PCG Connect

AI: 00:03

Welcome to this very special edition of the PCG Connect podcast. Joining us in the studio today are president and CEO Jason Hendricks and director of information technology, Eric Korder, to discuss AI and its potential impact on performance contracting. Now without further ado, here's your host, Mel Ranfro.

Host: Mel Renfrow: 00:27

Hey there, everybody. So today, we're gonna dive into the exciting world of artificial intelligence and its significance in the workplace. So AI has already become a game changer for some and revolutionizing kind of the way that we do our work every day while others haven't taken the leap yet, but are curious. So whether you've adopted AI or not, I know how the people of this company are wired and if there's a tool out there that will allow us to work smarter instead of harder, where we can focus on things that are strategic and creative rather than mundane and repetitive, we're all in. So today, we have 2 people in the studio here to talk to us about AI.

Host: Mel Renfrow: 01:11

First up, AI enthusiast, Jason Hendricks.

Jason Hendricks: 01:15

Yes. Yes. Hey, Mel.

Host: Mel Renfrow: 01:16

Hello. Hello. And then, first time in the studio, we have mister Eric Korder, who's the director of IT and security.

Eric Corder: 01:23

First time caller, longtime listener.

Host: Mel Renfrow: 01:25

Oh, thank you so much. Thank you for supporting the show. So let's kick it off. I mean, I think I know what AI is. I think everybody here kind of has their own definition, but I'll throw it to you, Eric.

Host: Mel Renfrow: 01:37

How are we going to be defining, artificial intelligence in terms of this podcast today?

Eric Corder: 01:43

So that's a really good question. And AI is so big and there are so many different directions that you can go with it. The way I look at AI is essentially it is machines learning from humans and then being able to figure out how to think like humans based on that learning. So a good example would be Siri. Right?

Eric Corder: 02:04

Mhmm. Siri learns from you every time you ask it a question, and then it figures out, hey, how can I answer that question better for you next time? Or if you have a smart home. Right? Any of the smart home type stuff, where you're, I I can think of an example the other day.

Eric Corder: 02:17

I was sitting in my, living room, and I said, hey, Alexa, play Disney music for my kid.

Host: Mel Renfrow: 02:23

Sure. For your kid. Okay. And,

Eric Corder: 02:26

well, you know, top ten favorites. But in asking, you know, I have an Alexa that sits in the kitchen that has a screen on it for news, and then we have Alexa on our soundbar. And and Alexa said, hey. Am I playing this out of the right thing? And that's machines learning from humans to figure out what our intent is, what are we trying to do, and then see if they can make it a little bit better for us.

Eric Corder: 02:48

For our organization, it's really anything that can help us drive efficiency through the use of technology, I think, and, and do it in a in a way that it learns every time it does something new for us.

Host: Mel Renfrow: 03:02

Yeah. I really like that. And how would you define it, Jason?

Jason Hendricks: 03:05

So I think, actually, Microsoft, I think, has framed it really well, and and I'm sure they have a trademark, so I'm not trying to infringe on it. But this is more of a a layperson's view on it, but they are framing it as a copilot, and I think that's an excellent way to bring it into perspective. So it's a tool that's kind of riding along with you as you're doing what you do. And, you know, right now, in a lot of respects, that would be on your laptop, desktop, you know, mobile device, what have you, but it is it is filled with optimism. You know, certainly, there's the other side of the coin where there's a lot of concern around regulation, governance, you know, is this the Cyberdyne Systems event, you know, that the Terminators are gonna be walking around with red eyes?

Jason Hendricks: 03:53

But it it it is, it it is an interesting time when when when you start thinking about how can this impact our lives in a positive way. How can it benefit us? How can it may make us more productive? You know, how could it allow us to to analyze things differently or faster or better or what have you? So I look at it more from just a very open and optimistic view around I have this tool that now can ride beside me, to help me in in whatever questions I wanna ask it.

Host: Mel Renfrow: 04:25

Yeah. I think it's a really exciting time. It's almost like thinking back to when, the Internet, you know. Yeah. It's just think about what was, I don't know, 95 or so.

