration, and provided a one-click remediation, removing manual navigation through each layer.

This example would have involved members from multiple teams and potentially hours of work to identify the root cause in the pre-agentic AI days. Now it can be resolved almost immediately.

Enterprises struggle with change management, and network topology documentation is often outdated. Using AI agents enables faster issue resolution and helps maintain accurate network documentation. This underpins Cisco's AgenticOps model, in which AI agents continuously manage infrastructure while engineers confirm changes rather than initiate them.

For CIOs, the greater challenge is cultural. The traditional IT mindset—where value is associated with expertise in the technical environment—must evolve. AI agents will outperform humans in detection, diagnosis, and remediation. The competitive advantage for technical staff now lies in the speed of validation and in sound judgment about when to override.

This shift requires a new approach. Prepare your teams accordingly.

Focus On Agent Orchestration

Salesforce’s Summer '26 release introduces Multi-Agent Orchestration in Agentforce. This capability enables several AI agents to collaborate seamlessly across both simple and complex workflows. Agents share context in real time, so even though multiple agents may be coordinating tasks behind the scenes, the customer only interacts with a single point of contact. This orchestration enables agents to collaborate on different steps of a process, hand off tasks smoothly, and ensure that information flows efficiently throughout the workflow.

This goes beyond automation—automation replaces a task, while orchestration replaces a process by coordinating multiple agents that share context, escalate intelligently, and collaborate seamlessly without losing the thread. In this model, CIOs shift from deploying solutions to orchestrating new workforce layers, ensuring that data infrastructure, governance, and change management can scale with Multi-Agent Orchestration technology.

No Agent Runs Without A Security Foundation

Salesforce and Cisco understand that trusted security is a requirement.

Cisco announced an expanded set of agentic security offerings: AI Defense, Zero Trust for agents, and an Agentic SOC,alongside its acquisition of Astrix Security, which focuses on securing non-human identities and AI agents. As agents multiply, each becomes a potential identity, increasing the possible attack surface. Cisco also announced Live Protect, a runtime defense integrated directly into its infrastructure. No maintenance windows or patch cycle delays—protection activates and adapts in real time as threats emerge. Security for agentic AI must be embedded within the infrastructure.

For CIOs, the pattern here is consistent with what we are seeing across the vendor landscape. Security is no longer a layer you add at the end of a deployment. It is the cost of entry for operating any agentic AI. If an agentic AI agent makes a mistake and a breach occurs, it is still a breach for the organization.

Taken together, these themes signal that the agentic enterprise is not a future vision but the current reality every CIO must navigate. Decisions about infrastructure, orchestration, and security are now, not later.