Using AI to Manage the Network: 10 Focal Points for Improving Service Capabilities, System Integrity, and Staff Impact
Description
This IDC Perspective provides insights into using AI to manage the network. Onrushing digital business demands, continual technology advancements, and ever-advancing IT portfolios and practices are applying more pressure on the network infrastructure and network management systems, services, and staff. Network budgets, designs, repairs, tools, and talents are failing to keep pace with IT and business requirements. Enter AI. Armed with a comprehensive set of network data, AI-powered analytics, and precision-guided automated actions, networking solutions — from hardware devices to software solutions to cloud-based services to management systems — are increasingly applying AI to heighten network resiliency and responsiveness as well as networking staff productivity and impact. IDC research and consultations have exposed worthwhile guidance for IT organizations looking to advance their network success by taking advantage of AI-powered networking solutions. As AI accelerates as a core network capability, key focal points are helping guide investment, innovation, best practices and, ultimately, IT and business returns."The network and networking staff are not keeping pace with IT requirements and much-needed digital business advancements. Cloud computing services have been offering a more efficient and effective alternative to traditional datacenters and computing architectures for over 20 years. In all that time, the network continued to advance primarily as an on-premises and highly customized environment — deployed, operated, protected, and repaired by highly trained technical staff executing mostly manual tasks. The timing and risks associated with these tasks are more and more of a mismatch to the fast-moving, fail-safe digital business model, " says Mark Leary, director, Network Observability and Automation, IDC. "The power of AI enables networking systems and network management tasks to be more fully automated, less prone to failure, faster to fix, less vulnerable to threats, and more accepting of rapid and reliable innovation. This leads to heightened network service integrity and networking staff productivity while reducing the cost and complexity of engineering and operating the network."
Table of Contents
15 Pages
Executive Snapshot
Situation Overview
Be Prepared to Overcome Barriers When Applying AI to the Network
Solidify and Simplify Networking via a Platform Approach
Leverage Automation for Both Analysis and Action
Accelerate AI Influence over Network Management Functions
Demand More from AI in Support of Networking Staff Tasks
Align AI to Network Domains of Critical Concern
Leverage Network Data for Both Proactive and Reactive Management
Increase Supplier Contribution to Network Success
Raise Expectations for Productivity, Agility, and Resiliency with AI
Hope Must Be Tempered by Real Capabilities and Results
Advice for the Technology Buyer
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