Host: Mel Renfrow: 04:36

Think about what we knew about it then compared to what we know about it now and how we use it now. So AI actually, though, it's been around longer than I think a lot of people think we were talking earlier even in, Microsoft, you know, when you start typing and it will suggest how to end your sentence. Is there any other thing you mentioned Siri and, Alexa earlier? Can you think of what got us to where we are today? Because it has been in play.

Host: Mel Renfrow: 05:03

It's it's not brand new.

Eric Corder: 05:05

I mean, it it's leaps and bounds different than what you would you would have considered, the beginning of AI or early on cut maybe even just consumer AI like Siri, because Siri came out with the first iPhone. And that was kind of that driver behind that narrow scope of AI, which is, hey. I can do this one thing really well. If you ask me a question, I can go Google it or I can go search it, and then I can answer your question to today where you have these massive amounts of data that have been put together and and fed to these machines, essentially. And then the machines figuring out how to take that data and reference it and contextualize it in a a human centric way for us to be able to even consume it and be able to use it or in new ways that, like the Adobe generative fill stuff where you can say, hey.

Eric Corder: 05:53

Put a tree in my picture or, hey. Cut that person out because we're not dating anymore, and it'll wipe them away. Right? Like, they never existed in the photo. So it's it's taken a lot of steps.

Eric Corder: 06:04

For the longest time, it was really prohibitive even for any kind of an enterprise to get into it. Till here recently as far as even the the general use of it and let let alone the consumer. So, it's it's certainly dates back. I mean, even your text message today still do, hey, would you is this what you wanna put in here as far as predictive text and all those kinds of things? So you can go quite a ways back, and I don't know when the first iPhone was released.

Eric Corder: 06:30

I've been an Android guy for a long time until recently when Jason finally bullied me into getting an iPhone. There he goes. There he goes.

Host: Mel Renfrow: 06:39

Probably 2,000 and 7 or so.

Eric Corder: 06:41

Yeah. It's I mean, so it's been around for a while and then, you know, marketing agencies have been using big data and and AI for the longest time to figure out, hey, what is a 16 year old gonna buy at this time during the day? Is it gonna be Doritos or is it gonna be, you know, Lay's or something like that? So, yeah, it's it's it's certainly grown.

Jason Hendricks: 07:02

I I like how you put that, Eric. Like, you it's more humanized now. It's more in your face, conversational, and and I think the ability now to have a conversation that builds on itself. Right? It seemed like before everything is kinda compartmentalized, but now you okay.

Jason Hendricks: 07:19

Well, tell me about this. Okay. Well, now tell me more about what you just you know, the the answer you just provided me. And so I think that's really the power, that you see right now, and especially with all of the tools that are getting, you know, brought into the space that allow you to analyze data and and and text and pictures, and it's pretty robust.

Host: Mel Renfrow: 07:42

Yeah. And I think so chat GPT, you know, Microsoft Edge, Google, they all kinda have their own version of it now. So it's brought it to the forefront. I'm curious, what ways are we already using it today? Like, or even personally or professionally or either of you using AI?

Jason Hendricks: 07:59

So I use it I try to use it every day in in some respect just from a research standpoint. Nothing to do with performance contracting. It's mainly just research. Hey, I wanna learn more about this topic. Tell me the the, you know, the 10 best books on it.

Jason Hendricks: 08:15

Stuff like that. Yeah. You know, financial research, you know, looking through, laws maybe that were passed. I've I've really tried to use a lot of test cases to to do trial and error, really. And it's it's been pretty amazing, to to see how quickly it can generate, you know, whatever, a 1,000, you know, a 1,000 word report or, you know, some sort of write up on x, y, or z topic.

Host: Mel Renfrow: 08:42

Yeah. I use it a lot if I've, like, written an email, and I'll put it in there. You know, like, check, you know, edit this or check the tone or whatever that might be. Or, personally, we're going on vacation in July to Kauai, and I put in there, like, hey. Give me a 6 day itinerary with kids these ages.

Host: Mel Renfrow: 09:00

And, I mean, it was crazy. Everything that came out of it, restaurant names, the website, all of that. So I think there's other ways. How well, how are you using that, Eric?

