Welcome And Why AI Matters

Jeannie Walters 0:10

It's time for CX Pulse Check, where I invite a special co-host who helps me break down the current events in customer experience so that we can all learn from one another. And I am so excited about my co-host this month because I've known Brandon for a long time. We have been part of a group that focuses on AI in customer experience. So I bet you can guess some of the things we're going to talk about today. But Brandon McGovern is the head of customer experience at HP, and he's here with us today. Hi, Brandon.

Brandon McGovern 0:44

Hi, hi. I'm so excited to be here and chat with you today.

Jeannie Walters 0:48

Well, I'm excited you're here too. We've talked about this for a while. So I'm glad that we made it happen.

Brandon McGovern 0:53

Yes, absolutely.

Jeannie Walters 0:54

I would love for you to share a little bit about what you do at HP and why this topic is so near and dear to your heart.

Brandon McGovern 1:03

Yeah. So I, as you said, I work at HP. I've been with HP for about 16 years. And a lot of that time has been spent managing customer experience. It's looking after understanding insights, understanding sentiment of our customers and driving that into every business and every function within the organization so that we can improve the experiences that we're delivering. And of course, like everybody else in the past year or plus, we have been really actively looking and testing AI and understanding how AI fits within the CX world and where the applications are and how we can do better with it. So this combination of uh of two topics are super passionate to me. And I know that we've we've talked about it in the past, and so I'm ready to dive in.

Jeannie Walters 1:50

Awesome. Well, it's been it's been really cool to see how you've applied it. And I think as a leader, um, a lot of people should be inspired because you've tried things too. Sometimes you just have to pilot things. We talk about this a lot when we talk about AI, right? Like we need to just try things out and move through and see what works and keep figuring out the parts that we don't even know what we don't know yet.

Brandon McGovern 2:14

Absolutely.

Jeannie Walters 2:15

So yeah, it's been it's been really cool for for me to see that with you. And I think, you know, as we kind of evolve as a society around AI, one of the things that I'm seeing is that we're figuring out not only that we need those guardrails, but like what some of those guardrails should be. And as we talk about some of the topics today, I would love to challenge the people who are watching or listening to this who are leaders themselves, think about what are some of the lessons you can take back to your organization and how can you really lead? Because I think customer experience leaders have a unique perspective right now, where we are seeing how customers are interacting with this technology, how they are, how their expectations might be changing. We're seeing the pressure from leaders or others in the organization. I've heard some crazy goals like you must use 25% of your job must be AI, which is a very odd thing to say, I think. Um, and then there are other, you know, pressures around how do we make sure we're more efficient? How do we make sure we're doing all these things? But if we don't marry that with what we want to do for the customers and defining what they're really expecting and relying on that data and those insights you talked about, then I think we're missing a really important part of the puzzle when it comes to integrating AI into organizational structure. So

Brandon McGovern 3:52

What you said is so true. So yes,

Norse Atlantic And Automation Backlash

Brandon McGovern 3:55

we could rip on that for a long time.

Jeannie Walters 3:56

We we probably could. So, well, let's dive in. We've got a couple of great articles to cover today. And the first one is about an airline. You may be expecting that we're going to talk about Spirit Airlines because they've been in the news because of their closure and bankruptcy and all of that. But we're actually talking about Norse Atlantic, which isn't something that comes up a lot when I'm, you know, flying American Airlines all the time. But the the this is from Wired magazine, and the headline is Norse Atlantic Airways Offers Dirt Cheap Tickets. There's a Catch. And the catch is essentially that they put so much of their customer service operations into technology and removed the humans that a lot of customers started complaining. Um, now the Federal Trade Commission is getting involved and some others because they felt like there was no way to actually access the service that they needed. That's oversimplifying this a bit. But I'm curious what you thought of this and some of the takeaways that you had.

Brandon McGovern 5:08

Yeah, this is so interesting. And frankly, I it's it's not really a new problem, but as you read through the article, it's almost a problem that's getting even more attention because of AI. Um, I don't see this as a tech failure. I see it as a governance failure and a management failure and a leadership failure.

