Audio transcript:
Are You Surviving the Quarter or Shaping the Decade? How Smart CEOs Are Seizing the Moment
Joyce Mullen:
There are clients who say, I have no interest in this. I do not believe this is real. And
Jillian Viner:
There, wait a minute. You have skeptics, like C level skeptics of ai, C level skeptics
Joyce:
C level skeptics, huh? By 2030 in this industry, we will pull $4 trillion of cost out of processes using technology agents automation. That's a big number. Yeah. But the vast majority of the development and the opportunity associated with AI is really unleashing productivity and allowing us to grow it a way that we never dreamed possible.
Jillian:
Welcome to Insight on the podcast for leaders who need technology to deliver real business results. No fluff, no filler, just the clarity you need before your next big decision. Hey there, I'm your host, Jillian Viner, and today we're talking business strategy with Insights President and CEO Joyce Mullen. Let's get into it. Okay. Um, I wanna start with the very obvious thing, which is really, quite frankly, your timing and why you are the absolute perfect person to be having a conversation about instability and uncertainty. <laugh>. Um, I gotta look at my notes here because your career here has been interesting to say the least. <laugh>, uh, you stepped in. Is
Joyce:
It something I said? Maybe it's something I said.
Jillian:
I don't think so.
Joyce:
Drove all this craziness.
Jillian:
Yeah, yeah. Well, you stepped in as insights President North America in October, 2020. Mm-hmm <affirmative>. We don't need to be reminded of what it was like Yep. In October of 2020. Um, but I'm gonna brag on your behalf for a moment. 'cause I know that you won't do it. That's not your personality. But you stepped in and despite that volatility, you actually led insight to 14% growth in 2021.
Joyce:
Well, we got a little help from the market. Right?
Jillian:
Alright. See, you're just, you're, you're too, uh, too modest. But then in January, 2020, you officially, sorry, 2022, you officially became on as our president and CEO. Um, and then insight reported record, first quarter results, all while still navigating supply chain constraints, major internal transformation, and then shifting return to office dynamics, which still going on. Mm-hmm <affirmative>. Um, all during a continuous, uh, evolving technology landscape. Just when it looked like things were maybe gonna like chill out and stabilize for a bit, this little thing called generative AI hit the scene. Yep. And just disrupted everything all over again. Yep. And of course, now we are in a new wave of uncertainty because of tariffs and, um, trade policies. So I just kind of wanna hear from you, um, you ever had a dull moment in your career? <laugh>?
Joyce:
Well, technology's always been really exciting, but I would argue it's more exciting than normal right now. And the macro issues, I mean, I really think our customers are thinking about two things. They're thinking about this whole re globalization, this, the tariff, the trade policy work. It's kind of making everybody think a lot about their supply chains and where products come from in a way that they have never before. Hmm. Not exactly true. We got a little bit of a dry run at this, you know, uh, several years ago. But this is like more profound. The changes are much bigger and could be much more, I impact impactful and much more pervasive across all of our customer base. So it's not just where do computers come from, it's where everything comes from. And it's really having a very big impact on our customer's ability to plan.
Joyce:
So that, for that category of work, I think we've demonstrated a lot of agility. We've demonstrated incredible set of offers that we can bring to our customers and help them understand how do they get the most out of their technology investment, because we do understand the supply chains of all of our partners, et cetera. So that's, that I think is something we're good at and will continue to be agile and support our customer's needs. Um, the second thing is this AI transformation. And it is so exciting. I can't even, um, really articulate how interesting, challenging, but also impactful. This is gonna be, I think this is the biggest change since the industrial revolution. Maybe electricity. It's on that order. And the reason it's on that order is because of the impacts that it's gonna have. So first of all, everybody talks about AI as a mechanism to reduce costs.
Joyce:
And that is certainly true. But I heard some really interesting stats the other day. By 2030 in this industry, we will pull $4 trillion of cost out of processes using technology agents automation. That's a big number. Yeah. But we will also drive $22 trillion worth of growth GDP growth in that same period. And that $22 trillion moves to 40 trillion by 2040. So it is a cost out exercise to a certain extent, but the vast majority of the development and the opportunity associated with AI is really unleashing productivity and allowing us to grow in a way that we never dreamed possible. And there's no doubt that, you know, we will see unbelievable transformation in healthcare and in education and in sort of some mundane work, I would argue call centers for example. And there's also gonna be brand new revenue models, brand new businesses that we never even dreamed of. And that's why it's so exciting and so transformational.