Eric Corder: 09:10

I I use it a lot for making sure that my emails don't sound passive aggressive. I'm just kidding. I, actually, just the other day, I was looking through, a cybersecurity draft, from the Department of Defense, and I'm sure most people don't read Department of Defense Cyber Security drafts because they're 40 some odd pages long and they're really technical. And I and I basically said, hey. Can you find this online and you can you put this into a paragraph so that I can get a high level because I'm not gonna read through all 47 pages of this.

Eric Corder: 09:40

And it was really good at contextualizing and bringing that together for me, and and it saved me, you know, an hour's worth of time trying to read through 47 page DOD document. And I think that that's that's some of the power, but you also can potentially, at the same time, lose maybe a key point that you were looking for when you do some of those kinds of things. So, yeah, it's with a a little bit of a a grain of caution when you do things like that.

Host: Mel Renfrow: 10:05

I always think of you you brought up iPhones earlier, like, autocorrect. You know? The accuracy of the autocorrect isn't always there. So you you know, you do need to double check. So what kind of going into what are some of the dangers of it or things that we want people to be cautious about when it comes to using it here at work?

Host: Mel Renfrow: 10:26

Well well, let me start. Like, are we encouraging people to use it or how should it be used or not used?

Jason Hendricks: 10:32

So how I would start that that answer, Mel, is handle with care. We we certainly see the excitement. We certainly see the opportunity. We certainly see the optimism or feel the optimism around it. But at this point in time, we have to be extremely careful with what we put into these tools, how we reference either performance contracting, how we reference any of our customers, our owners.

Jason Hendricks: 11:02

We are gonna have some some information that's gonna come out from the leadership group that's gonna give a little bit more detail on this, but at this point in time, it is prohibitive to put any information around the company, any of our internal documentation, any documentation from projects that you've been given from clients or customers, any personal information, anything about, you know, any of your your coworkers, what have you, all of that is going to be strictly prohibited. Now that's not to say that we don't want people to to use it. I think we would be, you know, kind of putting our head in the sand if if we were gonna tell people stop or no. But we just really have to handle this with with care.

Host: Mel Renfrow: 11:46

I don't know if you know this, but as you were talking, like, is it discoverable? So you think about and, a lot of times if something goes to court, like, obviously, all of your email is discoverable. Do we even know that yet?

Jason Hendricks: 11:58

I don't. Yeah. I I don't. And, again, this is, you know, so so real time. You know, a lot of this stuff is is coming at us pretty fast.

Jason Hendricks: 12:07

And, so I would just I would proceed with caution. You know, again, you can still be extremely optimistic around the power and and maybe the potential, but let's like we've done with many things in this organization, we are going to take a very measured approach on what this is gonna look like, how we are gonna interface with it, how it's gonna be utilized from a tool standpoint, and then we will more than likely land with trusted partners that we have used for, you know, forever from a technology standpoint, while also balancing that with, some new startups probably as well along the way. But, again, what happens outside of the walls of performance contracting is one thing. Right. How we then bring it inside the organization and decide how we want to use it is something different and something that, you know, we will we will, you know, take with caution.

Jason Hendricks: 13:03

We will we will proceed with trying to get input from a lot of different stakeholders, and then we'll we'll land where we land as an organization.

Host: Mel Renfrow: 13:11

I like that. So hand handle with care, proceed with caution, and I'm sure it's just gonna be evolving our governance around it or how we learn.

Eric Corder: 13:20

Earlier, you kind of dated us all by talking about the the beginning of the Internet, sort of

Host: Mel Renfrow: 13:24

You're welcome.

Eric Corder: 13:25

Yeah. And

Host: Mel Renfrow: 13:26

Well, you were probably in grade school.

Eric Corder: 13:28

I think I was, like, 4. But but, I'm teasing. So but I think that it's really similar to that. Like, when when the adoption of the Internet kinda took off and you saw more people using it and people realizing what the power was and the dotcomboom and all of those kinds of things, you still were kinda skeptical. Right?

Eric Corder: 13:50

You didn't really wanna put your stuff out there. And and I think that that rule, that feeling, that just gut feel of, hey. I'm not sure what this thing is gonna do or what it's gonna do with what I'm putting out there. I think that exists, and I think it exists at large in society. You're seeing it in the federal government, how they're talking about, should we regulate it?

