Courtesy of Verizon Business
To guide the strategy, Bhattacharya said Verizon created an AI council made up of executives from legal, IT, security, network, product development, consumer, business, and other departments. She said the group hoped to mitigate risks linked to AI adoption, with the aim of protecting customers’ and Verizon’s proprietary data and using data responsibly.
Verizon also released a set of AI principles to ensure the company uses AI responsibly, in ways that safeguard data and prevent bias, she said.
AI in action
Incorporating generative AI into its business-to-business customer-service strategy helps agents answer questions and resolve issues faster, Bhattacharya said. She added that the AI system could quickly pull up a customer’s history, including their devices, services, call history, and visits to Verizon stores.
This keeps agents from spending time asking background questions — they already have the information in front of them, she said. “It adds a layer of conversational capabilities that reduces the cognitive load on both the customer side as well as the agent side,” she added.
Generative AI then helps predict the reason for a call based on a client’s past needs and offers recommendations to agents to resolve issues, Bhattacharya said. However, agents make the final decision about whether a recommendation is appropriate and should be followed.
The technology also summarizes calls, which agents previously did manually, and automatically tracks follow-up actions, such as callbacks.
“Those are all the things that happen now with AI to ensure that the customer experience is much more seamless, the resolution is faster, the summary is accurate, and the follow-ups are complete,” Bhattacharya said.
Did it work?
Bhattacharya said it’s too early to share data about how generative AI was improving Verizon’s business customer service. However, she told Business Insider that 80% of the time, Verizon expects agents to anticipate the reason for a customer’s call based on their history. With the help of AI, she added, agents are about 90% accurate in recommending a resolution.
Still, Verizon continues to refine the AI models based on feedback from customer-service agents, she said. Each new customer-service AI tool is rolled out as a controlled pilot first, in which about 10% of agents use it. Once positive results come in, larger groups of agents start to use it.
“It’s a continuum,” Bhattacharya said. The goal is to get to a “high-90s accuracy level,” she added.
She said generative AI reduces call-center challenges and improves productivity. It also helps new agents finish their training quicker.
What’s next?
Verizon continues to use AI across the business. In customer service, Bhattacharya said the company was on the “brink” of using the technology for hyperpersonalization.
That means offering highly curated products or services for each business customer based on the millions of data points it’s collected about their usage, geography, call history, and existing services — instead of making recommendations on broad demographics, she said.
“What generative AI will allow us to do is operate at scale but view each caller as a segment of one,” Bhattacharya said.
The goal is to use generative AI to make customer interactions as seamless as possible, she said. “Telecom is a complex business,” she added, “so everything we’re doing around AI is making everything simpler and more natural for our customers and internal employees.”
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