Against a backdrop of increasingly complex network operations and a shortage of skilled personnel, AI-powered autonomous operations are attracting attention as a way to balance cost control with quality. Through specific functions and use cases, this article explores the direction of automation efforts in the field.
Traditional operating models are reaching their limits as network configurations become more complex and skilled personnel remain in short supply. AI-powered autonomous operations are attracting attention as a way to balance cost control with quality maintenance.
By incorporating autonomous AI agents known as agentic AI, organizations may be able to detect early signs of failures in real time and remediate them proactively.
Nakamura Yuya (中村裕也) of Hewlett Packard Japan explains that using agentic AI is expected to help address the limits of monitoring, prevent failures before they occur and reduce downtime.
Organizations are considering using AI to reduce labor-intensive tasks such as investigating failures and reviewing configurations. The direction of efforts to reduce the workload and promote automation in network operations is being discussed.