Network operators are sitting on a lot of data that can be critical for powering generative artificial intelligence (genAI) platforms, but many of those operators remain challenged by the amount of data they control and how to best work with it.

Craig Silliman, president of Verizon Global Services, during an investor conference this week said that the carrier “ingests over 70 billion data points off the network every single day into our AI engines.”

That volume provides a significant opportunity in powering a genAI model, but also comes with a lot of challenge.

“AI and analytics engines are only as good as the data you put into them,” Silliman said. “We have an enormous body of data across Verizon, but it sits in 29,000 different data sources, which in many ways are fragmented, we don't have common taxonomy. So the journey we're on right now is bringing all of our data together into common platforms and common governance and taxonomy structures.”

Silliman said that this will allow Verizon to take costs out of its operations, “because we spend an enormous amount of money just translating data, moving it from one platform to another.” More importantly, the streamlining of access to that data will help power new services and outcomes.

“It'll accelerate the speed at which we can operate, the insights from insight in data through analytics to insight to customer action,” Silliman said.

Analysts noted this focus on reliable data is crucial for telecom operators to best utilize their large cache of information.

“GenAI is not an off-the-shelf solution or tool that operators can plug into any network and get to work right away,” Monica Paolini, founder and president of analyst and consulting firm Senza Fili, noted in a blog post. “They still need knowledge of their network and experience in running it to guide the model and to select the right data to feed. GenAI models thrive on large data sets, but larger data sets may be noisier and, hence, lead to less accurate results. Running models on reliable and high-quality data, and having well-defined targets are crucial to successful outcomes.”

Ishwar Parulkar, chief technologist for telecom and edge cloud at Amazon Web Services (AWS), told SDxCentral that the cloud giant is increasingly focused on using its extensive computing, storage and analytics capabilities to help operators tackle this challenge.

“They have a lot of network data and sensitivity around that data, and there are still questions around how these large foundational models can imbibe that data without compromising the data,” Parulkar said.

This focus on AI security will be increasingly important as governments also sharpen their focus on maintaining data sovereignty in the age of AI. This was highlighted by the White House Office of Science and Technology Policy having recently introduced its “Blueprint for an AI Bill of Rights.”

“Rules along these lines could limit how genAI is implemented,” Tom Rebbeck, partner at Analysys Mason, wrote in a recent report on these efforts. “The telecom sector could evolve along different regional paths if rules are only introduced in some places.”

The telecom ecosystem is attempting to help guide these efforts.

“That's why one of the things AWS is focused on is building capability in tools to enable some of the security and privacy, of maintaining data security and privacy,” Parulkar said of AWS’ efforts. “But that's where the industry is at. We started exploring how genAI can go deeper into network operations and configurations and design. But this year will be a little early to see something significant.”

Parulkar said he expects those advances to come next year where he expects “a lot more actual tangible products being built in this space.”

In the meantime, the telecom market is continuing to bolster its ability to tackle the genAI challenge.

Industry trade group GSMA, which hosts the annual MWC events, late last month struck a deal with IBM to launch a new training program targeted specifically at genAI.

IBM noted that its most recent “AI Adoption Index” found 40% of telecom operators surveyed are exploring or experimenting with genAI, and 45% have accelerated the rollout of AI. GSMA added that its own research found that while more than half of operators were actively trialing genAI platforms, that activity was mostly being accomplished by larger operators.

A recent IDC report predicts that genAI-focused skills training will drive $1 trillion in productivity gains by 2026, which combined with the treasure trove of telecom data underscores genAI's potential to drive new opportunities across the ecosystem.