Jeannie Walters 5:25

Yes. I wish I had one of those sound effects so I could be like woo.

Brandon McGovern 5:27

I mean, so clearly what you can imagine within this company, and of course I don't work there and I don't know, but that they had a mandate and they jumped very quickly and very deeply into applying new technology before they validated use cases in order to scale it. And what they would have found, I'm certain of, is that there are some use cases that can be automated and some use cases that can't.

Jeannie Walters 5:55

Yes.

Brandon McGovern 5:56

And typically those very highly emotional use cases, you don't want to put a robot in between. You need that human connection, you need that emotional connection.

Jeannie Walters 6:06

Yeah.

Brandon McGovern 6:07

And this is not, as I said, it's not a new pattern. We we saw digital transformation, push to self-service. We saw companies remove phone numbers years ago as the digital transformation started. But I believe AI has now made it easier to just scale and also bringing more visibility just because everyone's talking AI. Um, it actually, you know, it can cause more damage. And I mean, there was a lot of customers here who were really impacted.

Jeannie Walters 6:35

Yes, really impacted both emotionally and financially, right? Like that was the thing that I picked up on as well. And I think that when you talk about like how we turned off uh phone numbers for digital transformation, one of the questions I always have is the leaders who are making these decisions, and when they don't change it fast enough, like that that was one of the problems I saw here was that there were problems that were well identified, and for some reason nothing was changing for a long time. And my thought is, what are they tracking? Because if they're tracking something like, well, we're more operationally efficient and they're thinking, you know, high fives, everybody, we nailed it. This AI thing is great. Um, that is a different story than what the customers are actually experiencing. And this is kind of the crux of what we do. We see a lot of internal processes that look like they're working, but if you're not paying attention to the actual customer experience. And to your point, if you don't have that governance around how we use these tools, then it's it's easier to miss than we think, even when there are patterns.

Brandon McGovern 7:51

And let me tell you, it's hard to claw back once you make these really rough, tough decisions.

Jeannie Walters 7:55

Yeah.

Brandon McGovern 7:56

Um, because they have very serious financial consequences. No, they also have financial consequences to the customers. So um once you start going down the path, I know it's hard to reverse. That said, it doesn't give you an excuse not to. And I think I think, as we said, having the right governance in place so that you can test new solutions, you know where they fit, and then you know where they don't fit is is really critical here. I I don't I wouldn't fault Norse for testing new things. The problem is they did it with brute force.

Jeannie Walters 8:28

Yeah.

Brandon McGovern 8:29

And they didn't allow an escape hatch for customers who needed it when they needed it.

Jeannie Walters 8:33

Right.

Brandon McGovern 8:34

And and that's a recipe for disaster because once something, once a critical event happens, which is what happened here, um, where a lot of people needed to call in and couldn't, it it opened the door for fraud, it opened the door for a lot of other problems that honestly they probably didn't predict in uh early on, but they could have avoided if they were a little more surgical in the way that they approached the problem.

Jeannie Walters 8:58

Yeah, I totally agree. And I think that when we look at the example of Spirit Airlines too, like they kind of claimed that everything was the oil prices and things out of their control. But I just had a white paper published with Thematic at we discovered that if you looked at actual app user reviews of airlines, that told a totally different story where they were saying, like, I used to like this airline, now I don't. I'm not getting the value. They were defining value differently. And so I think that when we think about what are those indicators, how do we know we we have to broaden our perspective too and make sure that we are meeting customers where they are and not putting our head in the sand because you know what? The process looks great. So I think that's amplifying everything with AI.

Brandon McGovern 9:57

I'll also tell you, as CX practitioners, we tend to look at the surveys that we send and noting, you know, or the feedback that we're getting in different ways. And we should always remember that that's only customers who have made it through our processes or that are our customers today. And looking at those broader signals helps us understand the broader sentiment that the industry or that the market or that people who aren't quite your customers yet have about the really good early morning signals.

Jeannie Walters 10:27

It's really also, I think, important to remember

Metrics That Hide Real Customer Pain

Jeannie Walters 10:30

that when we can find those public signals, so can prospective customers, so can investors. So, you know, like they see those things.

Brandon McGovern 10:38

So can competitors,

Jeannie Walters 10:39

and so can your competitors, exactly right, exactly right. So um, and if you're savvy, you notice your competitor gaps and you go, hey, I've got an idea.

Brandon McGovern 10:48

Yeah, opportunities. They can be rich.

Jeannie Walters 10:50

Yeah, that's right, that's right. So so airlines, of course, big topic of discussion because we all fly, and every everybody's kind of involved with that right now.

Cisco And The Pain Of Adoption

Jeannie Walters 11:04

Another thing that I'm watching, and I think everybody else is watching too, is there's so much big tech right now, and there's so much discussion about big tech and how we can like fit AI into different workflows with that, and every and now there's kind of an AI race going on and all of these things. So Cisco, which is not a small company, they started organizing and implementing around AI. And this is from Business Insider, and the headline is Cisco Exec Says Adopting AI is Like Surgery Without the Drugs. And that just struck me as like as we're having all these big discussions about the potential of AI and all the amazing things and the possibilities that it can do for humans. This was a pretty raw and honest headline or quote, I thought, from one of the execs. So when you think about the potential of it, and when you compare it to this headline and what Cisco was saying about it, which was essentially we were amplifying some of our mistakes, uh, the things going wrong just got amplified. Um, how you know you're in a large company? How do you balance all of that? What should people be looking for?

Brandon McGovern 12:23

Yeah, I is this first of all, props to Cisco for admitting a problem that we probably have all had.

Jeannie Walters 12:29

Yes.

Brandon McGovern 12:29

Um, and as we're trying to run and adopt AI, many, many teams are getting that mandate. You must be 25% AI or whatever it might be, right? There, we're getting it shoved into our face. And we need, um, and so some people are reacting, and some teams are reacting. It's very natural to do that. I think the bottom line, and the thing that we've learned is that you have to stay focused on what are the outcomes that we're really trying to drive, and then we have to validate before we can scale. And and we've had a couple of different um initiatives where we've tried to automate tasks instead of automate outcomes. Um, and typically when we start looking at those at that task level, that's when you're really possibly at a too granular of a level. Because AI gives us the opportunity to rethink the way that we work. And if you look at what are the outputs that you need and what are the inputs that you have, and then go and redesign that um that overall workflow that AI kind of helps you advance, then then then you can really unlock more than just taking it step by step. Now, yeah, I don't put fault on them, actually, because I think we've all tried starting at micro steps and then working our way out. But really, I think that the biggest unlock is to start um at the broader process and figure out how AI can help you advance it.

Jeannie Walters 13:59

And I think, you know, saying that you need to figure out how AI can help you is also really important because if we're using AI for AI's sake, we're not going to actually improve the experience. We're not going to deliver on the KPIs that are important. We're not like we have to start just like any other business decision, you have to start with, first of all, will this represent us in the way that we want? Will it actually deliver on who we are? And then what about delivering on those outcomes we need? What are our shareholders expecting? What are our is our board expecting? All of those things. Because if you if you kind of skip those steps and just start, and I think that's to your point, what a lot of us did, because that's kind of what we were told to do. Nobody had their full arms around the the power of it, I think. And even in my little personal use, I mean, you you start using it more frequently, and all of a sudden you're like, wait, so I have a chat over here and a project over there, and I've got this and that. And if you don't have that structure around it, then it's really easy to kind of get lost in the weeds and not even remember why you're tying it all together in the first place.

Brandon McGovern 15:17

When we first were introduced with AI, it was like now everything can be faster.

Jeannie Walters 15:22

Yeah.

Brandon McGovern 15:23

And I think that was the wrong mindset.

Stop Chasing Speed Start Chasing Possibility

Jeannie Walters 15:25

Yeah.

Brandon McGovern 15:25

And one of the things that I've been pushing, it's not about being fast, it's about what is possible now? That's the question we should be asking. Not how can we be faster, but what is now possible. And I think starting with productivity as a success metric is can be damaging because productivity is just about speed and efficiency, but it's not really necessarily about whether or not you solve the problem. I think back to market research, jobs to be done. What are those jobs that we're trying to do, and how do we re-engineer with AI as a tool that helps us get to those, as opposed to keeping doing the same thing just a little bit faster?

Jeannie Walters 16:03

Yeah, exactly. And I think the other thing that is really interesting, and the article hit on this, and you hit on this, with instead of being task focused, we really have to think of workflows. And I want to give credit where credit is due here. So I hope I'm remembering this correctly. Um, but I believe I heard this on the podcast Hard Fork, which is a New York Times technology discussion. And one of the things that they highlighted was like, if you look at the history of email, not everybody was like, oh, cool, email right away. That's not what happened. It didn't really take off until larger organizations started realizing, you know what, these executives don't need to, you know, print out everything and do it by hand and have their secretary type it up again, like this we can do better. And it wasn't until it was really like almost forced into the leadership workflows when it became universal and ubiquitous. And so that was a small change in some ways for many of us, but it was a dramatic change for people who had been doing things a certain way for decades. And I think we're going to see that same kind of acceleration once it becomes just, oh, everybody uses AI this way. Because right now we're all experimenting, we're all piloting, we're all figuring it out. And I do think that your point about not focusing on speed and productivity is really, really important because, you know, one of the things I talk about and I wrote about in my book is that we have to have that North Star of what is the experience we really want for our customers and who are we no matter what. And if you are on the inside of the organization talking about customers like their cost center or their problem, that will get amplified with AI, even if you don't think it will, like all of that stuff comes out. So it's really important right now to know who you are and to know what you're trying to deliver before you amplify it. And if you are, you know, walking the talk, I think that's going to show up. I think people will start realizing like the organizations who are using this well are actually the organizations who already are authentic, who already have integrity, all those things, because that's what people are craving now, too, is that authenticity.

Brandon McGovern 18:43

I very resonant. I you said it very well. I think, I think um, especially as as consumers, we get more comfortable with engaging with AI. Um, I think I think expecting being able to read between what the AI is saying and what the company is intending. I I think people are getting smart about that. Yeah. And we're only we're only going to get smarter because everybody's using it in their day-to-day job or lives, yeah, um, in addition to their jobs. So you know, the the familiarity is growing very rapidly. Um so yes, I I think I think authenticity is going to become a very important piece.

Jeannie Walters 19:26

And

Customers Now Read The Fine Print

Jeannie Walters 19:27

uh a small example of that, which is probably for another podcast, but um, you know, I've been thinking like there is no fine print anymore. Right. So if somebody is questioning, do I have a warranty? Is this fair? How do I get my money back? Um, they have the same information that the company does now. And so I think we have to be prepared for customers now to be much savvier about the fine print and just assume there is no fine print because the whole idea of fine print is we're gonna, you know, say a bunch of gobbledygook, nobody's gonna read it, and we'll go on and use it when we only need to. And now customers will have that information.

Brandon McGovern 20:16

I mean, there's a lot of legalese in there, right? And yeah, and and it might be necessary for some of it. Sure. But um, but you're right. We're gonna AI can help you parse through that pretty quickly and take out the things that matter the most. I think that's a really insightful um uh thought there, uh, like it's of how things change with with AI. I hadn't thought about that fine print piece.

Jeannie Walters 20:38

Yeah, it's it's I think it's coming. I think people are gonna get savvier and savvier about it. So we have to start thinking about customer support differently too, and like how do we react when somebody maybe got the wrong information or all of that too? So big huge, like I said, another podcast. But this is what we do, we riff. So um, well, we are, you know, I I love all of these discussions because they're so rich. And I think one of the things that we're in a space and time right now that is the beginning of the marathon of all this, right? Like we are learning as we go. And I think that in 20 years, like we might look back on this conversation and it will be like that horrible clip from the 90s where you know Katie Curick is like, what is internet? Um and we'll laugh about it, but we don't know what yet is coming, but at the same time we know that we have to adjust and continue to kind of model things out and figure out in real time with our customers. And so uh this next article I thought was interesting because it's about how some organizations are already starting to consider adjusting the course.