Jillian:
Yeah. We're gonna talk a little bit more about that. But what I always hear from you, and you just demonstrated right now, is you continuously look at change as opportunity. If something's disruptive or different, that means there's change on the other side of it. So you're always sort of looking ahead at what this means. What could this unlock for the future? Um, you know, we're already halfway through 2025, which is really hard to believe. It's insane. It's insane. <laugh>. Yeah. And, and on one hand it's gone by really, really fast. But on the other hand, it almost feels like we've been going at it with this like, yellow caution flag on people seem afraid to sort of hit the pedal to the metal. Mm-hmm <affirmative>. I'm curious from you, you know, what, what's, what's the first six months of this year taught you kind of, what are you hearing around colleagues? Are they looking at the rest of the year with a little bit more decision making?
Joyce:
Well, there's no doubt that there's caution driven by the macro issues that we just talked about in two ways. One is I don't really know how to plan my business. 'cause I don't really know what's gonna happen with tariffs. I don't know what's gonna happen with my supply chain. I don't really know what my, the demand for my products and services looks like. So, God, I'm hesitating there. Yeah. The other thing that is driving it is there's, it's clear that most of our customers are saying, okay, AI is big. Um, I don't really know exactly what that means to me and my business. I'm trying to figure out how to spend money, but really cautiously because I wanna preserve money for ai. So all of that leads to a little bit of delay in terms of decision making and, and progress, frankly. Um, we expect that to improve in the back half of the year, but honestly, I expected it to improve in the back half of last year. That does
Jillian:
Surprise me that, yeah. You're, you, you've been, you've been really bullish on AI from the start. We'll talk about that. Um, where are you hearing from other CEOs or maybe amongst your own team, what are you kind of prioritizing for the rest of the year to make sure that you do come out ahead?
Joyce:
Well, the first thing is we've gotta make sure we can help our customers navigate all the, the tariffs and trade policy issues. Um, the second thing is we, I think have an opportunity and a responsibility to help them with no regrets. Moves that are gonna make, help them en enable their environments for AI adoption. So things like making sure your security is in place, things like making sure your infrastructure is relatively modern and, and you can move data around. Um, cloud adoption is a pretty important part of that. Making sure you understand where your data is and how to access those data. Mm-hmm <affirmative>. And so, because those are critical to any kind of AI process or Agentic work for sure. Yeah. So those no regrets moves, I think are the things that resonate most effectively. And by the way, a bunch of those can also be cost reductions. So in this environment, cost reductions help. You're
Jillian:
Setting yourself a good foundation. Exactly.
Joyce:
Yeah.
Jillian:
Uh, let's talk about clients. I know that's your favorite part of the job. When you think about the clients that you're talking to on a regular basis right now, what kind of things are you seeing that excites you? Who are the people that are really seizing this moment? What is it that they're doing differently that's setting them apart?
Joyce:
You know, I think, um, so first of all, it's really interesting 'cause there's quite a spectrum. There are clients who say, I have no interest in this. I do not believe this is real.
Jillian:
And wait a minute, you have skeptics, like C level skeptics of ai, C level
Joyce:
Skeptics, C level skeptics, huh. And I think probably that's because we're still so, so early in driving adoption. And frankly, it's not easy to implement agentic capabilities in an environment if you don't have your data set up. So it's accessible. Mm-hmm <affirmative>. If you haven't figured out how to imp, you know, improve the, the skills and capabilities of your teammates so that they can actually build and use these, these new technologies. It's pretty daunting. It's huge.
Jillian:
If you're just doing it from the basic email summary meeting and recap, you're not
Joyce:
Yeah. Yeah. By the way, co-pilot's good. But the promise of AI is not copilot. It's be beyond, way beyond co-pilot. It is coding that is 30 to 50 to 40, 40 to 50% more efficient. It is making sure that you can take people out of the soul sucking work and focus them on the things that require judgment and character and relationships. Mm-hmm <affirmative>. And I think that is where it gets a little trickier. That requires change management, it requires business process reimagination. And if you just try to say, I'm gonna just go, you know, I'm gonna implement AI without a real specific outcome in mind, I think it's really, really hard to see the results. So that is kind of how we're trying to position AI is do something. I mean, think about it in bite-sized chunks. Mm-hmm <affirmative>. We will work with you to deliver results fast. The output will be clear. The ROI will be clear, and then we will earn the right to do the next thing and the next thing and the next thing. But trying to tackle this from soup to nuts is just an impossible task.
Jillian:
How do you eat an elephant? Yeah.
Joyce:
<laugh> can't do it. Can't do it one bite at a time. Yeah.
