Why AI for Networking Is Redefining IT Operations

As networks grow in complexity, traditional management methods can’t keep pace with the speed and scale of modern demands.

Artificial intelligence for AI operations, which is commonly known as AIOps, is emerging as a practical way for organizations to simplify network management, improve performance and empower IT teams to focus on higher-value work.

Unlike the idea of fully autonomous networks, today’s AIOps solutions act as intelligent assistants. They gather, correlate and analyze data across multiple network systems to help administrators quickly identify root causes, predict potential failures and automate repetitive tasks — all while keeping a human in the loop.

One of the most immediate advantages of AIOps is accelerated troubleshooting. Instead of logging into multiple systems to isolate issues, administrators can use an AI-enabled dashboard, or canvas, to view correlated data on a single pane of glass.

This centralized visibility allows IT teams to diagnose issues faster and reduce manual configuration errors. By automating routine tasks and minimizing misconfigurations, organizations can improve network stability and reduce downtime. The result is a more efficient and less error-prone environment.

A frequent misconception is that AI will replace IT roles. AIOps is designed to enhance human expertise, not replace it. AI can handle repetitive or data-intensive work, but it still relies on people to ask the right questions, train models with accurate data and validate the system’s recommendations.

Another misunderstanding is that AI systems will work perfectly out of the box. As with any advanced technology, AIOps requires human oversight to fine tune prompts, interpret insights and ensure accurate results. Successful adoption depends on partnership between skilled IT professionals and AI tools that augment their abilities.

AI for networking is already proving its value in several practice areas.

• Predictive analytics: AI can identify performance anomalies — such as ports showing abnormal error rates — before they lead to service disruption.
• Traffic optimization: Intelligent algorithms dynamically route traffic along the best-performing paths to improve reliability and throughput.
• Wireless efficiency: Through radio resource management (RMM), AI can automatically shift clients between access points to reduce congestion and interference.
• Threat detection: By monitoring network behaviors, AI can flag unusual activity — such as unexpected data requests from IoT devices — to help IT teams respond faster to potential security threats.

These capabilities not only strengthen performance and reliability but also allow IT staff to devote more time to strategic initiatives instead of constant firefighting.

The biggest barrier to AIOps adoption isn’t the technology itself, but rather the legacy infrastructure still in use. Many organizations continue to manage networks through command-line interfaces, which limit visibility and automation potential.

To fully leverage AI, organizations need to operate on modern platforms — such as Cisco Catalyst Center, Aruba Central or similar solutions — that provide centralized management and integrate with AI-driven analytics. These platforms serve as the foundation for advanced features such as digital twins, where administrators can simulate network changes before deploying them in production.

Modernization also involves improving data visibility and security through role-based access control (RBAC) and cross-platform integration. As vendors open their ecosystems to third-party data sources, IT teams gain a more complete, multidimensional view of their network’s performance and health.

Every organization’s AIOps journey is unique. Some may just be beginning the journey, moving from manual configuration to a managed platform, while others are ready to experiment with assurance features or predictive insights. The key is to understand your current maturity level and build a roadmap that evolves over time.

CDW’s networking experts can help your organization assess the current environment, identify readiness gaps and develop that roadmap for AIOps adoption. Through services such as the Next Generation Network Assessment, CDW provides visibility into hardware, software versions, access controls and platform capabilities — laying the groundwork for AI-enabled IT operations.