Telcos need to address challenges to deploying AI to realise autonomous operations: Analysys Mason-Nokia study

Telecom operators need to address several challenges, such as accessing high-quality data sets, to effectively deploy artificial intelligence (AI) in order to realise autonomous operations, according to the findings of a survey by Analysys Mason, commissioned by Finnish telecom gear maker Nokia.

“CSPs (communication service providers) are unable to access high-quality data sets (which will enable them to make more accurate decisions) because they are using legacy systems with proprietary interfaces. This will restrict how quickly they can integrate AI into their networks,” as per the findings.

It stressed that almost 50% of tier-1 telcos ranked data collection as the most challenging stage of the telco AI use case development cycle. Other challenges include a lack of technology maturity, inability to scale AI use case deployments, lack of budget, and a lack of the right skillsets, among others.

At the same time, the study found that only 6% of telcos surveyed believe they are at the “most advanced” level of automation, or zero-touch automation, which relies on AI and machine learning (ML) algorithms to manage and improve network operations. The high-quality data issue is also impacting CSPs’ ability to retain AI talent.

According to the study, 87% of telcos have started to implement AI into their network operations, either as proof of concepts or into production; with 57% saying they have deployed telco AI use cases to the point of production.

Telco respondents stated that they believe AI will improve network service quality, drive top-line growth, customer experience, and energy optimisation to meet their sustainability goals.

“CSPs must transition to more-autonomous operations if they are to manage networks more efficiently and deliver on their main business priorities. But as this research demonstrates, accessing high-quality data remains a critical obstacle to deploying telco AI within their networks,” said Adaora Okeleke, Principal Analyst, at Analysys Mason.

Okeleke added that telcos need to “really examine” their AI implementation strategies to address the data quality issue.

“CSPs are aware of the challenges of more deeply embedding AI into their operations and, as this research points out, the steps they can take to positively alter that situation, including building the right ecosystem of vendor partners with the right skillsets that can better cater to their network needs,” said Andrew Burrell, Head of Business Applications Marketing, Cloud and Network Services at Nokia.