Jillian:
Yeah. So you talk to leaders from across industries, including some of our partners. What kind of conversations are they raising? Are you hearing kind of the same drumbeat or same message from leaders or there very different camps about where they are with the view of AI and AI adoption?
Joyce:
So we have, we are so fortunate that we have strong relationships with the massive change makers in this space. So the hardware guys like Nvidia, Dell, HPE, the, the platforms like, uh, Microsoft, Google, AWS, ServiceNow, um, everything in between. And I would argue that they are, they don't represent a normal subset of our customer set because they are obviously very, very motivated to sell technology. Sure. Mm-hmm <affirmative>. And, and so they're probably closer to it than most. So I would argue most of our partners of co there's a spectrum. Again, most of our partners are very, very excited about the opportunities associated with ai. Um, Dell was talking about this at a recent event that we just had. They were talking about how for the first time in the history of the company, revenue grew and their operating expenses declined. Wow. That's impressive. And they attribute that to the implementation of a focus on simplification of processes, standardization of processes, and then automation of the processes.
Joyce:
It's pretty impressive. Um, I, I just was with the ServiceNow team. They talked about, uh, dramatically shortening the cycle time to, to deliver solutions and services to their customers, dramatically shortening the cycle time to build products. Mm-hmm <affirmative>. And Microsoft says the same. They were talking about amazing, um, improvements that they've seen in, in their own coding capabilities and the percentage of the code that is created by the large language models instead of created by developers. So, I mean, there's a lot of improvements that we're seeing now. As I said, this is probably not completely representative of the world at large because these are very technical, very, very focused, um, companies who understand the technology and have been working on it for a long time. Mm-hmm <affirmative>. But those kinds of success stories are really important for us to share with our clients because they can kind of illustrate the art of the possible by adopting these things.
Jillian:
It's ambitious. Yeah. I mean, and I imagine a lot of leaders at maybe mid-level enterprises, bigger enterprises, they're probably looking at them going, well, I can't do that. We don't have those resources. But you're kind of framing it as well, someday you will be able to do that because these, this will be
Joyce:
Possible. And by the way, we can help you in the interim. So
Jillian:
It's understandable that those big guys would be excited about it and already seeing results. But for leaders of the other mid-level, you know, mid-market companies, especially across these different industries, like where are they at? How are they feeling? Are they feeling behind? Are they on top of it? What's kind of the general temperature out there?
Joyce:
I would say the vast majority are just starting to try to use some of the capabilities and technologies. Mm. And they feel like there should be promise, they're getting pressure to figure out how to use it, and they're not really sure how. And you know, this is where companies like Insight come in.
Jillian:
It's probably comforting to some degree to know that if you're feeling behind, you're not the only one.
Joyce:
Well, yeah. But I think it's also an amazing opportunity. 'cause if you can get ahead of the curve, you're gonna be in a much stronger position. And I,
Jillian:
This is the moment.
Joyce:
This is the moment while
Jillian:
Everyone else is still figuring it out.
Joyce:
Yep. Go for
Jillian:
It. This is the moment. Yeah. Well, yeah. That's your motto is Go for it, <laugh>. Go for it. Exactly. Yeah. I know you said it's kind of early, but has anybody been able to do this successfully yet?
Joyce:
Absolutely. We're seeing it across so many of our, so many of our clients we're seeing really terrific adoption on use of their data to get a 360 degree view, for example, of what their customer interaction is with them. Boeing Resorts, resorts comes to mind. They have Big Sky and some other resorts, very, very cool company. But they're thinking about how does, how does the customer interact with their systems? How do they understand what their preferences are? And one, you know, maybe it's in a, in a, at a ski resort one day, but it's at a beach resort the next. And they figure out how to make sure that they're adapting there. Um, and then they're automatically serving up options that are, that are interesting to them. Um, Sherlock is a, is a company I really like. I like because they basically, uh, they're the, the company that basically comes up with these little thumbnails that you see on Netflix or Oh yeah. Uh, whatever, to choose to choose a, a, a movie to watch. And our teams help them figure out how to use agents to look through all of that video used to be a manual process, used to take days. Now they serve up 10 images that meet their criteria. And, you know, the people who have to have apply the judgment <laugh> Yeah. And the character. Um, they're the ones who choose it.
Jillian:
There's definitely been movies I've pulled up on a streaming surface, and I'm like, really? That's the screen scratch shot that they Yeah. That they chose. But now that you think about it, like Yeah, that's hours of footage you have to go through. Yeah. Now they're expediting. That's amazing. Yeah.
Joyce:
That's also not that fulfilling of a job, I don't think.
Jillian:
Probably not. I mean, I'm a, I'm a love movies, but I don't think I wanna be scrubbing through footage. Yeah. Uh, the Boyne results, uh, resorts example is interesting. Personalization has been something that businesses have been after forever. And I think sometimes we gawk at, you know, giving away data. But everybody loves a personalized experience when it absolutely makes a better vacation. Or you show up with the right snacks in your room or what have you. So that's incredible.
Joyce:
Oh, in the same technologies are gonna be used to make sure we personalize medicine in a way that is much more effective and way better patient experience, way better patient outcomes. Think about personalizing education. I mean, we all know people learn differently. Yep. And if you have a dedicated free, a AI tutor who can help you and you learn differently than the next kid, I mean, there's a real opportunity to improve productivity there too.
Jillian:
I was just talking to my intern earlier and she said she's using AI all day long to help her understand things. Yeah,
Joyce:
Me
Jillian:
Too. This is all new language. <laugh> Me too. <laugh> me too. Uh, alright, let's talk about tech investments. Yep. I've heard you say that tech is not discretionary, it's not optional, but there's a lot of companies where, you know, margins are slim, budgets are tight. They know they have to make tech investments, but they're not in a position to test and learn. Right. They've gotta make tech investments with confidence. Is there a philosophy that you follow or certain questions that you ask, or maybe a group of people that you bring together so that you make those tech decisions with confidence? Like, how do you know where to pull back in areas and where you really need to go deep?
Joyce:
Well, we spend time with our clients to understand that we, we do, um, what we call a radius, which is a, we use a lot of ai, a lot of AI flashpoints in a radius. But what we basically do is listen to what they're talking about, understand where the biggest issues are that they're trying to solve. Try to help them prioritize those issues based on what's ever most important. Sometimes it's, it's, it's financial results. Sometimes it's safety, sometimes it's customer experience, whatever. Um, and then we, we, I think one of the things we do so well, and we distinguish ourselves from kind of the big sis big consulting companies and also from VARs, is to really chop up these projects into bite-size pieces so that we can deliver those outcomes and earn the right to do more. And I mean, I think that is, that's the way we buy technology.
Joyce:
That's how we like to do it. Mm-hmm <affirmative>. And so we're pretty clear that it is a better way than trying to get customers to commit to some really big, long-term project with milestones that are hard to quantify in terms of benefit to them. Mm-hmm <affirmative>. Also, that ties up a lot of operating expense over time. And you might wanna change your mind about the speed and frequency and sequencing as you learn things with your data and with the projects that you complete. So I really like that approach. Um, we're proven that out over and over again. That's
Jillian:
Thoughtful. And for I understand too, it really starts in the beginning to understand, okay, if we make this change, what are the downstream impacts? Right. That we thought about those things.
Joyce:
Right. And you're not gonna be able to think about, especially if we do a great job helping them reimagine the business process mm-hmm <affirmative>. Because we're talking about not just automating the 15 steps that we know about. We're talking about parallel processing a bunch of these activities that was really never possible before. And that means we have to think kind of exponentially, which is so hard to do and really sort of reimagine. Like, if you just think about what you're trying to get out of a process and say, do I really need all these steps at all? And maybe you don't, maybe you can just go from instead of A to B2C, d, all the way to G you might just go F to G. I mean, that's kind
Jillian:
Of, sometimes we overcomplicate things. Yes. <laugh>,
Joyce:
We, we have very good experience on that. <laugh>,
Jillian:
Breaking it down, simplifying it. Uh, I wanna go back to something personal. You are a tremendous leader, highly respected here at Insight. What's the best leadership advice that you've had in your career?
Joyce:
Well, I have told, I feel like I've told this story a lot, but I do really feel like, um, I learned from, uh, when I was a very new plant manager from John Yoder, who'd been a plant manager for 50 years at Cummins Engine Company. He, um, he basically took me aside and, and I was trying to figure out, okay, I'm brand new. I really don't know anything about manufacturing. I kind of knew at least textbook wise about, you know, operations and supply chain. And, um, he said, he took me aside and he said, Joyce, you gotta paint the bathrooms. And I thought, that is really a bizarre thing to tell you, tell somebody. And he, um, I said, what do you mean, John? He said, just think about it for a little while. You'll figure it out. So I went back to the plant, went into the bathrooms on the shop floor, and learned that this is a place where people were visiting it every, you know, couple of several hours, I'm sure several times a day.
Joyce:
And the mirrors were broken, the tiles were broken, the toilet seats were broken. It was just not a place that screamed we respect you. Um, and I thought, oh, I kind of see what he's talking about. This is not the environment that, you know, indicates respect or, um, benevolence. Yeah. Or any kind of, you know, any kind of signal that those people who do all of the work mm-hmm <affirmative>. Are important. So I went back to my team and I said, okay, we have to, we have to. This is really not what we're trying, this is not the message we're trying to send. Um, so we didn't have the budget, of course, we figured it out and redid the bathrooms. Now this was a UAW plant, and the president of the U aaw was named Rocky. He, um, had quite a rocky relationship, <laugh> anyway. Um, and he, I thought he was gonna be really excited 'cause this was really an important thing to do and a good thing to do for the team.
Joyce:
He had very little to say about it, but he said, um, he said, you know, you get a girl in here to run a plant. First thing she does is paint the bathrooms. Next thing you know, she'll be hanging up curtains. And, um, so he wasn't that pleased. But I do think that that notion of saying, thank you very much, we respect you. We see you, we hear, you know, we hear your concerns mattered. We about, I guess it was probably about eight months later, we negotiated the longest term contract we'd ever negotiated with, with a union there. Hmm. And I'm not saying it's 'cause we painted the bathrooms, but I think it is because of this notion that we're in this together, we wanna demonstrate the respect and the, and the, and frankly the care, um, for all the people who do the work every day value.
Joyce:
So, yeah. You know, and I think that applies no matter where you are. I mean, it's interesting. I just listened to John Levy, who's a behavioral psychologist, and he was at one of these meetings I went to not too long ago. He said, in times of uncertainty, leaders have to demonstrate first competence. Mm-hmm <affirmative>. But we spend a lot of time on competence. That's not the issue. Even more important than con competence is honesty. So clarity, honesty about, okay, your work might change. This is why it's good for you. This is maybe what you need to do. This is how we should think about this. This is the work over time that will probably not be, um, work for people anymore. Like, let's talk about that. Um, but then even more important than honesty is benevolence. And that is demonstrating how much you care about the teammates you work with every single day. Because, you know, that's something AI can't do. Yeah.
Jillian:
I, I love that you even went down that road. I mean, you kind of took the next question outta my mouth, because that story is so timely right now. When you think about just the, the volume of uncertainty. I mean, AI in the eyes of people who see the future and believe in this as a really positive change maker, it's exciting. But the reality is a lot of people are terrified. They do see change, and they wonder how it's gonna impact their, their lives, their jobs, their futures. And on top of that, you know, there's just a lot of uncertainty going on in the world, and people kind of crave familiarity. You know, it's like people like me who watch Schitt's Creek on repeat every single night. Because it's familiar. I think calm, think it's
Joyce:
A really good idea. <laugh>
Jillian:
Just helps my brain latch onto something familiar and feel good. Um, but it's hard to create that I think, sometimes in a workplace. So when you're thinking about all of that emotion that people are feeling that they become so change adverse, you know, it feels like your way of quote unquote painting the bathrooms is just, as you said, being, being honest with them, being clear with them, and approaching with, with some humility. Is there anything else that you use or coach your teammates to do to again, quote unquote paint the bathrooms
Joyce:
<laugh>? Well, you know, I think we really have to make sure that we are encouraging our team to learn these new skills. I mean, there's, I mean, you mentioned it, your intern is using AI every day. We're all like trying to figure it out something. Everyone knows how to do all this stuff yet, um, we have an opportunity, an obligation, a responsibility to learn it faster, because we have clients who depend on us for exactly this capability. And that means we have to make the tools available to our teammates. We have to encourage them to use it. We have to make sure that they're willing to try and fail, because try and fail, as long as we learn is a win. Try and succeed and deliver great results is also a win. So it is kind of a no-lose situation, but we've gotta attack it with that kind of attitude.
Joyce:
And, you know, everybody always says this, so I I, I don't even know who to attribute the quote to, but AI won't take your job, but someone who knows how to use AI will take your job. And so I think it, we all have this opportunity to figure out how to build our own skills. One of the things that keeps me thinking a lot about how do we tr is, is how do we transform our workforce? Hmm. How do we train entry level salespeople? How do we train entry level coders? How do we make sure people are learning the skills that they need to learn? Which is probably different than the way it used to be. You know, it was two years ago. Yeah. So I think that is something that from an organizational development and skill development kind of point of view, we have, uh, we're all gonna learn and learn together.
