Written by Andrew Wooden
A report commissioned by kit vendor Nokia claims operators are unable to effectively deploy AI ‘because they are using legacy systems with proprietary interfaces.’
The report – conducted by Analysys Mason and based on responses from 84 operators – claims that operators cannot access high-quality data sets due to legacy systems with proprietary interfaces, and that ‘this will restrict how quickly they can integrate AI into their networks.’
Half of ‘Tier-1 CSPs’ (CSPs being another name for operators) ranked data collection as the most challenging stage of implementing AI, and only 6% of respondents believed they are at the ‘most-advanced level of automation’. It also calls this level of telco AI nirvana ‘zero-touch automation’, which uses AI and machine learning algorithms to manage network operations.
87% of those surveyed have started to implement AI into their network operations, either as proof of concepts or properly into production, though the report claims the high-quality data issue is also impacting operators’ ability to retain AI talent.
The overall advice from the report is that operators ‘should evaluate their telco AI implementation strategies and develop a clear roadmap for AI implementation to overcome their data challenge and other impediments, such as an inability to scale AI use case deployments.’
