Cisco has spent the past year positioning AI-native networking as the next major evolution of enterprise IT. Behind the messaging is a genuine architectural shift: networks that can self-diagnose, self-optimize, and self-secure—capabilities that are not theoretical but deployable between now and 2027. For partners and IT leaders, this moment represents a chance to turn Cisco’s platform vision into tangible business outcomes such as improved hybrid work, stronger IoT resilience, and modernized branches designed for edge AI.
AI-native networking is far more than layering AI onto existing dashboards. Cisco’s approach rethinks the entire operational loop: massive telemetry reveals what’s happening, intent and policy define what should be happening, and automation transforms how the network responds. Cisco trains its models on telemetry from tens of thousands of environments, more than 38 million devices, and over one billion connected clients across 190+ countries. This scale enables highly accurate baselines, stronger anomaly detection, and more reliable recommendations—all foundational for predictive automation.
Cisco’s integration of ThousandEyes Digital Experience Assurance marks a major leap. Instead of relying on traditional monitoring, ThousandEyes gathers billions of measurements per day across enterprise networks, cloud paths, and the public Internet, correlating that data with Meraki and Catalyst telemetry. Customers using these capabilities have cut mean time to resolution by as much as 50–80%. When a remote office reports that Salesforce is slow, the AI can pinpoint the failing hop, tie it to an ISP segment, and recommend or automatically launch a policy or path correction.
Optimization is just as transformative. Cisco’s AI-enhanced RRM for Catalyst wireless and AI-driven capacity planning for SD-WAN continuously refine RF and WAN performance. Rather than writing fixed rules, administrators define intent—such as ensuring Teams or Zoom calls always meet a given quality threshold—and the network dynamically tunes itself to maintain that standard.
Security follows the same AI-native pattern. Cisco XDR correlates telemetry across endpoints, network traffic, identity, cloud, and email, cutting through noise and highlighting real threats. Security Cloud Control unifies enforcement across Duo, Secure Access, Identity Intelligence, and more. Instead of analysts stitching together logs, the system detects anomalies—like an IoT camera behaving suspiciously—and can automatically isolate, segment, or revoke access.
Cisco is also leaning into self-healing operations through agentic workflows. Demonstrations show AI agents reading Splunk logs, identifying configuration drift in Meraki, comparing it to a source of truth, and automatically correcting the issue using APIs. This moves NetOps toward defining guardrails while autonomous agents handle remediation.
For partners, the path to monetizing these capabilities spans four major service lanes: assessments, design and migration workshops, managed services, and continuous optimization. Cisco’s research underscores the need: while 97% of organizations feel pressure to adopt AI, 86% admit they’re not ready. This creates strong demand for AI-Native Network Readiness Assessments that evaluate telemetry maturity, assurance coverage, automation potential, and security posture, culminating in a roadmap aligned to Cisco’s AI-Ready Infrastructure specializations.
Design and migration workshops then help customers build their next-generation architecture using Cisco Networking Cloud for unified operations, ThousandEyes for digital experience assurance, and XDR plus Security Cloud Control for converged security. These workshops often evolve into larger refresh or transformation projects.
Managed services represent the biggest revenue opportunity. Hybrid Work Experience Assurance, Branch-as-a-Service, or Secure IoT/OT Connectivity services allow partners to deliver ongoing value through end-to-end visibility, SLO-based performance monitoring, AI-driven optimization, and automated remediation. These packages can be priced per site, per user, or per “experience domain,” and Cisco’s partner programs increasingly incentivize these types of offers.
Real-world use cases bring the strategy to life. In hybrid work, ThousandEyes and Meraki/Catalyst telemetry expose end-to-end experience across home networks, ISPs, and SaaS platforms, allowing AI to diagnose and fix issues quickly. In IoT environments—manufacturing floors, hospitals, campuses—AI-based device profiling and XDR anomaly detection help secure unmanaged devices and enforce segmentation automatically. In branch environments, Cisco’s Unified Edge platform enables local AI inference and smarter traffic handling, letting the network decide in real time which workloads should stay local and which should move to the cloud.
Over the next two years, AI-native networking will meaningfully change the way NetOps and SecOps teams work. Instead of configuring individual devices, teams will curate intent and outcomes. Instead of monitoring dashboards, they’ll rely on AI-backed diagnosis and remediation. Instead of selling one-off infrastructure refreshes, partners will deliver recurring experience-driven services.
Cisco’s investments in AI-native NetOps, digital experience assurance, XDR, Security Cloud Control, and edge architectures ensure this shift is underway. For partners, the opportunity is clear: turn Cisco’s platform innovation into packaged, repeatable services that guarantee digital experiences—not just connectivity.
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