Jillian:
Do you think people are a little bit afraid that they're gonna have to let go of some of the, I don't wanna call it busy work, but it, it's like the quick task things that at the end of the day, you're like, well, it was busy, had a lot of meetings, but I did blah, blah, blah. So I feel like I was productive. Like, a lot of that I think is gonna get done by ai. And so we're gonna be tasked with more of the strategic deep thinking. Yeah. That's gonna be a big shift.
Joyce:
Yeah, it's a big shift. Yeah, sure. There's comfort. It's like, scree, <laugh>. I mean, I mean, if
Jillian:
I, it's easy,
Joyce:
Doesn't, my job is to get back to the customer and tell them when their order's gonna arrive. Okay. I'm, I'm pretty confident I can do that really effectively. Yeah. But is that the best and highest use of your brain, your knowledge, your judgment, your skill, your character, your relationships? Probably not. Yeah. Yeah.
Jillian:
Well, speaking of reruns, that was a great transition. <laugh>, uh, I wanna rewind to one year ago in this very studio, we were sitting here with a group of C-level leaders, very smart people, talking about generative ai Right at the moment when adoption of generative AI in the business was, was kind of new and fresh. Uh, and you said something during that conversation that really stuck with me. Let's, let's play that.
Joyce:
I have a son, I'm not gonna talk about what company he works for, but he, he does a whole bunch of work now through chat, GPT or through Bard. He checks his own code and he is basically reducing the amount of time it takes to troubleshoot, um, any kind of code that he, he builds. And when I say, okay, well what are you doing with the extra time? He says, oh, well, I'm going on a bike ride <laugh>, or I'm, uh, I'm, I'm rock climbing. And I'm thinking, okay, well then we as leaders have an obligation to raise the bar on productivity expectations and enable the adoption of, of those tools because it's in our client's interest to get through those backlogs faster, because that's gonna drive the next wave of technology adoption. And that's true of us internally as well.
Jillian:
He said he was using Bard, so RIP Bard. But Gemini has been a really great predecessor.
Joyce:
So yeah,
Jillian:
Gemini, good job.
Joyce:
Google Gemini's doing a good job. Yeah.
Jillian:
Uh, so first of all, I really wanna know, how's the bike riding, rock climbing going? Yeah.
Joyce:
Much better for him than for me. <laugh>. <laugh>. Um, yeah. You know, I think, um, I think everybody's graduated a little bit to demonstrating higher expectations. I think every, most companies, most leaders are for other reasons as well, constraining budgets mm-hmm <affirmative>. And looking for different ways to get things done. So I think we're on a path, but, you know, I think there's more to do there. I was
Jillian:
Gonna ask you like, that was a big bold commitment. You, you believe that we have to get productivity to a better place. Yep. How do you think we've done? It's
Joyce:
Okay. Yeah. I mean, we're seeing some really good, um, improvement in terms of the way we measure, uh, code development, productivity. Mm-hmm <affirmative>. Um, quality improvements in code. I mean, it's all of those things. That's an internal measure that we look at. Um, you know, we're working really hard to improve our, we've, we've managed our opex, we're seeing better opex leverage, not only because of ai, but, but we're using that as a way to get to the outcomes with a constrained budget. And I, I think that's, that's an obvious choice.
Jillian:
We talked earlier about generative AI use cases being maybe not as exciting if, if they're, if you're just stuck, you know, at the beginning stages of email summarization and there's so much more that it can do. Uh, again, you've been really bullish on this so, you know, what have you, what have you found so far, maybe with an insight that's been really, I don't know, impressive magical?
Joyce:
Yeah. You know, I'm really excited about what we did with our sales support tool, because basically that is like having a research assistant in every sales person's pocket basically goes out and looks at all the data around, uh, that's available for any of our customers. Um, it gives a summary of the things that they care about most. Well, it depends what you ask it. Mm-hmm <affirmative>. But now part of, I would argue, I don't know what the numbers are, but I use it every single time I go to see a customer. And I think, uh, you know, it's a, it's a great resource that takes a long time doing research on a client, especially a new one where you don't have a relationship can be a really, you know, that's kind of drudgery work. Yeah. And, and I really, but
Jillian:
Important. Yeah.
Joyce:
But really important <laugh> and I love that we now have access to this. And every single one of our sales teammates, actually every single one of us has that has that assistant in our pocket who's already done that research for us. It's really good.
