AI is having a profound effect on corporate networks. Even the slightest latency can impact the performance of AI workloads, creating bottlenecks that hinder AI model training and result in poor GPU utilization. As a result, many organizations are modernizing their networks to better support the demands of AI.
At the same time, AI can also benefit network management by improving visibility, automating tasks, analyzing data and addressing many issues without human intervention. AI-enhanced network management goes beyond traditional monitoring to enhance efficiency, reliability and security and provide the actionable intelligence needed for strategic decision-making.
The Problems of Traditional Network Management
IT teams use an array of tools to monitor and manage the corporate network. A survey by 451 Research found that the average IT team uses 10 to 30 monitoring tools, often from different vendors. A separate IBM study found that the average organization uses 83 different security tools from 29 different vendors. This overly complex environment increases operational and security risks.
Juggling multiple tools and analyzing disparate metrics makes it difficult to identify the root cause of problems. Security tools are seldom integrated, leaving blind spots that are potential entry points for malicious actors. Manual effort and a constant barrage of notifications and alerts stretch staff resources to the limit.
AI-enhanced network management not only relieves these pressures but also effectively transforms network management. IT teams gain an end-to-end view of network health and application performance and the insights needed to enhance the user experience.
Taking Network Analytics to the Next Level
The key is AI’s ability to analyze vast amounts of data in real time. AI-powered tools can ingest and process telemetry data from across the network to spot subtle deviations in behavior that human administrators might miss. Best-in-class tools can also identify long-term variations in performance and compare the network’s health with comparable networks in related industries.
These capabilities enable AI to create custom baselines to reduce noise and false positives while providing IT teams with the intelligence needed to accurately identify the root causes of issues. AI-powered tools can respond to issues in real time or provide administrators with remediation guidance. AI can also predict many problems before they occur and identify potential security threats.
Machine reasoning can further enhance network management. While machine learning relies on statistical pattern recognition, machine reasoning uses symbolic concepts and a knowledgebase to draw logical conclusions from established facts. Its structured approach is ideal for tasks such as network troubleshooting that require logical deduction and step-by-step problem-solving.
Eliminating the Need for Manual Intervention.
Network automation is another key benefit of AI. AI-powered tools enable more intelligent automation that reduces administrative overhead by minimizing the need for manual intervention. These tools can deploy and manage network policies, identify and classify devices on the network, and ensure the consistent enforcement of security across the enterprise. Because AI “learns” over time, it can create a more adaptable network that meets increasing demands and optimizes the user experience.
Implementing AI-enhanced network management does present challenges. Organizations will have to hire experts or upskill existing staff to set up, maintain and fully utilize AI. AI-powered tools can be expensive, and legacy systems may not support them. Accessing real-time data from across the network can be difficult in multivendor environments. Ultimately, however, the benefits of AI outweigh the cost and effort involved.
How Cerium Can Help
The Cerium team has extensive experience in networking and a practice dedicated to AI. We can help you take advantage of AI-enhanced network management tools from Cisco and other leading vendors to transform your network operations.
