Think Bigger: Leading AI Transformation At Scale

[00:00:00] Tessa Burg: Hello, and welcome to another episode of Leader Generation, brought to you by Mod Op. I’m your host, Tessa Burg. And today I’m joined by Chris Colangelo. He’s the AI leader for the Verizon Business Group, and we’re gonna dive into how leaders create customer-centered innovation at scale. I’m very excited because we still hear from a lot of our clients they’re not sure where to start.

[00:00:21] Tessa Burg: They’re not sure what technology they should be buying versus developing themselves. And our conversation is gonna explore that AI transformation or any transformation that you’re doing isn’t really about the tech, it’s about the leadership challenges in front of you. So Chris, thanks so much for being here.

[00:00:41] Tessa Burg: I’m very excited to dive into this topic.

[00:00:44] Chris Colangelo: Yeah. Thanks for having me.

[00:00:46] Tessa Burg: So let’s start with the big idea. You’ve spent your career leading major digital transformations. Tell us a little bit about yourself and your background.

[00:00:55] Chris Colangelo: Yeah. So I actually grew up in our sales channel. So I started out selling, Verizon products and services, and really got into, the technology space, by helping one of my colleagues.

[00:01:06] Chris Colangelo: And I understood the way that they were approaching their job was suboptimal this example was the way that they were quoting out customers wasn’t right, and the tools that we had at the time were not adequate. And so it was really out of passion for helping kind of my fellow colleague that I really got into this space of moving into technology, building out new systems and tools.

[00:01:28] Chris Colangelo: From there was able to just kind of progress, into internal employee tools. Then I moved into, our digital channels. I ran multi-billion dollar, e-commerce space for Verizon for many years. And then as part of that, really moved into a lot of the AI technologies that we would do as part of our e-commerce platforms.

[00:01:46] Chris Colangelo: And that’s how I got into doing AI for Verizon today

[00:01:51] Tessa Burg: So even your early experience hits right on the topic. You’re helping someone out, helping to understand their challenge. But we see a lot of people whenever they’re, as you put it, like a suboptimal experience or could be better, they tend to just want to pick the next tech solution or say, “Well, we’ll just license this,” or, “Maybe this technology doesn’t work,” or, “Maybe that platform doesn’t work.”

[00:02:12] Tessa Burg: How do you pivot that conversation to first focus on what is the challenge that you’re trying to solve and move people from trying to, like, find that silver bullet application or piece of technology?

[00:02:23] Chris Colangelo: You know, I think it’s one of the things that’s interesting now. AI is really cool in that before your architecture decision was very expensive on…

[00:02:33] Chris Colangelo: not maybe large architecture is still very expensive, but if you… You know, what coding language you use or what method you use to build an application would matter quite a bit. Now, because you can refactor things so quickly, you know, that, that seems to be a cheaper decision. And so people are spending a little bit less time focusing in on, “Okay, how do I want to actually go about designing a particular solution?”

[00:02:56] Chris Colangelo: and more about, “Okay, what are we actually trying to solve to, to begin with?” And one of the challenges that we see is a is a really big challenge is, are you thinking big enough and are you trying to solve a problem? Or are you saying, “Okay, we have a new technology like AI, it can solve anything.”

[00:03:12] Chris Colangelo: And by and large it can be useful in almost all scenarios. But is it the largest problem that your customer has or that your employees have that you’re actually going after? And then is AI the right solution to bring to that?

[00:03:26] Tessa Burg: Yeah. You said something that really struck me, and it’s, are you thinking big enough?

[00:03:32] Tessa Burg: And that when people are under a lot of pressure or a process or a challenge seems highly complex, and you’ve led efforts that have reduced friction in highly complex B2B environments. How do you identify where to start in that process and what points of friction are worth starting to reduce and make more and add value to the process?

[00:04:01] Chris Colangelo: Yeah, it’s always tricky. I think to, to properly, like, reinvent a process, you typically

[00:04:09] Chris Colangelo: do need to understand it. The problem is the moment you go through and do the process mapping to understand the process, you have the tendency to want to iterate on it. And so I think, you know, some level of ignorance is useful into a process if you start to think through, You know, we do a little bit of, like, blue sky iteration thinking before we do the process mappings.