Why Many AI Rollouts Disappoint

Jeannie Walters 21:58

So this one is from The Register, I never know where I'm gonna find things. The Register, and the headline is Dissatisfied: Three-fourths of AI Customer Service Rollouts are a Letdown. Now, obviously, that's pretty dramatic. And I would say that some of them probably wouldn't say it exactly like that. But I think this process that we're in, it's kind of the messy middle where we're learning as we go and we do have to make adjustments sometimes. And that might mean even pausing something before we get it right or saying we're not going to do this for a while. There is all sorts of data out there about how customers feel about AI. And frankly, I don't trust much of it because it really depends on who's doing the research. Um and it also customers sometimes don't even know they're interacting with AI and they're having a great experience, and sometimes they are interacting and have one bad experience, and that colors how they feel about everything. So I I feel like the the point I'm trying to get to is that I feel like we're all in this kind of messy middle together where we're figuring it out. But you've had to adjust, you've had to learn on the go. So, what are some of the lessons? What are some of the things that you would or or just highlights from the article as well? I'm kind of jumping all over the place, Brandon.

Brandon McGovern 23:23

That's okay. I love this article, but I also like a part of me hates it. And let me tell you why. Okay. And it's not a critique, but I like it.

Jeannie Walters 23:34

No, I love it.

Brandon McGovern 23:36

The problem with it is it's certainly painting AI and all of this adoption in a bad light. Like, oh my gosh, three quarters. Um, it even cites that those companies with gut with uh governance have even a higher uh with strong governance, have even a higher uh failure rate.

Jeannie Walters 23:53

Yeah.

Brandon McGovern 23:53

But what it doesn't tell you, and by the way, I'm a data guy, like I that's that's what most of us CX people at the heart, we like data, but what it doesn't tell you is what the denominator was and what it is now. And and the thing is, is I know anecdotally, there are tremendously higher number of pilots that we're doing. There are so many new solutions out there that are getting tested. And even within any single contact center, they're probably testing multiple solutions. So, of course, some of them are gonna fail, and likely many of them are gonna fail, but some of them are gonna succeed. And the ones that succeed are not the ones that are getting the the big headlines. It's the ones that are it's it's that some are failing. Well, maybe they're just not as good as the ones that are succeeding, and maybe it's natural, maybe it's actually healthy that these companies have um have a way of governing these and deciding which ones they like more and and what they want to move forward with. And and I'm seeing quite a bit of adoption, also testing and failures, and seeing all of it, right? Yeah, um, and then I couple that to with something we were talking about a minute ago, a little bit you were talking about how customers feel about AI. Like the bar of AI has been has been raising over the entire calendar year, really, as everybody's gotten their hands on ChatGPT and Claude and Gemini. The the consumers now have a reference point. And so good AI has to be great. They won't we we won't put up with marginal AI anymore. So that puts more uh more for the on the vendors who are you know pushing these solutions for testing to prove, and also you know, uh a higher bar for the operators who are trying these new solutions that they they have to succeed again. So so I actually don't know that it's a bad sign that things are failing, especially if we don't know the denominator of what how many pilots were run before and after. I actually see this almost as a good sign that there's a lot of smart people out there trying a lot of things, and things are gonna fail when you try a lot, but it some things are also gonna squeeze through and they're gonna make a big difference.

Jeannie Walters 26:01

I I love this point you're making that basically it's not good enough to be good enough, right? Like if we're gonna succeed, we have to make sure that we are exceeding the expectations and crappy experiences that people have come to know. And we all have been in those, you know, chat loops, we've all had those experiences as customers, and now we're moving past that when we're doing it well. But that is the big asterisk, right? Like it you you have to be constantly innovating in a way and looking at how we can use this in the best way and how do we make sure that it's more than good enough. Um, I think that's a really, really important point for folks to walk away with because it is like anything else. We have to make sure that we are really delivering and not just checking the box and saying, yeah, we're using AI, right?

Be Surgical With Intents And Handoffs

Brandon McGovern 27:03

So I'll also oh, I'm sorry.

Jeannie Walters 27:05

No, I was just gonna say, I love it.

Brandon McGovern 27:06

I'll also jump in and say, like you also can't just what we've seen, what I've seen, and what what I've talked with others about is we you can't deploy these AI chatbots or AI agents um just as uh across everything. You have to be very thoughtful in a contact center as an example, which intents are they going to be good at and which intents are they not going to be good at? And if if you really parse it down to the right level, it can be very successful. Companies like the one we talked about, the airline we talked about earlier, like when you when you really roll it out broadly, that's where you see massive failures because you're pushing AI against use cases and intents that frankly it at least at the time being, they're not going to be good at. Maybe in the future they are. I will never say never, seeing the pace of AI these days. But um, but right now, to be successful, you have to be a bit more surgical.

Jeannie Walters 28:04

Yeah, I I think that's a really important point as well. And I think it also is important to think about how this all comes together in the ecosystem you're working in. You know, if you're if you're having a great experience in one uh part of the organization, but then you kick them to another and it's terrible, there they might still feel bad about that AI, even though it did exactly what it said it was going to do. So we it's it's so much bigger than I think how we measure it right now. And to your point, I think there are plenty of pilots that we never hear about, right? They they succeed, they don't. We don't know because the companies aren't going to necessarily share those things far and wide. So yeah, it's it's a very interesting time we live in.

Brandon McGovern 28:50

I think there are many times when we're we any one of us might be talking to an AI agent and we don't know we are.

Jeannie Walters 28:57

Yep.

Brandon McGovern 28:57

And is that good, bad? You can you can make your own judgment how how much companies should disclose it. But the fact of the matter is the experience was solid enough that you it didn't matter if you knew or not, um, which is interesting to think about.

Jeannie Walters 29:13

And now we're moving into when our customers will have their agents talking to the brand agents, and the robots will just be everywhere. And you know, it's it's like I said, we live in interesting times.

Brandon McGovern 29:28

We could just go to happy hour or something. I don't know. Let the robots work it out.

Jeannie Walters 29:33

Like get that get that refund from that airline for me. I'm gonna go out. So yeah, it's uh well, I knew this would be a rich discussion, and um, I'm so grateful that you were able to make it with me today and and to uh just share all of your wisdom. It's been really a fun time discussing all

One Leadership Nugget And Where To Connect

Jeannie Walters 29:53

of this. And as we leave here today, two questions for you. One is, you know, is there anything, one little suggestion or recommendation you have for that leader who's listening to this right now, thinking, all right, this sounds good. What do I do? Um, if maybe they don't have total purview over AI in their organization. And then the second is if people want to get to know you more, what's the best way for them to do that?

Brandon McGovern 30:18

Oh gosh, such good, such a good question of like, what's that one nugget? I would say the single biggest nugget of advice that has changed me, and I know you were uh a part of the community that that really pushed this on me was was to jump in and try and get hands-on with it. The more you get hands-on, the more you you get familiar with using and testing different solutions, test different, even just the the AI, uh the LLMs themselves, the more you'll start recognizing where it fits and where it doesn't fit. So familiarity matters right now. And then in terms of me, I'm on LinkedIn at Brandon McGovern, and and you guys, you can you can look me up and I would love to continue the conversation there.

Jeannie Walters 31:04

Excellent. And we'll make sure that's in the show notes as well. But thank you so much, Brandon, and thank you, everybody here who listens, who watches, who's part of this community. You are leading into the future right now, whether you know it or not. We're all there. So keep up the great work and I will talk to you soon. Thanks, everybody.