Jillian:
Have you seen employee attitudes towards generated AI change over, over the course of the last year or so? 'cause I mean, we started with it almost as soon as it came out. I mean, you were, you were quick to get our, our security and our it all set
Joyce:
Up. I had nothing to do with it. <laugh>, but I mean, our team did a really good job getting that ready to rock and roll, you know? Yes. Because I, here's how I can tell the bar is raised. So we were quick to do that, but then all of a sudden, only that was insufficient. So we have much more co-pilot usage going on. A lot of it is for summarization, like you talked about, but I think we're seeing increased sophistication of our co-pilot work. That's pretty good. Mm-hmm <affirmative>. Um, I also feel like we have a lot of, um, a lot of work going on with some of our internal projects around coding, like I talked about mm-hmm <affirmative>. That's really been quite impressive. But here's how I know that cus 'cause we have teammates who are looking at this saying, Hey, we need access to different models. We need access to more models. They need to be more up to date. This is not serving my purpose anymore. So I like that our teammates are raising the bar on us
Jillian:
And they're like even focusing on the, the type of model to do the right
Joyce:
Kind of work. Yeah. That's really impressive.
Jillian:
Yeah. Uh, is there a particular use case that you love as like a day-to-day? Like, has it changed the way that you work or live in any way? Uh,
Joyce:
I'll, I'll, yeah. I mean, I, first of all, I don't search anywhere except for you're
Jillian:
The one killing our organic search on our website. I know
Joyce:
<laugh> probably could be. And also I worry about the sustainability issues associated with that. So I think there's a little but I, that, that will improve over time, by the way that I think that's gonna get be better fast. Um, but yeah, I mean, you get a much more thoughtful answer. Mm-hmm <affirmative>. You don't have to fight through a bunch of sponsored, you know, you're not even, you don't even wanna see this stuff. All
Jillian:
That marketing stuff. Yeah. <laugh>
Joyce:
And, and we're seeing, uh, and you get a much more thorough ex, you know, explanation. It is really, really helpful. So I use it all the time. I used it for, I mean, personally I used it all the time for trip planning or, um, identifying what's the best restaurant with an outdoor patio that's two blocks within two blocks.
Jillian:
Parameters. Yes. <laugh>. Yeah.
Joyce:
It's awesome. It's awesome. And that gets great reviews on Yelp and, you know, other Google, Google or whatever mm-hmm <affirmative>. Um, so I use it all the time personally. And then for work, I mean, it is a great, just like your intern said, it is a really terrific way, uh, to learn about some term, somebody saying in a meeting, I use it all the time. <laugh>, or to compare and contrast options mm-hmm <affirmative>. And understand kind of what we're putting in front of our front of our clients. We need to assume that every one of our clients is using it that way too. So when we give them a proposal or we give them a couple of options, they're gonna go run that through some kind of model and they're gonna figure out like, are are we giving 'em the whole story? Yeah.
Jillian:
That's an interesting view. I actually never really thought about that. But you do have to create things with that in mind and it's
Joyce:
Gonna change how we think about our own case studies. Yeah. And how do we get, how do we get insight to show up when people look to those models for the advice and counsel that they're, they've historically looked to search for. Yeah.
Jillian:
I'll say though, there is nothing like the authentic face-to-face conversation with someone who's lived these things. Absolutely. And come through these experiences.
Joyce:
And that's what our, our clients think the same. Yeah. So that's again, judgment relationship. Mm-hmm <affirmative>. That's where we can focus our time and effort.
Jillian:
You're talking to clients all the time. Do you find yourself giving a common piece of advice these days?
Joyce:
Start small, deliver results fast or earn the right to do more?
Jillian:
Just go. Yeah. Just
Joyce:
Do it. Just, yeah. But stop thinking about it. I mean, tons of pilots, you know, whatever. I mean, I, I I don't particularly love pilots. I think you should get on with the execution. <laugh>. I mean, stop talking about it. Just do it. Give people the tools, set up the parameters, the go. I mean the governance and the policy and the security is super important. Mm-hmm <affirmative>. So make sure that that's in place. Like, get people going.
Jillian:
I wanna close with a question. I'm told that you ask every candidate interview. Yeah. What have you learned recently?
Joyce:
Well, I've learned a, a lot of specific things because I asked Gemini or I asked
Jillian:
GT by the, I gotta say to hear someone with a Harvard and Brown degree saying that they're using, you know, Gemini to, to learn something. It's, uh, all the time. All the
Joyce:
Time. All the time.
Jillian:
No, but I, what I
Joyce:
Really, I, I think that the thing that I've learned most recently is that there is a level of enthusiasm and hunger. I know there's also concern mm-hmm <affirmative>. So I don't want to paint a rosy, rosy picture. Um, there is a level of enthusiasm and excitement about learning and growing skillset that I am really, really proud that we are driving in our team. And we've seen, you know, we've had this initiative, our snowball initiative, which is all around our internal adoption of AI at, at Insight and the number of teammates who are participating, learning, succeeding, and failing, but learning. So it's, uh, win-win all the time is, is spectacular. Snowball.
