Verizon is harnessing the power of agentic and generative AI to elevate both customer experience and workforce productivity. In a discussion with Fierce Network’s Mitch Wagner, Latheef Syed, associate vice president for Data & AI at Verizon, explained that the company’s AI strategy centers on two goals—improving customer experience and empowering employees. Through autonomous agents and intelligent automation, Verizon is streamlining operations, providing quicker support, and helping teams make better, data-driven decisions.
A critical part of Verizon's success lies in building a strong governed Data & AI maturity landscape that can accelerate strategies and speed to market. Latheef emphasized that data governance builds and enables the trust and reliability needed to scale AI responsibly. Analytics, meanwhile, serves as the backbone of every AI initiative-ensuring agents have accurate, high-quality data to learn from and act on. From customer segmentation to network optimization, AI and analytics are helping Verizon tailor experiences and improve efficiency across its business units.
Looking ahead, Latheef sees AI and humans working side by side. “The future isn’t about replacing people,” he said. “It’s about coexistence—humans and agents collaborating to make smarter, faster decisions.” As Verizon continues to expand its AI initiatives, it’s also focusing on building literacy across the enterprise and fostering a culture of responsible innovation.
Mitch Wagner:
Welcome, everybody, and thank you for joining us today. I am Mitch Wagner from Fierce Network Research. I am chief analyst for AI, cloud, and data center technologies. I am here with Latheef Syed. He is associate vice president for data and analytics for Verizon. We're going to talk about AI, data analytics, and data governance. Welcome, Latheef.
Latheef Syed:
Thank you, Mitch. Really happy to be here. I'm glad that we are able to come in and talk to you all about a few things here. Really looking forward to it.
Mitch Wagner:
Great. So let's jump in. What are you seeing in terms of industry trends for agentic AI and generative AI? Where are we seeing early wins and opportunities?
Latheef Syed:
Very good question, Mitch. See, with the current landscape, what's going on in the industry, we are seeing a lot of companies are basically testing in the early stages of agentic AI, basically building autonomous agents, executing tasks that are basically doing reasoning, and responding to the questions or the queries the individuals have.
Where we are seeing the agents primarily going in is on the specialized, specific functions. Right? This is where things like fraud detection, customer support, automation, supply chain, all those things can play a critical part, and the industry is moving towards that in some of those companies as well. What I can say this is, even though there are different levels of maturity for different organizations, it's going to be very critical in the next couple of years how we basically bring all these foundational pieces together, allow the agents to be autonomous, make contextual decisions, reasoning, and also execute on some of the tasks that are critical to get the benefits from those functions as well.
Mitch Wagner:
Great. So could you describe how Verizon is implementing agentic AI and generative AI to generate strategic value?
Latheef Syed:
Absolutely. I mean, we have been on the agentic path for a while here. Our key priority is basically helping that can elevate the customer experience. At the same time, we always work on the customer-first approach. What it means is, from agentic AI and GenAI journey, what we can do to enable more in terms of our workforce productivity, helping the frontline in terms of doing a lot of things that can help the customer with the right answers, and also helping with the support use cases as well.
Our primary goal has been always how do we alleviate some of the pain that the customer has and also bring in a best-of experience in terms of addressing the customer needs through GenAI and agentic AI capabilities, especially when they are task-heavy in solving some of those challenges.
Mitch Wagner:
What does a company like Verizon need to do to prepare for agentic AI and generative AI? Are the biggest changes cultural? Are they technical? Are they strategic?
Latheef Syed:
It's a three-legged stool, I would say. Right? We have people, process, and performance/technology. From a people standpoint, it is a huge cultural shift, because we, as an organization, want everybody to be aware of what AI can do and what's the art of possible across the organization, and then comes all the other things in around how do we put the processes in place, build the right responsibility across, and also have a tooling and technology that can perform and scale accordingly.
So at Verizon, we are looking this in two different ways. One is having AI governance that is established across the enterprise so people are aware. The individual functional units are aware of what is the art of possible, and number two is running the literacy program so that we can build a community of practice across the enterprise where individuals can develop, use, and apply AI responsibly.
Mitch Wagner:
So how does data governance fit into Verizon's plans for rolling out agentic AI and GenAI?
Latheef Syed:
Yeah. It's a very critical thing in the industry if you look across. Right? There is so much information overload. At the same time, AI is in need of all this trusted data behind the scene with the right processes in place. With the governance, we are bringing trust, reliability, safety for rolling out critical use cases through AI, especially through GenAI and agentic AI.
As agents become more autonomous, it's going to be important that we govern all these things with the right guardrails and framework. We are investing heavily on the frameworks that can look at the risk, build trust, explainability, and also allowing security to be ingrained in the process so that agents can work with the responsibility of trust and more of a cadence coming across the board accordingly.
Mitch Wagner:
So how does analytics come into it? How does analytics make agentic AI and generative AI actually work in practice?
Latheef Syed:
Analytics is the cornerstone. No agentic AI or GenAI can be successful without analytics and having a reliable data. I mean, what I mean by that is, AI actually is useful as long as the data is good. So in order to have a better data, good data to make decisions, we have to have the right quality, trust, clean and also labeled data that can help.
For example, if you're rolling out agents for different programs or different functions, we have a way to measure how those agents are performing, how the data can feed back into the process through the human in the loop, and allow to build more and more analytics that are helping guiding the agents to do the right task with the right context. For example, GenAI marketing agents can be used for customer segmentation analytics to generate personalized campaigns. Rather than doing generic messages, they can build tailored messages for individual segments through the agentic AI process.
Mitch Wagner:
So from an operations point of view, where have you seen agentic systems deliver the quickest wins at Verizon, and how do you see that impact growing?
Latheef Syed:
There are a lot of areas. Looking at constantly the way to introduce agents is going to be critical, and we have done so in different areas. A primary area of focus has been around workforce productivity. The reason why I say that is, how do we look at what the agents are going to be doing, looking at a particular problem or process that has to be revamped?
And at the same time, taking that mundane, regular task that can be automated with the right processes in place is going to be critical. The other advantage we have is building that entire knowledge base across the enterprise. Through agents, we can start extracting the metadata. We can start extracting the business processes through the store of information.
It would help us to build the right context around the data and also build the next level of knowledge base that can help answer some of the business questions the customer care reps have, the network engineers have, or even, for that matter, the marketing and the other teams have as well. So it's important for organizations to have that continuity without losing a lot of subject matter expertise, and this is where the knowledge base can be helpful.
Mitch Wagner:
So let's look ahead to the future. What does the future hold? Where do we want to be compared with where we are today?
Latheef Syed:
Today, most of the organizations are doing more of a piloting around agentic AI and GenAI. Of course, there are different levels of organizations out there having their maturity. Running pilots is a very narrow intelligence. I call it ANI. It's artificial narrow intelligence. But we have to go beyond that in terms of doing AGI and ASI, which is the future as the industry is looking into.
We want to be in a place where agents can work together across departments, across business units, and not just in their own silos. And also looking at some of the promising things coming out in the industry, I'm seeing that end-to-end workflows will minimize human intervention, and the agents can be more direct in terms of engaging with business by building seamless integration to make decisions with the right context.
So with all this being said, future isn't about just replacing people. It's about coexistence with the humans and the agents in the loop and redefining the work. This is something I'm seeing. It's going to be very promising as we roll out our strategy and also building the creativity that handles AI responsibly.
Mitch Wagner:
And that's a wrap. Thanks, Latheef, and thanks to our audience for joining us today.
Latheef Syed:
Appreciate it, Mitch.