[00:04:31] Chris Colangelo: We come into some of these situations and say, “Okay, what would this function look like?” Before I actually fully understand it, before I do all the research, actually starting some of the ideation on, like, how would I do this fundamentally differently? And you know, for us you know, time can be, you know, one of those pieces, but there’s lots of different factors that can dramatically change a customer experience or an outcome.

[00:04:54] Chris Colangelo: And then you go through, okay, now that you’ve done some high-level thinking without knowing, you know, too much about a particular area, now you can go through, do the detailed process mapping, understand exactly how things work and that’ll help you with the gotchas where if you would just you know, come in with, you know, some brand-new idea, it’s like, okay, that’s not practical.

[00:05:11] Chris Colangelo: That’s not actually gonna work. And you kind of mesh the two together to get into a, you know, truly workable solution. But the big thing that we see is, like, in some processes, especially with AI now, you know, people will be talking about, okay, let’s do a twenty percent or a thirty percent improvement on a process, and we’re now looking at to say, “Why couldn’t this be ninety-five percent reduction?

[00:05:35] Chris Colangelo: Why couldn’t we have a process that takes a month and then have it be an hour?” And you really start to walk through that. You, you– in many situations, you realize, well, it is possible. We just don’t like it. It’s uncomfortable. All these different, you know, bureaucracies will have a problem with it.

[00:05:51] Chris Colangelo: But then you’re actually able to identify how much of that is true and unmovable. And then in, in some situations there– it is possible to have more compliance, more security, and still have this, like, infinite speed and scale. It just takes some careful consideration and a lot of partnership with those teams ’cause they’re typically not used to working in those environments where you look at, like, digital twins and things of that nature.

[00:06:17] Tessa Burg: So you’re making this sound easy, but having gone through this process, I know it’s really hard to get people to open up their minds to really think about what could this look like fundamentally differently. ‘Cause you’re, in a way, or not even in a way, but you’re asking them, you’re giving them a preview of the change to come.

[00:06:38] Tessa Burg: And change can be hard, and doing something different than how I do it today might be scary or because I do know every nuance of this process and I do know all the steps and I do know all the detail and I do know all the security, I know all of this, it’s really hard for me to get past that and say, like, “Well, this is what would have to be true in order to have it done in a day.”

[00:06:58] Tessa Burg: How do you create a culture and a space where people are able to stretch and not feel threatened or not feel resistant or ev- even just push themselves without that consequence that what they manage today isn’t gonna all fall apart?

[00:07:19] Chris Colangelo: So I think there’s a couple tracks with this, and I’ll start with the last thing you said in terms of the thing that you manage is not gonna fall apart.

[00:07:26] Chris Colangelo: Well, we try to tell people in many situations it will fall apart. You have to realize, like if you have something, a process that takes you three months to do today and we’re gonna turn it into an hour, like, you very quickly start to say, “Okay, what do I do now? What is my job?” Like that-

[00:07:42] Tessa Burg: Mm-hmm

[00:07:42] Chris Colangelo: becomes very concerning to people because obviously, like you can’t reduce that much time out of, you know, a process without having some disruption in labor. And so we spend a lot of time focusing on like what is the value that you as an individual bring to, to the organization. And so I try to tell people, like y- your job is to bring value.

[00:08:04] Chris Colangelo: Your job is not to be this system admin or to be this role that you’ve been doing for the last five years. Y- your talents are so much higher than the box that you’ve put yourself into. And I think, y- you know, if people can continue to produce value, they’re going to have successful careers.

[00:08:23] Chris Colangelo: It is when you hold on to old ways of working that are going away, you will go away with them. Like I-

[00:08:31] Tessa Burg: Mm-hmm

[00:08:31] Chris Colangelo: … I just think as an AI leader, that’s what we try to tell people. But what we also see is the, you know, humankind is very greedy in that we have already brought like this unbelievable technology for example, for business intelligence, where now we have AI that I can ask any question to, and it can run a full analysis that would’ve taken us months to do, and now we get it back in like 15, 20 minutes.

