Written by Yanitsa Boyadzhieva
- New report from Analysys Mason pinpoints the main obstacles to telco AI use case developments
- Inaccessibility to high-quality data is the top challenge for numerous telcos globally
- This issue impacts operators’ ability to integrate AI into their networks and to retain much-needed talent
- Telcos are urged to assess their AI implementation strategies and tackle the data quality obstacle
The biggest challenge facing operators on their path to accelerated implementation of telco AI for the automation of their networks is the inability to access high-quality data, according to research undertaken by Analysys Mason.
The resulting report, Accelerating the adoption of telco AI to deliver autonomous networks, which was commissioned by Nokia, focuses on the current levels of automation across telecoms operators and the main barriers standing in the way of AI use case developments, despite ongoing investments.
The number one challenge telcos face when developing AI use cases is the lack of access to high-quality data, which can impede efforts to “effectively” deploy AI for network and service operations enhancements – this was highlighted by 21% of the 84 service provider survey respondents (see graph above).
