AI-Powered Workplace Solutions with Kyndryl’s Dennis Perpetua

This is Techstrong tv. Hey everyone. Welcome back here to Techstrong tv.

I'm really happy to introduce you to Dennis Perpetua, where Dennis is the global CTO Digital Workplace Services and Experience Officer, as well as being a vice president, and most importantly, a distinguished engineer at ndl. Hey, Dennis, welcome to Text Drunk tv. It's great to have you on here.

Thanks so much, Alan. It's nice to be here. So that was a mouthful of a title.

Um, I'll, I'll talk briefly to distinguished engineers, right? That, as I said, most importantly, that's probably a, in my mind, the most coveted and, and, uh, of, of the several titles you have there, right? That's not something they throw around lightly at companies like Ken ndl and IBM and and so forth.

But, you know, how did this tell us a little bit of your journey to distinguished engineering global CTO? Yeah, thanks. Thanks for that question, and thanks for the, the, the, the, the framing of distinguished engineer.

It's, it's not a title that everybody universally understands. Vin a distinguished engineer for about eight or nine years. Um, and, and so that, that's, that's come, I've been in it for about 24.

And so my background has been in systems management infrastructure. I spent a lot of time in virtualization. I spent a lot of times inside the data center, uh, you know, sit sitting next to the, uh, the systems that run the world.

And, and really in the last nine years, I've had the opportunity to really get involved with a ai, artificial intelligence and the digital workplace. And, and that's been an exciting journey because what it allows me to do is what I think is prominent around a distinguished engineer, which is to, um, couple technology with business outcomes. And so I've had a weird journey to where I am.

My background is actually, my undergraduate degree is actually in psychology. Mm-Hmm. Um, I worked as a professional photographer and graphic designer for a little bit, so I have a little bit of credentials around, say, user experience from that point of view.

Mm-Hmm. Um, and then, uh, I have a, a master's degree in computer science. And so I've, I've kind of looked at my journey, which maybe five, six years ago would've sounded like a hodgepodge of things to now kind of making sense in the hybrid IT world and the AI world because it, it marries up the technology, the user experience, and the business outcomes that, that we're all each expected to deliver in our roles today.

Excellent. What a great journey, man, photographer, psychology major. You're not the only, you know, believe it or not, I've struggled with a lot of people who wind up in it with a degree in psychology.

Y You know, five, six years ago, it was something that I'd hedge and I would be a little bit shy to, to say I'd only talk about my technology degree, but I think recently it, it's actually more commonplace and, and more valuable to have, uh, uh, uh, an experience that looks at how we actually bring technology into the, into the workplace more effectively. You, you know, AI particularly, it's, and, and this isn't say a, a covid statement or a hybrid IPT statement, it's really, you know, how we look at ai because AI is a, is a human technology. We're all experiencing it, we're all working with it.

And, and that combination is something that I'm seeing more and more, uh, popular lately. Sure is. Hey, Dennis, I mentioned KY and I can't help with KY and I think IBM and of course RY was a, a giant sized spin out for my IBM, but it's, it's a, it's a public company in its own right.

It's been thriving since spinoff, but not everyone out here may be as familiar as I am. Why don't you give 'em a little bit of the NDL story? Yeah.

I think the first thing that I, I wanna definitely make sure everybody's aware of is we are our own company. ndl is not related to IBM at all. And, and as I go through my days, um, I still have a mixed understanding of that out there that I see we're absolutely our own company, and it, it really is a sign of the times because, um, we are the, the largest, uh, infrastructure provider on the planet.

And, and so that's quite a statement. And when I say it's a sign of the times, really I think what what was happening was we needed to have the ability to be our own independent company so that we could bring the best technology solutions to our customers, not beholden to a single software companies technology. And so as we became our own company, it allowed us to really form strategic alliances to bring the best technology to our customers.

We focus on, uh, fortune five hundreds, um, and, and anybody who's looking at big infrastructure technology solutions, um, that are really trying to drive the right business outcomes for it. So as we see the market changing, we've opened up our tech stack to be able to bring the power of, or the size of us, the power of the size of us to bear with our alliances, to bring the right alliance partners to the table with our customers. So that's that situation where the expertise that we have in ndl, the power that our alliances bring to us and our customers' business problems can, can really, uh, provide value and to, and provide innovation.

Um, and we have a strong, strong approach around partnering with intent with our customers that is consult led. And, and that's a really important piece because that's an aspect that we've grown over the past three years, is to really have a strong consulting capability. So as we look at a customer's business objectives, we have the right consulting, um, teams in place that can allow us to look at the entire stack from infrastructure up to application and business outcomes to allow our customers to, to get the most value from some of the technology that they've deployed or are looking to deploy, uh, with our alliances.

Great. I love it. com.

Yep. And, and I'll just, uh, um, share that a little bit of a unique spelling. It's two words that are brought together, which means that, you know, the, the net of it is, is, is we are the heart of progress that the meaning has roots in, in that and, and really is a, is a testament to our intention as a company, as an independent company, to, to really work with customers very closely to understand their industry, their challenges, and, and to work with them to achieve some of their goals.

Great. I appreciate that. Dennis, if you don't mind, I'd like to kind of switch gears and, and jump into our topic of discussion for this interview, which is, you know, you guys are accelerating deployment and adoption of AI powered workplace solutions, and you're using or basing it, you know, this on copilot for, uh, Microsoft 3 6 5.

Um, you know, I, I think I said it there, but what's that all mean? And and where does rubber meet the road? Give us some insights.

Yeah, so, you know, we have a, a heritage of ai, so we have a lot of experience working with AI solutions. Obviously in the past year and a half, two years, uh, the conversation around AI has dramatically changed the, the promises that have been in place for say the last decade have started to really come to fruition and, and what we see in the market. And, and I see, you know, there's, there's plenty of examples where folks are coming out and still still claiming skepticism around the promise of generative ai, but we're in a position particularly with Microsoft copilot and our, our, our alliance with Microsoft to be able to actually deliver on the promise and the value that is expected from it.

And so when we look at copilot, you mentioned M 365 copilot. Copilot is a broad term now. There's, there's over a dozen different copilots that are out there.

And so what we're doing is working with customers to enable the ROI and the value of that to be brought in. It's not something that you just flick a switch and turn on. There's a lot of things in the background that need to be done from, uh, data management to, uh, organizing the type of training material to security questions.

Most importantly, though, the thing that we're seeing, um, us provide a lot of value on is making sure that the use cases and that ROI that is expected from generative AI and copilot is being realized. And, and that's, that's one of the things that I think, um, we have a tremendous amount of experience to, to really help customers deliver on. Absolutely.

You know, it's, so we do a show every morning, Textron Gang, and it's kind of, you know, the view meets Fox and Friends meets Morning Joe, if you will, right? It's a bunch of myself and a couple of our editors and pundit's just talking about what's cool today. And so we were this morning actually talking about AI and weather forecasting.

You know, there's an arms race in, in forecasting hurricanes and stuff. You've ever seen those spaghetti models they always show, right? Well, it turns out the European model has been much more accurate, and we have, we have a weather gap, weather forecasting gap here, kinda like right outta Dr.

Strange glove. Um, but anyway, you know, gene, it's a real world example though of where AI today, not pie in the sky, no pun intended, not pie in the sky, not five years from now today is working and making a difference. Can you give us some examples of where today this is making a difference?

Yeah, I think, you know, one of the things when I mentions that there's lots of different copilots and that that is, that is one of the things that's, that makes the examples a a wide swath, right? So we could start every, we could start from some of the most basic examples. And, and by the way, when we get into it, most of the time, you know, folks are coming back and saying, well, it's a soft ROI, it's a, it's a, it's improving quality, but, you know, how do I measure that?

And, and it's improving, maybe speed, but, you know, it's, it's really not easily trackable. And so what we see on the, on the most basic side of the, the, the spectrum there is, is this allows us to actually be much more productive in our day-to-day lives. From a meetings perspective, that's really, really boring for most of us, but it's actually very, very significant in terms of understanding how we're leveraging this.

My favorite use case is, is pretty benign. It's, it's, it's not very exciting, but when I use copilot to actually give me the meeting, meeting summaries, it actually nets out a very vigorous conversation into a couple of bullets. And that becomes a catalyst for everybody to go off and do their action items.

And so when you take an hour long and install down using copilot, it really is very powerful. More importantly though, I think where we're going with this, we're actually seeing much greater benefit in and in, and really what that means is the digitalization of the world. Your example around the weather models, that's, that's kind of already a digital world, but what we're seeing is better opportunities to bring this technology into kind of analog business processes and to expand on it.

And so what that means is we move up the stack into workflow orchestration and inject AI into that. And so one example is, is we've helped a company digitize their, um, inspection records for heavy, heavy construction equipment. So not the, not the type of stuff you see driving on the road, but very large, you know, the, the big stuff, you know, the, the things where the wheels are are taller than a first story building.

Um, and that's, that's really exciting. 'cause what it does is it drives safety, it drives, um, experience, um, efficiency and and speed to being able to get those things done. Many times these inspections have to be done daily.