[00:08:56] Chris Colangelo: And so now it becomes, okay, well, what do those people do? But immediately now that I can get all this intelligence that I couldn’t get before, you’ve– you immediately uplevel the questions that you’re asking where… And it’s like how greedy. Like why aren’t you grateful for this, you know, you know, breadth of intelligence that I just gave you?

[00:09:14] Chris Colangelo: But that’s just not the way the human brain works. As soon as I give it to you, your brain starts firing again on, okay, well, what about this new like other thing? Ans- like how does it work between, you know, my acquisition channels, and then they’re calling in, and they’re onboarding experiences, and now people are thinking bigger and bolder things.

[00:09:31] Chris Colangelo: They’re asking much harder questions because you made, you know, easier questions just at the snap of a finger, and so that produces a ton of work, right? So that’s the- Mm-hmm … the kind of the good thing here is like, you know, the work is– we’ve never seen the work just go away. It just changes and it moves and it shifts into different areas.

[00:09:48] Chris Colangelo: But as this technology progresses, you know, the work just changes, and so you wanna make sure that you’re ready for that. Now, on the other side of your question you know, moving into, to organizations and cultures, what we found, believe it or not, is- the under-resourced groups are the easiest to drive these levels of transformation.

[00:10:14] Chris Colangelo: The teams that are really just tapped out, they’re stre- they’re just, they’re stretched super thin. They’re just like, “I want help,” and they’re kind of ready for it. Where we try to be a little bit you know, careful and it’s harder is when you have really high-budget teams, really well-resourced teams, high levels of bureaucracy inside the team ’cause they have enough kind of budget and infrastructure for that.

[00:10:36] Chris Colangelo: Those are the teams that I think get really worried, and it’s actually much harder to kind of get that through. And so one of the things that we look at is, like, where can I find wins and get momentum and find kind of willing thought partners that kind of, can kind of lean in because they want to make this progress and to them, there is no other way, right?

[00:10:55] Chris Colangelo: You’re, you’re-

[00:10:55] Tessa Burg: Right

[00:10:56] Chris Colangelo: … you’re bringing a cavalry. They’re not looking at it as a threat, they’re looking at it as a lifeline. And we build momentum there. And then the other groups I think look at that and say, “Okay, wait a second. This … it feels like I’m missing out,” and then they kind of jump on, on board.

[00:11:09] Chris Colangelo: But that’s what, you know … we do both. We deploy obviously in multiple areas but we tend to see, you know, a lot of traction in these kind of under-resourced areas or recently impact areas where they’re they have very legitimate problems that they’re trying to solve. And so again, you’re not just coming in and saying, “I have AI, how can I help?”

[00:11:27] Chris Colangelo: It’s they’re saying, “I need to get this done,” and AI happens to be a viable solution.

[00:11:33] Tessa Burg: Yeah. I love both of those points, and they hit on keeping the human value, but then also as part of that solution, you’re– they’re a part of where does the human value need to fall so that what we’re producing, the work that we’re doing, the process gets, one, training.

[00:11:53] Tessa Burg: Like, we’re gonna have to let other people know that we’re doing this. We’re going to have new ways of auditing and measuring. How do you start to break apart new processes or break apart things that you want to scale and help design those systems for keeping a human in the loop? And what does that look like?

[00:12:12] Tessa Burg: ‘Cause I was– So I was doing this commodity work. I’ve leaned in on my thought leader. I understand my value. And then how do you bring them along to that new value, and especially that new value at scale, where you have to start to democratize what that new process and what those new deliverables or outputs are?

[00:12:27] Chris Colangelo: Well, y- so I think that y- y– I don’t want to boil this all down to just say it’s just human in the loop running the AI because, like I said, what we see is an actual elevation of, like, creativity and thought and process outside of the human in the loop. The human in the loop in some ways can be temporary, meaning I’ve got an AI, you know, process that is using a human to validate that it’s doing everything correctly.

[00:12:53] Chris Colangelo: But in most situations, the goal is to remove that human in the loop to let it run, right? Not that you’ll never have guardrails or audits or whatever it may be, but you’re really trying to get your AI to a, certain threshold where you say, “Okay, hey, ninety-five percent of the time I’m just approving this thing.”

[00:13:07] Chris Colangelo: So then you just say, “Okay let’s let this workflow just kind of run on itself.” So even the human in the loop eventually i- in some situations can get removed, in some situations it can’t. But it’s, you know, moving people into, like, these higher functions where now they’re solving new problems in terms of you know, how do I better the customer experience?

[00:13:26] Chris Colangelo: There’s some new roles that have come out of AI. You know, so those are all the different pieces that we have. But I think you mentioned this piece of, like, Scale and where, you know, how do we engineer, you know, these different processes? For us it’s, you know, and I’ll take marketing for an example.

[00:13:39] Chris Colangelo: So we have a very robust marketing AI transformation, and the first thing we did was we said, “Okay, we are going to be able to do AI-generated campaigns, audiencing, briefing optimization,” you know, all these different types of things. But what you find from that is if I could take the process of taking the idea and working it through and reduce it from three months to an hour, the number of ideas radically changes.

[00:14:12] Chris Colangelo: The quality of the creative radically changes. And better yet for us, what we’ve done is i- in many situations people are planning to do work that would fail, but they don’t know it because we’re not connected enough across our processes. And so we start to look at it now to say, “Okay, I’m going to simulate your campaign for you and tell you exactly what the yield would be based on all these historical factors what your current campaign looks like versus the past campaigns.”

[00:14:39] Chris Colangelo: It may be an overperformance, but I could tell you basic yield, and it’s, that drives better conversations inside of the firm because you say, “Well, my target’s 10 times that.” So now you have to re-engineer your whole thing to… and again, so it’s like what is the value that they’re providing? It’s like they have to solve a new problem, which is our old way of working was gonna get me to 10% of the results that we actually need.

[00:15:02] Chris Colangelo: I have to think completely differently, a new approach, because the old playbook for whatever I’m trying to do here would not work at all. But they’re not learning that in post. They’re learning it-

[00:15:11] Tessa Burg: Right

[00:15:11] Chris Colangelo: … in the planning which in most marketing teams I, I think that’s not happening where you’re getting this, like, really good clarity that…

[00:15:18] Chris Colangelo: Because again, it’s too much work, like the sunk cost is too high, so you end up, you know, if you’re, you know, three months into, you know, a body of work, you’re probably just gonna launch it. You’re not gonna rip the plug at the last minute ’cause you’re still getting some yield. It’s just not enough to get you to your eventual targets.

[00:15:34] Tessa Burg: Yeah. What I like about that example is you shared there’s a tool that they’re using to pre-test or pre-evaluate the creative, but they’ve always wanted to do that. So it was easy enough for them to understand how to use it immediately. You didn’t have to spend a lot of time on the training because it, who do- who hasn’t wanted to do that?

[00:15:55] Tessa Burg: Who hasn’t wanted to know the results of a campaign before it launches? But it’s not that they even moved roles. Like I th- there’s a lot of conversation around, well, what is the, you know, marketing roles of the future gonna be? They’re in the same seat. They are just evolving. Like to your point, their thinking is just evolving, but it’s not like you had to formally give them the new role, give them a new title, train them on the new skill sets to do this.

[00:16:21] Tessa Burg: What you did was give them a solution that solved a problem they’ve always had. It answered questions they’ve always been asking and always wanted to have answered. It reduced the time between steps to have to connect to different data, get, pull a bunch of different things. They do it manually to get your best guess, but still that takes months of gathering data.

[00:16:43] Tessa Burg: So they have always wanted this. You just expedited the delivery of value to a challenge, and then they evolved the role. You didn’t- Right … set a new role goal. I think that’s a big… I repeated it back because I don’t think there are many, especially marketers, who understand that or have had that experience, and it is also not the normal steps of a digital transformation project.

[00:17:14] Tessa Burg: You don’t go into a digital transformation knowing that people are going to evolve because they’re working differently. You typically need to be much more intentional and have these gates. And so I just found that, like, really your answer is very insightful, and I don’t think a lot of … I think people kind of have to free themselves up or start with that, again, solving the bigger problem.

[00:17:36] Tessa Burg: What have they always wanted to do? Where are we having the most stress and tension? And the roles of the future will emerge from there.

[00:17:45] Chris Colangelo: Yeah. Yeah. Absolutely.

[00:17:48] Tessa Burg: So when you look ahead at, like, the next two to three years, what is keeping your challenges pipeline full, and what are you excited to sort of solve and scale next?

[00:18:03] Chris Colangelo: Anything two to three years is highly unpredictable in the current world that we’re in, so I feel like it’s an unfair question. The… Yeah, look, I think the challenges are more or less the same. It’s interesting- I believe that marketing is gonna see the shift of personalization and customer experience really coming together.

[00:18:30] Chris Colangelo: In, in that… And you see this all the time, where if you go and you watch a personalized TV or ad or whatever, you see a, you know, commercial for, like, joint pain or something like that, and some pharmaceutical drug. And you’re like, “This doesn’t apply to me.” Like, I would much rather watch something else.

[00:18:47] Chris Colangelo: And I think that there’s just gonna be a bigger and bigger shift to say, like, we owe it to our customers to provide them one-to-one personalized content-

…

[00:18:57] Chris Colangelo: Not because it converts better. Like, I think we think of that. And obviously we want it to convert better. But because we can do a better job of educating our customers on the industry that they’re in, opening the aperture of the solutions or the risks that apply to their businesses that we are uniquely positioned to give them.

[00:19:15] Chris Colangelo: And by talking to them in a, this very personalized way, I actually think it’s just a better customer experience. Another part of this is we have some unbelievable AI that we… We’re able to tell sales reps live on a call like this what they should be saying, you know, in a given interaction.

[00:19:31] Chris Colangelo: And we were listening to a call where the AI had told the sales rep what to say. They didn’t really hit it directly, but they were close enough, and then the customer actually brought the exact product that, that the sales rep was supposed to talk to them about. The in… It wasn’t just the product, it was the product and the use case, right?

[00:19:50] Chris Colangelo: So the- they mentioned the right product, but not the use case the customer wanted. The use case wasn’t a good fit. The AI nailed it, and the customer actually said, “Is it, you know, this use case?” And then the sales rep kind of agreed. And it was so crazy ’cause the sales rep, you know, takes a picture and you know, sends it to us and say, “Oh, my God, this AI is incredible.”

[00:20:06] Chris Colangelo: But from that, while we’re listening to that recording, we said, “Wait, this customer just told us this other use case that he pitched is not a good fit for them.”

[00:20:13] Chris Colangelo: And you’re sitting there going, “How do I make sure that we never pitch it to them again?” Because we know that this is not it’s not a good solution.

[00:20:22] Chris Colangelo: ‘Cause they very clearly articulated we agree with that rationale, that, like, not every product is the right solution for every use case. And so to me, that’s what, like, personalized marketing really looks like, is it’s we’re really listening. And so-

[00:20:35] Tessa Burg: Mm-hmm

[00:20:35] Chris Colangelo: … you know, yeah, we’re gonna pitch different products, we’re gonna pay attention to conversion rates, but we’re gonna look as much at the rejection from a customer experience lens than just to say, “Okay, I’m gonna run a campaign, and I get 3%, so then I’ll run another campaign and I get 3%.”

[00:20:48] Chris Colangelo: ‘Cause, you know, the marketer, you know, and some of the exact product that you’re just looking to say, “Well, it all adds up, and so I’m getting to my targets.” But there’s a- But all the non-converts-

[00:20:57] Tessa Burg: Right …

[00:20:58] Chris Colangelo: it’s frustrating for the customer.

[00:21:00] Tessa Burg: Mm-hmm.

[00:21:00] Chris Colangelo: And so we’re gonna try, we’re gonna get a lot closer on, you know, less volume, higher quality and really in a way that services the customer is kind of how we think about it across all of our channels.

[00:21:11] Chris Colangelo: We really want our marketing and what we’re telling our salespeople, all of that to be completely in sync. And we’re gonna be listening across all touch points on rejections for the purposes of customer experience. You know?

