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Introduction

This report is the first in a series of reports on the role of AI in network operations. It provides information on the drivers for the adoption of AI, and highlights examples of AI network operations use cases currently deployed by CSPs.

Highlights

  • Growing network complexity is driving the need for CSPs to automate network operations.

Features and Benefits

  • Highlights the key drivers for the adoption of AI in managing CSP network operations
  • Provides insights into the varied set of possible AI use cases CSPs can deploy

Key questions answered

  • Why do CSPs require AI with their network operations?
  • What AI use cases can CSPs deploy to improve network operations?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Recommendations

  • Recommendations for CSPs
  • Recommendations for vendors

Growing network complexity drives the need for automation in CSPs

  • Growing network traffic
  • CSPs are deploying next-generation networks
  • Automation will be critical to the management of CSP next-generation networks

AI brings a data-driven approach to scale automation of CSP network operations

  • What is AI?

AI use cases to improve CSP network operations

  • CSPs face multiple challenges with network operations
  • AI use cases that CSPs can apply to improve network operations

Appendix

  • Ovum's taxonomy of AI algorithms
  • Further reading
  • Author

Recommended Articles

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