AI strategy: To centralise or not? (chart)

Though only a handful of telecoms operators, including Telefónica and Elisa, have an ambition to drive new revenue growth through development of their own IP in AI, all operators will need AI to permeate their internal processes to compete effectively in the long term – it is the next logical phase of cost efficiencies the industry has been pursuing over the last ten or more years. The value of AI and automation go beyond this, augmenting every decision and process to become more informed and accurate, and establishing the fundamentals for faster experimentation, which could give rise to entirely new ways of operating.

Our research outlines the roadmap to a successful AI and automation strategy, the crucial second stage of which, following the adoption of big data analytics, is to establish a centralised AI initiative. Those who have done so are especially successful in progressing from PoCs to live AI deployments, as evidenced in the chart above, based on an STL survey across more than 50 telecoms operators.

Key activities of the centralised AI unit include:

  1. Coordinating the organisation’s approach to data management
  2. Setting the AI development roadmap
  3. Building data science and software development skills and tools
  4. Evangelising the value of AI

See our research on analytics, automation and AI: