Nearly half (45%) of telecom providers expect spending on generative artificial intelligence (AI) to “surge” over the next two years, according to research conducted by global strategy consulting firm Altman Solon. Providers could see a six-fold increase in AI spending by 2025, the researchers said.

The findings are based on a survey of 100 “senior business leaders” at tier one providers headquartered in the U.S., western Europe and the Asia Pacific region.

Altman Solon studied 17 potential telecom generative AI use cases that fell into four broad categories, including product & marketing, customer service, information technology (IT) and network.

Customer chatbots are the most widely adopted use case, the researchers said. Sixty-three percent of respondents already have customer chatbots in production.

“Other common use cases focus on employee assistance, including call center documentation and network operations knowledge management, each key drivers of operational efficiency,” said Altman Solon, which uses the term “Clear Wins” to describe these use cases.

AI use cases that are expected to take longer to implement are those within network planning and IT software development. The reason is that these use cases are more complicated to implement.

“Within these areas, network root cause analysis, interfacing with network ML [machine language] models and software code documentation are use cases more likely to be adopted in the near term, while network planning and optimization have inherent complexities that delay their likely adoption times,” said the researchers.

Source: Altman Solon

Most providers expect to use off-the-shelf models rather than developing their own foundation models. Nearly two-thirds (65%) of respondents plan on training their models on their own proprietary internal data.

The Altman Solon report offers several pieces of advice for telecom providers implementing AI, including:

  • Review data governance practices and ensure compliance with data security, privacy and sovereignty requirements
  • Strong data governance practices will be particularly important for what the researchers call “Big Bet” use cases such as those involving network planning and optimization
  • Telecom providers should embrace integrating generative AI throughout their operations and have a clear understanding of use cases, deployment paths and data dependencies

Two providers that are testing AI applications internally are AT&T and Lumen.

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