Accelerating the adoption of telco AI to deliver autonomous networks

03 April 2023 | Research

Adaora Okeleke

Perspective | PDF (15 pages) | Data, AI and Development Platforms

"Communications service providers are adopting AI on their path to deploying autonomous networks, but data access is the top challenge."


Communication service providers (CSPs) want to accelerate the migration to autonomous networks in order to address mounting pressures to manage costs, grow revenue and improve customer experience. CSPs need to automate network and service operations as much as possible to grow revenue margins and maximise the return on their investments. Analysys Mason’s research indicates that USD125 billion of CSP capex investment was spent on building 5G networks in 2022 and we expect a further USD132 billion to be spent in 2023.  CSPs that can automate their processes can also address emerging sustainable demands such as energy consumption and other associated metrics. CSPs are therefore investing in automation to drive the improved efficiency of their network infrastructure and operations.

Analysys Mason conducted a survey of 84 senior CSP executives worldwide between September and November 2022, to assess their CSPs’ levels of AI adoption, technology-readiness and upcoming investment plans. The results highlight the urgent need for CSPs to address barriers to deploying AI in order to reach the level of autonomous networks.  Only 6% of respondents view themselves as being at the most-advanced level of automation (zero-touch automation), which relies on AI and machine learning (ML) algorithms to manage their networks

The key findings of the survey are as follows.

  • CSPs believe that AI will help them to achieve their operational and business objectives. Improving service quality, growing revenue and improving customer experience are CSPs’ top-three priorities. Other priorities include energy optimisation to meet sustainability goals and operational efficiency.
  • CSPs are deploying several AI use cases with over half running in production and the others running as either proof of concepts (PoCs) or still being explored. Network-related use cases are most common, followed by customer service-related use cases with a focus on improving operational efficiency.
  • CSPs are recruiting expert personnel and developing strategies to ensure that they are able to implement their telco AI initiatives. Only a small percentage of CSP respondents reported that they have invested in AI platforms. Most CSPs do not intend to develop these AI platforms themselves but plan to acquire them ‘as a service’ from their cloud AI platform providers.
  • Access to high-quality data remains a key challenge for CSPs that want to use AI to meet their goals for autonomous networks. This challenge is impacting CSPs’ ability to retain AI talent and this, in turn, is affecting AI maturity.
  • CSPs can outsource AI development and management tasks to fast-track AI use case implementation. This demand creates opportunities for vendors that offer telecoms-specific AI solutions, but these vendors need to demonstrate that their solutions incorporate telecoms, AI, and software expertise.

This perspective summarises the key findings and takeaways from our research.

Accelerating the adoption of telco AI to deliver autonomous networks