Jillian:
Yeah. What do you mean? So,
Joyce:
So we have this pro uh, um, we, we took out a really senior leader, um, we dedicated him to internal AI u use and case studies. We have business plans across every aspect of our North American business. We have started building sort of smaller bite-sized kind of improvements and use cases. Some will fail, some will succeed be, it's gonna be great no matter what. And it's already a yielding results in the process. We're teaching all of our teammates to use these tools. And then we have a several, um, sort of cross enterprise projects that we are working on right now. And that we will Dr. Will dramatically change kind of our cost structure and our speed. 'cause this eventually is all about speed to deliver sort of, you know, various, various processes, which might mean creating a sow for a customer. It might mean managing an environment for a customer. It might mean figuring out how to use ag agentic, uh, agents to help us sell. It might mean using agents to drive our operations, whatever. I'm super excited about it. So
Jillian:
You're putting the, the, not only the use case, but really the autonomy in the hands of your users across different lines of business and telling them, Hey, what what problems do you have? Yeah. And could we maybe fix this with ai? Yeah. And they're bubbling.
Joyce:
Go, go learn. Go learn how to do it. No, just do it <laugh>. Just do it. Don't, I mean, you can bubble it off if you want. <laugh>. And we by the way, are I think are having a lot of fun recognizing the teammates who've done a bunch of these improvements mm-hmm <affirmative>. And we're, um, excited about making sure that they're recognized. But I think it's all about overcoming that fear that you were talking about.
Jillian:
Yeah. Yeah. It's, it's really inspiring when you see how someone is using something and it kind of sparks a different idea of Yeah. How you could apply it. Yeah. Yeah. Yeah. Brilliant. Yeah. Thank you for sharing that. Yeah, Joyce, it was absolute pleasure to talk to you. Thank you for coming on. I hope we can talk to you again. Of course. Anytime, maybe any year end wrap up and we'll see if maybe we got a little bit faster as the last half of the year closed up.
Joyce:
Yeah, we'll see how it goes. <laugh>. It's gonna be exciting. I think we have absolutely no idea what the next five years looks like. I think we have absolutely no idea. I listened to Jeffrey Hinton at this meeting I was just at in, um, in Europe. It was, and he's the guy who left Google. He's like the godfather. He figured out how to build neural networks in 1985. And he said, um, he had a lot to say about a lot of things and explained how neural networks were built. That's the thing I really learned in the last few days, <laugh>. Um, which is something I had no idea about. But anyway, he said, his parting comment was, we have absolutely no idea what the next five years looks like.
Jillian:
And so you say that with glint in your eyes.
Joyce:
I'm so excited. <laugh>, <laugh>, I'm so excited about it.
Jillian:
Again, you're the best person to talk to and it's like a middle of a, we don't know what's going on. Yeah. So I love it.
Joyce:
Yeah, exactly. I think I, I, I do think, and, and as leaders, we just have to make sure that we remember that not everybody loves it as much as I do. Um, but, and there is a level of competence, honesty, and benevolence that has to support our teammates in times of such dramatic change.
Jillian:
Great advice.
Speaker 3:
Thank you, TAUs. Thank
Joyce:
You.
Speaker 3:
Thanks for listening to this episode of Insight on. If today's conversation sparked an idea or raised a challenge, you're facing head to insight.com. You'll find the resources, case studies, and real world solutions to help you lead with clarity. If you found this episode to be helpful, be sure to follow insight on, leave a review and share it with a colleague. It's how we grow the conversation and help more leaders make better tech decisions. Insight Enterprises is a Fortune 500 solutions integrator. With over 16,000 teammates worldwide, helping organizations accelerate their digital journey and modernize their business and maximize the value of technology, we enable secure end-to-end transformation and meet the needs of our clients through a comprehensive portfolio of solutions, far reaching partnerships. And over 35 years of broad IT experience rated as Forbes World's best employer and certified as a great place to work, we amplify our solutions and services at a global scale, local expertise, and world-class e-commerce experience, realizing the digital ambitions of our clients at every opportunity. Discover more@insight.com. The views and opinions expressed in this podcast are of those of the host and the guests, and do not necessarily reflect on the official policy or position of insight or its affiliate. This content is for informational purposes only. It should not be considered as professional or legal advice.
