3 Uses for AI in Next-Gen OSS
AI is receiving a great deal of attention, but what does it mean for OSS?
Service providers are working to minimize their reliance on manual processes in order to bring operations costs down to sustainable levels. OSS will play an important part in achieving their goals. OSS naturally align with artificial intelligence-enabled machine learning. As networks become more software-defined, they can become less reliant on manual inputs from network engineers. As a result, AI may play a role in transforming and enhancing specific OSS functions, roles and responsibilities. Below are three examples where AI could have a crucial impact on OSS.
1. Dynamic Capacity Response
AI can significantly improve service provider efficiency with its ability to analyze vast volumes of traffic data, predict capacity needs and automate tasks. This machine-learned knowledge can help optimize route design and network configuration, maximizing utilization and minimizing capacity overbuild. Results can be fed back into the AI engine to continuously improve future predictions and decisions.
AI will also be useful in aiding efficient and fast fault management and resolution. Drawing from a library of previous incident and resolution information, AI will be able to quickly determine root causes of service-affecting issues and identify the correct remedies.
2. Self-Configuring Networks
As AI capabilities become more widespread, they can respond to localized issues. For example, AI will enable systems to correlate network traffic fluctuations to real-world factors like weather or major news events. Systems will learn patterns from previous similar situations and adjust the network to cope with shifting demand before it impacts performance. AI will also be able to recognize regular spikes in network traffic or maintenance periods and optimize the network’s configuration dynamically.
3. Predictive Security
Fraud prevention and security is another domain in which AI capabilities will have a major influence. AI’s ability to spot patterns and correlate them with previous events is ideal for identifying fraudulent behavior, sometimes before it's committed, while understanding the propensity of certain types of users to commit fraud. In addition, AI may be applied to stop cyberattacks by executing tasks such as preventing malware propagation.
The data used to drive AI already exists within service providers' OSS. And by leveraging AI, service providers can reach their goals of having more automated, streamlined operations processes and reducing costs.