- Executives from cloud and carrier organizations expect early AI use cases to become “table stakes,” not drivers of long-term value
- The next step for many telcos is AI for network operations, and that requires teaching agents to understand network data in context
- Using AI to enhance revenue will provide the biggest payoff, according to AWS’s CTO Telecom
AT&T CEO John Stankey says AI is delivering ROI for the company, but he’s not satisfied. “We’ve gotten very strong returns,” he told Bloomberg Surveillance on July 22, calling out software development, engineering applications, customer service and pricing as key areas where AT&T leverages AI. But he said the gains AI is delivering in customer service are likely to be “efficiencies that get competed away in the market,” as other carriers adopt them.
“The things that we do that really give us strategic advantage, like maybe writing software for capabilities that we didn’t have before that make us better at pricing or driving yield on the network or more efficient, those are the ones that maybe we get to keep,” Stankey said. “We need more of the ones that drive strategic advantage to balance out some of the ones that we know are just the table stakes that we need to compete in the market.”
Many telcos have already implemented agentic AI for customer service and are now evaluating AI for network operations, said Ishwar Parulkar, CTO Telecom at AWS, in an interview with Fierce Network.
Parulkar pointed out that network operations differ from the other two major AI use cases telcos have explored: customer service and organizational efficiency. Those can build on lessons learned in other industries. But the challenge of teaching AI agents to optimize the interactions between radios, frequency bands, servers, smartphones and telco software is unique to the wireless industry.
AWS has helped several telcos use AI to boost network efficiency, including BT, NTT Docomo and C-Spire. Parulkar said the hardest part of AI for wireless networks is building the software layer that helps agents contextualize and understand data.
“There's this emerging layer in the middle of context and semantics that has to be created, and what we learned was that most of the effort goes into creating that layer,” said Parulkar. He said a new service called AWS Context, set for launch in December, is being developed to help “build that layer in the middle” for telecom and other industries.
Competitive advantage
AI can definitely make networks faster and smarter, but how much long-term value can this deliver? “Over time, I think it's still network operations,” said Parulkar. “It's about reducing cost and being more efficient. I think where the difference will happen is when telcos turn it around to create value or increase the top line.”
Parulkar gave a couple of examples of ways telcos can use AI to enhance revenue. One is by reselling services that leverage both AI and the wireless networks, such as logistics. Another is by using AI to boost ARPU.
“One of the emerging areas is the connection between the customer and the network and using that to proactively determine what could happen to relate customer issues to network conditions, and then knowing or understanding the customer better, upselling or creating network offers or connectivity offers to serve that customer,” he said.
Parulkar said AWS has numerous telco AI engagements for both customer service and network operations but “the linkage between that is just starting, so we're working with some early thinkers in this space who are looking to connect customer experience with the network.”
The hyperscaler has positioned its infrastructure and expertise as a foundation for telcos that want to leverage AI, leaving room for its customers to create unique solutions using their own data and algorithms. But there are platform solutions out there, and if AI is indeed becoming table stakes for network operators, some may opt for a turnkey approach so as not to fall behind.
Using AI to prepare for AI
The biggest challenge for telcos, however is that they can't fully modernize their operations with AI while critical systems still run on legacy mainframes. But migrating these systems to the cloud is time-consuming and taking them offline is risky.
Parulkar said AI agents are helping speed up migrations. “With these coding agents, you can modernize the code itself. So there’s a lot to be done there, a lot to be taken advantage of there. So that's one big motion we see with telcos,” he said.
One example is AT&T, which is using AWS Agentic Services to accelerate the migration of network service enablement to AWS. Parulkar said the other nationwide wireless carriers are “definitely looking” at more workload migrations as well.
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