Cisco announces rollout of new AgenticOps features for IT operations

· Source: Tech Monitor · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure, Cybersecurity & Data Privacy · Depth: Intermediate, short

Summary

Cisco has announced a significant expansion of its AgenticOps operating model at the Cisco Live EMEA event, introducing new features across networking, security, and observability. These enhancements, rolling out in stages from February 2026, extend agent-driven automation and oversight to address the growing operational and security demands of distributed IT infrastructures. The AgenticOps model leverages real-time telemetry from Cisco platforms like Nexus One, Splunk, and Secure Firewall, along with third-party sources, to enable automated troubleshooting and operational management while maintaining human oversight. Specific updates include agent-led investigations for networking, prescriptive recommendations for data centers, multi-vendor issue resolution for service providers, and proactive analysis for zero trust policies in security operations. Additionally, Cisco introduced the Silicon One G300 processor for large-scale AI clusters and enhanced AI Defense and SASE capabilities.

Key takeaway

For CTOs and VPs of Engineering managing distributed IT infrastructures, Cisco's AgenticOps expansion offers a strategic shift towards automated operational and security management. You should evaluate these new agent-driven capabilities, particularly for campus, branch, data center, and security operations, to reduce complexity and enhance efficiency. Consider how the Silicon One G300 processor and Nexus One unified management plane could support your large-scale AI and network infrastructure needs.

Key insights

Cisco's AgenticOps model automates IT operations and security using agent-driven intelligence and cross-domain telemetry.

Principles

Method

AgenticOps processes real-time telemetry from Cisco and third-party platforms to enable automated troubleshooting, root cause analysis, and prescriptive recommendations across networking, data center, and security environments.

In practice

Topics

Best for: CTO, VP of Engineering/Data, Director of AI/ML, MLOps Engineer, AI Operations Specialist, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by Tech Monitor.