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Cisco unveils new AgenticOps innovations to simplify and scale AI-driven IT operations

by CXO Staff
February 24, 2026
in Future, News, Tech

New AgenticOps capabilities in networking, security, and observability reimagine how to automate, scale, and simplify IT operations in the AI era

Cisco unveils new AgenticOps innovations to simplify and scale AI-driven IT operations

Cisco has announced new AgenticOps innovations for the AI era. First launched last year, AgenticOps is an agent-first IT operating model for autonomous action with built-in oversight. New capabilities unveiled today across networking, security, and observability further transform how IT teams operate at scale.  

“For teams responsible for operating and securing distributed networks and infrastructure, AgenticOps represents a profound and fundamental shift away from complexity,” said Jeetu Patel, President and Chief Product Officer, Cisco. “This is the true power of Cisco as a platform. By delivering agentic capabilities aligned to critical IT operations priorities, we’re combining Cisco’s unique cross‑domain visibility, purpose-built models, and governance together to supercharge teams.”

Last year, Cisco introduced AgenticOps and redefined how AI is applied in networking to manage the growing complexity of modern IT operations. Powered by advanced AI and unified network data, including the Deep Network Model, solutions like Agentic Workflows and AI Canvas help IT teams troubleshoot faster and automate securely. Now, Cisco is extending agentic-driven operations across networking, security, and observability, delivering AgenticOps to support IT operations in cloud, on‑premises, air‑gapped industrial, enterprise, data center, and service provider environments.  

New tools, skills, and platform enhancements across networking, security, and observability include: 

Operating networks at AI scale with intelligent execution  

  • Campus, Branch, and Industrial  
    • Autonomous Troubleshooting: End-to-end agentic investigations across campus, branch, and industrial networks triage connectivity and experience issues, cutting MTTR to minutes.  
    • Continuous Optimisation: Context-aware agentic recommendations to prevent performance degradation before users feel it.
    • Trusted Validation: Risk-aware agentic assessments validate network changes against live topology, configuration, and telemetry, including identifying impact and blast radius.
    • Experience Metrics: Transforms thousands of network signals into a single view focused on clear, actionable metrics for user experience, such as Time to Connect, Capacity, and Roaming. 
    • Agentic Workflow Creation: Create production-ready, deterministic automations within Cisco AI Assistant.
  • Data Centre: Early detection and intelligent event correlation with AgenticOps for data center networks enables the delivery of prescriptive recommendations to optimize performance. 
  • Service Provider: Accelerating the journey to autonomous networking, agentic capabilities in Crosswork AI identify, diagnose, and resolve complex, multi‑vendor issues in service provider networks with greater speed, accuracy, and confidence.

Turbocharging firewall operations in Cisco Security Cloud Control 

  • Proactive Recommendations: Proactive analysis of firewall traffic allows agentic policy capabilities to identify and recommend more robust zero trust controls for sensitive applications.
  • Operational Efficiency: AgenticOps troubleshooting and optimization capabilities detect issues such as elephant flows impacting firewall performance.
  • Continuous Compliance: Agentic compliance capabilities continuously evaluate firewall configurations to automatically identify PCI-DSS deviations and recommend remediations to stay compliant. 

Visibility and control across Agentic applications 

  • Tracking the performance, cost, quality, and behaviour of LLMs and agentic applications, AI Agent Monitoring in Splunk Observability Cloud visualises agent workflows.
Tags: AgenticOpsAICisco
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