Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: It's always great to have the CEO of a company
Speaker 2: that you've been a customer of for like most of
Speaker 2: my adult life. So all my grievances, I'm just going
Speaker 2: to bring them to the to the to the to
Speaker 2: the table here in all seriousness, you've been CEO of
Speaker 2: Verizon since October, something of a homecoming for you, having
Speaker 2: having grown up at AT and T getting Virgin Mobile
Speaker 2: off the ground when it comes to running a wireless company,
Speaker 2: and you had that long interlude in the middle at PayPal.
Speaker 2: So we'll talk about that later. But what are the
Speaker 2: old rules no longer? Reply?
Speaker 1: Well, I think we live in a time right now
Speaker 1: of change that I've really never seen before. The pace
Speaker 1: of change is dramatic, I say, inside company right now,
Speaker 1: anytime the pace of change outside is greater than the
Speaker 1: pace of change inside, we're falling behind. And that's a
Speaker 1: that's a really high bar to get over. I think
Speaker 1: there's some similarities and some differences. I mean, way back
Speaker 1: when when I was at AT and T. You know,
Speaker 1: we're a big bureaucratic company. Verizon is a big bureaucratic company.
Speaker 1: It loves its processes, it loves to show its work,
Speaker 1: but like I'm about outcome and how fast can we
Speaker 1: move the company forward. We're very risk averse, and I
Speaker 1: get that, like there should be places where we are
Speaker 1: risk averse when it comes to cybersecurity, when it comes
Speaker 1: to the integrity of our financial numbers, Like, my tolerance
Speaker 1: for risk is like a one. But for the most part,
Speaker 1: my tolerance for risk for trying things and failing fast
Speaker 1: and then learning from it and moving forward is like
Speaker 1: an eight or nine. And I think in general the
Speaker 1: company's probably had a two to three. We're very hierarchical.
Speaker 1: I need to be very careful what I say, yeah,
Speaker 1: because it's taken as gospel, and the truth of the
Speaker 1: matter is things are changing so fast. Like yeah, I'm
Speaker 1: always learning. I can't predict the future. I can try
Speaker 1: and do my best to ascertain like the direction of it,
Speaker 1: but I'll frequently be wrong on that as well.
Speaker 2: It's still less than a year that you've been there.
Speaker 2: But how do you get from that? You said round
Speaker 2: two in those areas of eight areas where you want
Speaker 2: to see people take more risks, how do you get
Speaker 2: closer to that eight to nine level of tolerance?
Speaker 1: Well, I think you or I. I don't know if
Speaker 1: you would, but you know, I think leadership is like
Speaker 1: three things in my view. The first is to clearly
Speaker 1: define reality. And nobody really wants to hear that, to
Speaker 1: tell you, certainly. My first coming on stage in front
Speaker 1: of all the employees of Verizon, yeah, I had no slides,
Speaker 1: no nothing on screen, no talk track, just kind of
Speaker 1: like what I saw. And what I saw was a
Speaker 1: company that was losing in the market. We had lost
Speaker 1: market share for five straight years. We had gone from
Speaker 1: being number one in market cap to being last or
Speaker 1: forward P was last in the market and terrible, and
Speaker 1: so you know, I kind of laid that out for everybody,
Speaker 1: and I think we had just gotten used to gently
Speaker 1: seething market share. I suppose to playing to win. That
Speaker 1: just doesn't work for me. I mean, that's just not
Speaker 1: who I am. You know, when I first came in,
Speaker 1: I think people were scared because I said that, you know,
Speaker 1: we wanted to play to win. We wanted to stop
Speaker 1: losing market share and start gaining market share, and people
Speaker 1: were worried that was going to lead to, you know,
Speaker 1: a price war. But that's not the way that you compete,
Speaker 1: Like anybody can compete on price. Price is easy. It's
Speaker 1: about competing on other parts of the value proposition where
Speaker 1: you can actually differentiate yourself and create lasting value. Like
Speaker 1: if somebody puts some promotion out there, like I can
Speaker 1: match it now in two hours, so's there's no competitive
Speaker 1: advantage to that. So I think it's really about laying
Speaker 1: out the reality of where you are, and people don't
Speaker 1: want to be part of a losing team. And then
Speaker 1: the second thing a leader needs to do is inspire,
Speaker 1: lay out a vision of what you want to do.
Speaker 1: How are you going to reclaim your market leadership, and
Speaker 1: then clearly out the path between reality and that vision,
Speaker 1: and like how are we going to get there and
Speaker 1: over what time frame and what things are we going
Speaker 1: to chew off first and start to work on. So
Speaker 1: it is going probably faster than I imagine. I'm proud
Speaker 1: of the team. I don't like giving out compliments that easily,
Speaker 1: but I am proud of where they are. There's a
Speaker 1: lot more work to.