[00:21:23] Tessa Burg: Yeah. I love that. I used to tell my teams when we would look at campaign optimization, website optimization, anything we were trying to optimize, instead of the marketers would walk in, they’re like, “We get 6, 10%, 12% conversion.

[00:21:37] Tessa Burg: We’re amazing.” I’m like, what’s going on with the 90% of the people that are upset?” And when you flip it that way, it does open up more creative problem-solving, and it- you wanna dig deeper into who are those people? What were their needs?

[00:21:50] Tessa Burg: Was it the wrong time? Was it the wrong message? Kind of getting back to an earlier point, you start to identify what the real big problems are and broaden the thinking instead of getting down and doing things iteratively. Okay, we got from 6%-

[00:22:05] Chris Colangelo: Yeah

[00:22:05] Tessa Burg: … to 10, to 12, to 14, and it has a much bigger impact.

[00:22:10] Tessa Burg: So I love that you’re doing that. You’re-

[00:22:13] Chris Colangelo: Well, and, and-

[00:22:13] Tessa Burg: Okay

[00:22:14] Chris Colangelo: … some of the stuff too, it’s like it, it’s more possible than ever before. So we have AI-generated calling campaigns. They perform three times higher than traditional campaigns. And what’s crazy about that is we’re meeting with the team to say we’re pretty confident I can double conversion rate and cut the volume, and I could probably do it again.”

[00:22:34] Chris Colangelo: And so, so that’s where we’re just kind of in a new era that it, it becomes, like, highly possible to just nail it, to say, like, you, you know… and it’s weird because you’re just, you’re shrinking volume and shrinking volume, and you lose a little bit of that conversion, right? So getting that max potential is always a little bit of a challenge.

[00:22:52] Chris Colangelo: But the tech has moved in such a way that it becomes much more possible than ever before to continually double conversion rate and cut the volume. And we’ll continue to do that.

[00:23:01] Tessa Burg: Yeah. Yeah. I agree. We’re almost at time, but I had a last, very important question. Because we’ve covered a lot of things that digital transformation leaders should be doing, lots of rich nuggets of wisdom, but what are some things you would tell leaders to stop doing as they look to continue to find ways where AI can bring value to their internal processes and to their external customer value?

[00:23:31] Chris Colangelo: AI is an amazing tool. It is not the solution for everything. So I would be careful to try to apply AI to all processes. A lot of times you actually just have old systems, tech debt, things that you need to clean up, and pretending like you could just throw AI on top of it is not a good recipe. Now, there’s caveats to that in that AI is unbelievably good at helping you do old, boring traditional work, your data engineering combing through legacy monolithic applications, process mapping, all that.

[00:24:14] Chris Colangelo: So you could still move that work way faster using AI. But I’d be very careful to just try to apply AI on top if you have a really bad foundation not just with data, but even with the systems, because you’re gonna need … your AI will need API calls to do work. And so if you don’t have good plumbing for these things, if you don’t have good federated data, whatever it may be you’re gonna have a hard time.

[00:24:36] Chris Colangelo: And the problem with the modern AI is it can work around a lot of these things. It’ll slap an RPA on there, no problem. Like, oh, we can use computer use on there. But you want to be careful because just because you can doesn’t mean you should. I would watch out for that.

[00:24:51] Tessa Burg: I love it. Well, Chris, thanks so much for joining us today.

[00:24:54] Tessa Burg: It was an amazing episode. If listeners have questions or want to reach you, where can they find you?

[00:25:01] Chris Colangelo: LinkedIn would be the best place. Yeah.

[00:25:02] Tessa Burg: Fantastic. And you’ll be able to access Chris’s LinkedIn profile on our website with the episode. For all of our episodes, you can visit modop.com, M-O-D-O-P.com/podcast, or just search Leader Generation wherever you listen to podcasts.

[00:25:20] Tessa Burg: And until next time, Chris, I’m sure we’ll be catching up again soon. Thanks for joining us.

[00:25:24] Chris Colangelo: Thanks for having me.