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Analysys Mason is a Nokia study on artificial intelligence18. 08. 2023 Friday / By: Robert Denes / Generic / Exact time: BST / Print this page
A lmost 50% of Tier 1 telcos rated data collection as the most challenging stage of the telco AI use case development cycle. Other challenges include lack of technology maturity, lack of scaling AI use cases, lack of budget, and lack of appropriate skills, among others.
Telecom operators face a number of challenges, such as access to high-quality data sets, to effectively use artificial intelligence (AI) to enable autonomous operations, according to a survey conducted by Analysys Mason on behalf of the Finnish telco.
CSPs (Communication Service Providers) do not have access to high-quality data sets (which allow them to make more accurate decisions) because they use legacy systems with their own interfaces. This will limit how quickly they can integrate AI into their networks,” the findings state. He emphasized that almost 50% of Tier 1 telecom companies.
He described data collection as the most challenging phase of the telco's AI use case development cycle. Other challenges include lack of technology maturity, lack of scaling AI use cases, lack of budget, and lack of appropriate skills, among others.
However, the study also found that only 6% of telcos surveyed believe they are at the "most advanced" level of automation, meaning zero-touch automation that relies on artificial intelligence and machine learning (ML) algorithms to manage the network and in its development. activities. The issue of high-quality data also affects CSPs' ability to retain AI talent.
According to the study, 87% of telcos have started implementing AI in their network operations, either as a proof of concept or in production; 57% of respondents said they had deployed telco AI use cases to the point of production.
Telco respondents said they believe AI will improve network service quality, drive top-line growth, customer experience and energy optimization to meet their sustainability goals.
“CSPs need to move to more autonomous operations if they want to manage networks more efficiently and meet their core business priorities. But as this research demonstrates, access to high-quality data remains a critical barrier to telco deployment of AI within their networks,”said Adaora Okeleke, senior analyst at Analysys Mason.
Okeleke added that telcos "really need to look at" their AI implementation strategy to address the data quality issue.
CSPs are aware of the challenges of embedding AI more deeply in their operations and, as this research shows, the steps they can take to make a positive difference, including building the right ecosystem of supply partners with the right skills to better they can serve. according to their network needs,"“ said Andrew Burrell, head of business applications marketing, cloud and network services at Nokia“.