AIOPs: The Next Big Thing for Telcos

As telcos continue to roll out 5G networks, it is imperative for them to move beyond traditional network operations and on to a data-driven, adaptive approach for enhanced service delivery and business growth.

Although network data can provide information “gold,” it must be mined to accelerate the journey from traditional operations to artificial intelligence for operations (AIOps) for telcos. Often this process is hindered by a number of shortcomings. First, the data is not typically collected in real time, which is what is needed to facilitate modern software-defined services. Second, the massive volumes of network-level data take a very long time to assemble and analyze. Third, the data is not always provided in an easily consumable standard open format.

A lack of business intelligence—offering vital insights into device and application behavior on the network—makes it difficult, if not impossible, to effectively address issues that impact the quality of user experience. A deficiency in understanding how network services are being utilized down to a user or enterprise level makes it exceedingly challenging to assure performance. The same can be said for security issues affecting the network and user experience. When only “piecemeal” data is available, there is an inevitable struggle to manage the network as an end-to-end service.

AI Tools Hold Great Promise

AI’s ability to automate the ingestion of high volumes of data and leverage machine learning to analyze that data could be a real game changer for telcos. AI can present findings to either predict, alert, or advise on issues, and can aid carriers with proactive decision-making.

This potential has led to a growing interest in service provider AIOps platforms that can equip different teams with extensive analysis of volumes and categories of data to improve key processes and tasks and to guide more-effective actions. Evidence of this trend can be found in market growth statistics. According to a recent report, the AIOps market size “is estimated at USD 27.24 billion in 2024, and is expected to reach USD 79.91 billion by 2029, growing at a CAGR of 24.01% during the forecast period (2024-2029).”

AIOps platforms are expected to tackle the biggest challenges facing service providers when dealing with the huge volume of data generated by today’s complex 5G networks. In the past, tons of data would be deposited into data lakes, where scientists could spend years trying to analyze this vast amount of information. Although AI is exceptionally good at processing such large quantities of data, the value of the analysis is completely dependent on the quality of the data used to arrive at the results. In short, the adage “garbage in, garbage out” truly applies.

What is now needed to achieve meaningful results is more context and better curation of data. Real-time, comprehensive data analysis that includes packet, RAN, and core data is essential for enhancing network performance and user experience.

The Secret to AIOps Success

The secret to AIOps success is high-quality, high-value, and low-volume data. By conducting high-quality analytics and filtering at the source, it becomes possible to provide “gold standard” curated data that is AIOps-ready.

Fueled by rich network-level data across all lines of the business, including IT, enterprise, fixed cable, wireless, and security, AIOps can look to make important improvements in network operations. Such advances might include enhancements in how applications are managed and provided to end customers, end-to-end visibility of application and service performance to end customers, anomaly detection for automated pattern discovery and prediction, and increased utilization of software-driven networks for new business services, to name a few.

Evolving network architectures such as 5G require this type of curated data approach to enable new use cases and revenue streams for carriers. Furthermore, using this type of curated data makes true monetization possible via improved service quality, predictive maintenance, and security enhancements. AIOps holds tremendous potential. To realize that potential, telcos need to ensure the data they rely on is the very best it can be.

Learn more about how to achieve AIOps success.