And so this is, this has created a new opportunity to dig, digitize all of that end-to-end process and provide better accuracy. And so we're actually able to use AI to, to do anomaly detection in, in situations like that. I love it.

And that is, that's a, that's a real, real world thing that's happening. You know, just quickly, I was, I was up in New Jersey this weekend for a, a family relative's 80th birthday party. Surprise birthday party.

Don't make 80-year-old surprise birthday parties. It's not good for them. But anyway, and I was sitting and talking to some folks of that age, not that I'm a young whipper snapper, but they were older than me.

And we, this whole AI thing came up and I took out my chat, P King, I had to create a few photos, then I took photos and asked chat GP to write a narrative for it. And I think, Dennis, we forget the magical element of this. The people who maybe aren't exposed to it every day, such as you or I, or people in our audience, this is truly transformative, right?

It, it's not just cheap par checks, it's transformative, the kinds of things we didn't even get into creating code, you know, copilot like in a GitHub situation or something like that. Um, we didn't get into any of that just on everyday basis using your Microsoft office. Sorry, bedwin, I know they don't call it that anymore.

Using your Microsoft 365 applications with this copilot harnessed in there and the solutions you can create. It really, I mean, 20 years ago I would've told you were doing this. You would've no way, right?

Yeah. It, it, it's, it's, it is. And, and so I think part of the effort that people like you and, and, and the NDL team face is moving from what people think of as the magical to the mundane.

Of course, this is what we do. It's how we do it every day. It's the way we've been doing it now.

Right? Where do you, when do you, when do you think this becomes, 'cause right now there is sort of that wow factor, but they don't, like, I, I see a hesitancy of saying, oh, this is, this is the way we do it now. Are you seeing that?

Or what, what do you see? I think so, and, and you know, there's, there's a lot of statistics that are out there that kind of show that it's actually being used much more than we realize in, in the workplace. And so from our perspective, you know, we tend to, our entry point is a technology entry point, right?

So we're, you know, everybody we speak to is engaged with this, but when, when we move outside of the IT space, when we move into the lines of business, when we move into, say, hr, that's actually where we see, um, adoption being a little bit, uh, More, More, I don't wanna say muted, but it seems to be a little bit more diverse. A Little more resistant. Yeah.

Yeah. And, and, and it, and the reason why is because the use cases aren't, you know, well understood, you know, how does this apply to an HR perspective or how does this apply to a line of business? But research is showing that in those lines of business, if you're not doing it from a top down perspective, employees because of the example you gave, because you opened up your phone and you used it on your phone, it's becoming ubiquitous in everybody's lives.

And so the situation here is, is really about how do the enterprises keep up with the consumer expectation, right? I mean, I, I know for myself, I'm surrounded with it. I had, um, a, a, uh, a weekend in the mountains.

So, Um, As I, and, and what that means is I was splitting wood this weekend. I was getting everything ready for, for winter in, in upstate New York. I still used generative AI three times and, and I wasn't working.

And so that idea here, from a consumer perspective, the expectation and the usage of it is raising pretty high. And so if enterprises aren't keeping up with that, if they're not injecting it into the employee's work workplace, they're figuring out ways to use it on their own. And so this isn't a, a, a, a, a message of fear to say, you better get your arms around this o otherwise employees are gonna problem solve.

It's more a message of saying, help your employees use it because you can actually maximize their productivity even further by injecting it into use cases, by leveraging, um, the, the technology to make their employee experience better, that improves retention, it improves their productivity, it makes them a happier employee. So, so there's a lot of opportunity to look at it and say, you know, how do we actually move outside of the IT space and move into hr? How do we use it for employee onboarding?

That's something that we do tremendously right now. We personalize that experience. We use AI to do new employee coaching.

How do you enter into an enterprise ecosystem and, and understand where to get knowledge and who to communicate with to do your job effectively? Um, how do you move into the lines of business and, and what are those lines of business use cases all being held up by the consumer experience that, that you articulated with, uh, your weekend? Absolutely.

Hey, Dennis, I, yeah. I promised you these are only 15 minutes. We're at 20, but this is how these things go.

I wanna thank you for coming on here and giving us a little bit of insight into what Ken Jewelle is doing around, uh, AI powered workplace solutions with, with co as well as Ken Jewelle in general. Um, don't be a stranger. You know, now you're, you're no longer a rookie.

You've been here once. Come on back and keep us posted. Awesome.

I appreciate it so much. Thanks so much. All right, Dennis, let me make sure I get this right.

Perpetua, the global CTO Digital Workplace Services and Experience offers. So Vice President, and as I said, most importantly, distinguished engineer at Ken here on Techstrong tv. We're gonna take a break.

We'll be back in just a moment.