Speaker 2: Do, so you've talked about you've given hints on some
Speaker 2: of that work that you want to do. Moving away
Speaker 2: from low margin, highly promotional activity, simplify promotions, simplify plans,
Speaker 2: put some more flesh on those bones.
Speaker 1: For us, what does that look like? Well, I think
Speaker 1: at the end of the day, the reason people leave
Speaker 1: of Verizon is one when we price up with no
Speaker 1: incremental value, and we have done that for three years
Speaker 1: in a row. We have done something like thirty price
Speaker 1: ups with no incremental value, and that obviously distresses customers.
Speaker 1: And so we had started to see our churn go up,
Speaker 1: and I told the company, like, the first roll a
Speaker 1: rule of getting out of a hole is stop digging,
Speaker 1: and so we're just not going to raise prices without
Speaker 1: any corresponding value. And I'm beginning to see that as
Speaker 1: our churn starts to come down. The second is friction
Speaker 1: in the process. When you come into our store, How
Speaker 1: quickly can we help you when we sell you something?
Speaker 1: Is that reflected on your first bill? When you call
Speaker 1: in a customer service, you get somebody who's empathetic, does
Speaker 1: do what they see match with what you heard in
Speaker 1: the store and on your bill? And that's really really difficult.
Speaker 1: That's the end to end customer experience, and that's hundreds,
Speaker 1: if not thousands of things that you need to do better,
Speaker 1: and we are focused on every single one of those
Speaker 1: is incrementally getting better because I feel if we can
Speaker 1: have the best end to end customer experience, that's real
Speaker 1: differentiation because it's very hard to imitate and it's extremely
Speaker 1: hard to do, but extremely appreciated by customers.
Speaker 2: It's going to be hard for me, as a customer
Speaker 2: who's been with Verizon for a very long time, to
Speaker 2: notice even many incremental things. I might understand, Okay, yeah
Speaker 2: I do have a better but is it a better
Speaker 2: customer experience? But there's something concrete that I should look
Speaker 2: forward to to keep me from taking that offer from
Speaker 2: T Mobile or whatever.
Speaker 1: Yeah, there will be.
Speaker 2: Can you give us a little bit more of an indication? No,
Speaker 2: I want to be conscious for your point.
Speaker 1: I mean, I mean the answer still is no, I won't.
Speaker 1: But I think that when we talk about kind of
Speaker 1: this end to end value proposition, there are little things,
Speaker 1: there are bigger things, or how do you simplify things,
Speaker 1: how do you add elements of loyalty into what you're
Speaker 1: trying to go do? And so you know, my view
Speaker 1: is there's never a big bang in what you're going
Speaker 1: to do in front of customers, because if you can
Speaker 1: do a big bang, then your competitors can do a
Speaker 1: big bank. It's really it's unfortunately, it is like having
Speaker 1: a long term plan and every as I say inside
Speaker 1: the company, every single day matters, like I want to
Speaker 1: see incremental improvement every single day, and so learning to
Speaker 1: use the tools of our time, whether that be AI,
Speaker 1: and how we serve customers much better, whether it be
Speaker 1: specifical offers we put in front of you elements of
Speaker 1: the value proposition. So when you see things, expect that
Speaker 1: there will be other things a month from now, the
Speaker 1: next month, the month after, because it's got to be
Speaker 1: a steady drumbeat of improvements.
Speaker 2: When it comes to using encouraging your staff to use
Speaker 2: AI tools, what's your stature, what's your stance on that?
Speaker 2: And specifically, I think early on a lot of businesses
Speaker 2: were saying, hey, get out there, use as much as
Speaker 2: you want, create things, create chatbots, build agents. Have you
Speaker 2: had to become more disciplined about that? And what are
Speaker 2: your what are your marching orders when it comes to
Speaker 2: using AI tools to make either the workplace or the
Speaker 2: customer experience better.
Speaker 1: Well, I'm pretty outspoken on a as some of you
Speaker 1: may know, and I think as leaders of companies, I
Speaker 1: think we have a responsibility to talk about what could
Speaker 1: happen as a result of implementing AI. It's clear to
Speaker 1: me that whatever we have right now, these are the
Speaker 1: worst models that we will ever have in our lifetime.
Speaker 1: Because yeah, she knows it, like she'd be the first second. Yeah.
