Avoid outage outrage: Why AI-assisted operations is the next big thing for networks
By Kailem Anderson – You can’t go far in the broader tech industry these days without coming across a conversation about the future of artificial intelligence (AI). I’ve been talking about AI and machine learning (ML) in telecom networks for quite a while, and for good reason: network operators desperately want and need AI to help simplify their complex network operations.
Troubleshooting and resolving issues in today’s increasingly complex and dynamic networks has become a major operational burden, complicated by multiple management systems and a flood of raw network data and alarms.
This results in two major challenges. First, the flood of raw data obfuscates true insight into the state of the network, making it difficult to detect indications of potential network outages before customers have been impacted. Second, the “trouble-to-resolve” process becomes slow and tedious as the team struggles to identify, isolate, and rectify the issue’s root cause.
These challenges can result in network troubles that last for weeks or even months. In North America alone, an IHS Markit report from 2016 estimated that network outages cost enterprises $700 billion a year in lost revenues and productivity.