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    HomeNewsTelco silos stopping operators from realising AI potential, report claims

    Telco silos stopping operators from realising AI potential, report claims

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    A siloed approach to artificial intelligence is causing operators to be followers and not influencers of the technology, a new report has claimed.

    ABI Research said that operators’ use of the technology is split between customer services, service assurance, cybersecurity and network management, spanning modernisation, virtualisation and the cloud.

    However, the management and architecture of these systems is fragmented between the various departments, with their own vendor partners, frameworks and implementation strategies, the report claimed.

    Don Alusha, Senior Analyst at ABI Research, said: “At present, AI in telecoms has a narrow application in numerous use cases, particularly customer management and network acceleration. A holistic and general-purpose approach to AI may be required to enable Mobile Service Providers (MSPs) to become AI influencers rather than followers. This is fundamentally different from the siloed AI operations that predominate today.”

    He cited AT&T and Telefónica as the exceptions, with their respective Acumos and LUCA projects attempting to span different parts of their operations. However, Alusha said other operators need to overcome their logistical division and develop a coherent strategic framework for the technology’s implementation.

    He recommended a unified vision that spans cloud, vendors’ own hosting solutions, plus data centres and platforms. Open source AI frameworks and platforms, already used by the likes of NTT DOCOMO, could be the best method of building up internal skills, he added.

    Alusha added: “Work remains to be done on two fronts: one, standardise the data format to achieve data harmonisation; and two, institute AI standards with particular focus in the network domain, where little attention has been paid thus far.

    “Pushing for an AI global strategy beyond what is currently in place today is likely to have a stronger impact over time, particularly in the context of developing AI platforms with an eye to enabling massive scalability and agility of features.”