Speaker 1: Open AI is going to release four models, new models
Speaker 1: between now and the end of the year. Each one
Speaker 1: of them will be a step function improvement from where
Speaker 1: they are today. And so it's clear to me that
Speaker 1: AI will do at least three things inside the company.
Speaker 1: It will dramatically improve our productivity levels. It will dramatically
Speaker 1: improve our ability to satisfy customers. You know, in the
Speaker 1: last three months, we've been experimenting with agents that are
Speaker 1: replacing some of our customer service reps, and those agents
Speaker 1: their customer satisfaction rate is one thousand, two hundred and
Speaker 1: eighty basis points better than what we had before. Think
Speaker 1: about that, if it was fifty basis points, that'd be
Speaker 1: a big improvement. So our ability to satisfy customers, our
Speaker 1: ability to ingest all of the data around you. Like
Speaker 1: you may think of yourself as one customer, we think
Speaker 1: of you as kind of like the some total of
Speaker 1: who what lines you know, are under your account? Your
Speaker 1: kids aren't your account? Where do they call? How do
Speaker 1: you use it? Do you have a nest associated with
Speaker 1: your broadband service? And so we need to see all
Speaker 1: of that to be able to satisfy you. And then finally,
Speaker 1: AI is going to radically redefine our value proposition. I mean,
Speaker 1: my view of this is that we have an initiative
Speaker 1: inside the company called every Customer has a name, and
Speaker 1: that means every customer's individual. How we respond to you
Speaker 1: it should be empathetic, but every part of our value
Speaker 1: proposition should be tailored to the three hundred plus different
Speaker 1: ways that we can look at you and tailor or
Speaker 1: proposition to you.
Speaker 2: To what extent does AI just completely replace if they're
Speaker 2: so much better, To what extent does AI replete replace
Speaker 2: human customer service agents completely?
Speaker 1: For sure, you're going to see disruption in with AI
Speaker 1: in certain job functions. I don't see how that's not possible,
Speaker 1: And I don't see how anybody can look people in
Speaker 1: the eye and say that's not impossible.
Speaker 2: What percentage of customer service gets displaced?
Speaker 1: It can be a large percentage of customer service. I
Speaker 1: think that function, you know, is a function that has
Speaker 1: a lot of route parts of it. I forgot my
Speaker 1: past word. You know what's my billing amount? Those are
Speaker 1: all simple and easy things for an agent to go do.
Speaker 1: More complex things will be a combination of human and
Speaker 1: machines working together to satisfy what that doesn't mean like
Speaker 1: you will have functions that will be disrupted for sure,
Speaker 1: And I don't see how anyone again could say that
Speaker 1: they won't be, but you will have Like what we're
Speaker 1: seeing in our customer service right now is the road.
Speaker 1: Stuff can be done by agents more complex as a
Speaker 1: combination of an agent and a human working hand in
Speaker 1: hand to be able to satisfy that customer much better
Speaker 1: than either of them could do alone. And so I
Speaker 1: think you'll see all of those things happen. But I'm
Speaker 1: I'm going to lean heavy as I think all of
Speaker 1: my colleagues will, all the fortune one hundred will lean
Speaker 1: heavy on AI. You cannot be a part of this
Speaker 1: age without understanding the technological revolution. It'll be AI. I
Speaker 1: think personally we get to AGI, like some are saying
Speaker 1: before this now, but I think in the next two
Speaker 1: to four years we're in AGI. I think in the
Speaker 1: next four years we're at quantum. We're already preparing for
Speaker 1: Q day as there early as two years away, because
Speaker 1: we need to look at all the encryption pieces of this,
Speaker 1: and then you're at humanoid robotics, you know, a couple
Speaker 1: of years after that. That's all happening, and we need
Speaker 1: to be ready as a society, as leaders of corporations,
Speaker 1: and then we need to take the responsibility of that.
Speaker 1: So for instance, you know, I think I was one
Speaker 1: of the first to pull together a pretty wide scale
Speaker 1: We put aside twenty million dollars to train and reskill
Speaker 1: people that are impacted by AI. That's the tip of
Speaker 1: the iceberg for what we're going to go do. Like
Speaker 1: my view is, we have a responsibility to put serious money,
Speaker 1: resource and effort into training not just our employees, not
Speaker 1: just people that are impacted, but the communities we serve
Speaker 1: as well in utilizing AI in a responsible way. But
Speaker 1: as I say to everybody inside the company, you should
Speaker 1: not be scared of AI. You need to learn AI.
Speaker 1: You need to be able to use it in your work,
Speaker 1: you need to be able to use it in your
Speaker 1: personal life, because that's the age we live in.
