Heavy Reading reports that respondents to their 2024 5G AIOps operator survey are eager to integrate AI into their operations processes. Over half expect full integration within two years.
This enthusiasm is industry wide. McKinsey and company stated that GenAI is expected to deliver significant value to telcos.
That said, there’s also caution about its impacts, but AI is a tool that extends human capabilities. And people are at the heart of networking.
How & Where does AIOps Help Network Operators?
So let’s consider how uniting AI with automation and prediction can optimize operations and performance. Today’s dynamic services require proactive, not just reactive, multi-domain management in fast-changing conditions.
AIOps is meeting these needs in an expanding range of use cases, improving efficiency, and providing new insights across domains.
- In RAN, there’s RAN slicing, massive MIMO optimization, and QoE optimization.
- In transport, AIOps supports performance monitoring, predictive analytics, and assisted troubleshooting.
- In Core and edge, AIOps tools extract and analyze services, network performance and subscriber interaction data faster than ever before.
Adding Value to Prediction & Automation
Because AI analyzes vast amounts of data and rapidly infers patterns in groupings, prediction and automation have a greater value and effectiveness.
AIOps isn’t just another buzzword. The transformation is already happening in today’s networks. So how can you get there?
Starting your AIOps Journey
Moving to AIOps is complex, best viewed in three main stages: Manual, Open-loop, and Closed-loop. Every business takes a different approach. Most start small and build from there.
Success Factors in the AIOps Journey
- Like any new technology, AIOps brings challenges. Start by determining budget, time frame, level of effort, goals, and success metrics. Several key factors govern chances of success.
- Data quality and architecture govern the accuracy and value of analysis and prediction, and must be well-thought-out from the start. Data from multiple sources must be carefully harmonized.
- Skill sets and expertise must be in place to ensure long-term success and continuity.
- Operational costs from increased compute resources, storage, and power demand can be mitigated, and should be factored against the benefits.
- Integration brings unavoidable cost and workload, which can be minimized through established, open solutions, phased implementation, and working with qualified experts.
- And finally, security, which is vital in deploying AIOps solutions.
Extend your Operations Capabilities with AIOps
AIOps is a journey. Most operators need guidance along the way. Done right, AI extends human capabilities while reinvigorating businesses and their customer relationships.
Our rich experience comes from exploring and deploying AI with industry organizations and major network operators, with people at the heart of everything we do.
We want to hear about your AIOps vision. Let’s share an open dialogue about how to move forward.