Speaker 2: One of the first moves you made was a difficult move, admittedly,
Speaker 2: in eliminating a lot of jobs at Verizons to the
Speaker 2: tune of thirteen thousand, you set up this fun twenty million,
Speaker 2: you questioned, you said, that's just kind of the tip
Speaker 2: of the iceberg. What are some early like what are
Speaker 2: some of the early takeaways from that and what a
Speaker 2: companies need to do to reskill workers who are affected
Speaker 2: by you know, whether they're in customer service or some
Speaker 2: other area that's affected by AI.
Speaker 1: Yeah. Well, first of all, we're training everybody inside the corporation.
Speaker 1: We do week long events now and that can be
Speaker 1: from some people have don't even know you know, the
Speaker 1: right prompts to go use and how to use basic chatbots,
Speaker 1: two being able to gin up agents. You know, we
Speaker 1: have a whole AI tech stack that we are now implementing,
Speaker 1: most of which will be done next month in July,
Speaker 1: all of it finished by November. But you just you
Speaker 1: have to move quickly. You have to train. You know,
Speaker 1: we have seven thousand people in this reskilling that have
Speaker 1: already applied for that. But as I mentioned, I think
Speaker 1: our responsibility is to work with government. I'm spending a
Speaker 1: lot of time down in DC to think about how
Speaker 1: we take our resources, maybe the resources of fortune five
Speaker 1: hundred as well. Think about it, if we're putting fifty
Speaker 1: to one hundred million into it and you multiply that
Speaker 1: by you know, my peer set, and then what government
Speaker 1: can do. You can have a lot of money going
Speaker 1: into thinking about reskilling, retraining, and how to really utilize
Speaker 1: AI as hopefully a force that kind of unleash the
Speaker 1: best parts of humanity, as opposed to a force that
Speaker 1: you know, could add a lot of stress into our democracy.
Speaker 2: Speaking of powerful tools briefly in our last few seconds,
Speaker 2: i'd like you were at a time recently joined They
Speaker 2: don't even know that recently joined project Project glass Wing.
Speaker 2: Given your background in cybersecurity, give us a sense of
Speaker 2: now that you've had a chance to get in there
Speaker 2: and test it, how powerful is it?
Speaker 1: What does it do?
Speaker 2: Should we be afraid of it?
Speaker 1: Well, you should always be concerned about cybersecurity. I mean
Speaker 1: it is existential. Everything we do is controlled by software.
Speaker 1: You know, the elevators you go in, the planes that
Speaker 1: you uh, you know, board, your financials, everything that. I
Speaker 1: don't know how much money you have in your pocket
Speaker 1: right now, but you know it's probably not a lot.
Speaker 1: And all of your wealth is digital in some ways,
Speaker 1: so I think, and you know, a consumer has their
Speaker 1: identity stolen every two seconds, so I think cyber is
Speaker 1: existential for us. Mythos, which we've been working with as
Speaker 1: part of the Glass Wing, is a tool that can
Speaker 1: identify a lot of elements that might not have been
Speaker 1: seen as critical, but when you link them together, they
Speaker 1: become a critical infrastructure. I think that needs to be repaired.
Speaker 1: Mythos is very pow powerful. It's enabling us to identify
Speaker 1: vulnerabilities but also fix them quite quickly as well. But
Speaker 1: it's also forcing us to think about, you know, how
Speaker 1: we ingest third party vendors into our network, and how
Speaker 1: we everything needs to be patchable remotely, like within the
Speaker 1: next couple of months eighty five percent of everything done
Speaker 1: in our network. Instead of taking multiple hours or days
Speaker 1: to figure out what's going on, it'll we will identify
Speaker 1: it in minutes, go right to the element, and fix
Speaker 1: it autonomously. Lightning Round.
Speaker 2: If the government continues to designate Anthropic a national security threat,
Speaker 2: given its concerns about how its tools are used in defense,
Speaker 2: how problematic is that for you as a company.
Speaker 1: We have access to it, So I would say Mythos
Speaker 1: at a headstart, but all of these models catch up
Speaker 1: very quickly. I think open Aiyes model around cyber is
Speaker 1: extremely powerful as well. And as I mentioned, you know
Speaker 1: every two to four months, you know, these models double
Speaker 1: in strength and capacity. So I think Mythos was a
Speaker 1: real good look at what the capabilities of these models
Speaker 1: can do in specific functional areas. And I'm glad because
Speaker 1: we do a lot for the critical infrastructure of the
Speaker 1: United States and Mythos is going to help us protect it.