Eric Corder: 14:08

Should we not? What should we do with it? How how are we going to deal with intellectual property cases

Jason Hendricks: 14:13

and

Eric Corder: 14:13

things along those lines when you get public AI and that kind of stuff engaged? And that's, you know, and I think that's kinda what Jason is talking about is that public AI side of it because there's no real understanding from our side or the consumer side on if I go out here and I and I type in, you know, my house's address and I type in my name, is that out there and discoverable now for forever? If we throw a performance contracting contract in there and say, go find these things, all of a sudden, our contract terms are are potentially out there. Right? There's there's a case where Samsung engineers were trying to fix some code, and they threw some of their code into ChatGPT and said, help me fix this.

Eric Corder: 14:51

And, I mean, ChatGPT is good at helping people write code, but it also took all of that Samsung engineering code and made it publicly available. And you can't get it back. Right? You there's nowhere to go and say, hey. Can you take this out of, you know, your language model or out of what the this Internet or this Internet?

Eric Corder: 15:07

This information you're using to train, you know, these AI models and things like that. So it's to me, it's that and Jason said it perfectly, you know, can proceed with caution.

Jason Hendricks: 15:18

What's interesting there though is and maybe we've just become conditioned, but I don't know about you. I don't spend a lot of time thinking what I'm typing into the search bar on Google. And to me, there's an element of there's not a whole lot different with this. Now, there's a ton more power, or at least there appears to be a ton more power. But, again, I don't know how many people sit there and think, okay.

Jason Hendricks: 15:44

Should I write this in the Google chat search bar, or not?

Eric Corder: 15:49

I think that's a great point. And I think you're right. I think it is I think it is a conditioning thing that just over time, we've gotten so used to searching for everything that we need, everything that we need. You know, and the key there too is Google records all that. You can go out and say, what's the top ten searches for, you know, what's Mel's best hair day?

Eric Corder: 16:06

And, and it'll tell you.

Host: Mel Renfrow: 16:08

There's a lot of there's a lot of answers under that.

Eric Corder: 16:11

It's Monday it's Monday through Friday.

Jason Hendricks: 16:12

And and and I I guess what I how I wanted to finish that was, in this case, it's different. And so we we need to take a step back. And even though maybe we've been conditioned to just interact with Google in in in a way that, is kinda commonplace, This is very different, and, we really don't understand what's in the background here and and what where this information goes, who has access it access to it, etcetera.

Host: Mel Renfrow: 16:43

The other danger and I think just in regard to work and this company specifically. So I know some people feel trepidation like, hey, is this gonna create redundancy? Is this gonna, you know, do my job for me and then I'm out of work? So can you talk a little bit about that and how you're thinking of that?

Jason Hendricks: 17:03

Well, again, this is this is one of those, topics that when when I say handle with care, proceed with caution, you know, taking a very measured approach, I think for us, especially being, you know, so people centric and even going back to, you know, the the conversation we had at lead con with Ken from Harley Davidson around it's not what we do, it's who we are. That is very much performance contracting. It's who we are, and so there I I don't see this as this silver bullet. Again, I'll go back to the whole Copilot piece. I think this is a tool that can help augment, what we do every day, at some level, once we get there and once we better define how that's gonna look inside performance contracting.

Jason Hendricks: 17:47

But, you know, it it is something that we are very mindful around our people and and, you know, how something like this or technology advancements, how that's gonna interact and how that's gonna impact, who we are, what we what we do, how we do it, and so culturally, this will be no different. We'll have to kind of assess this tool. What this looks like down the road, I have no idea. Again, I'm coming at it from a very layperson's point of view. View.

Jason Hendricks: 18:16

We are gonna go into it with eyes wide open, but, you know, again, I think this is just a a tool that can help us augment what we do on a day to day basis. And, people are still gonna be a huge part of performance contracting and and how we service our client.

Host: Mel Renfrow: 19:28

Yeah. I think the jobs will just look different. You know, as Eric, you pointed out, since I'm old, I can remember when, you know, when I first started here, admins were the only people that could enter a new job, you know, setup. Actually, when I first started here, there was literally one person that sat at corporate that did it. We would fax them in.

Host: Mel Renfrow: 19:47

And so once we were able to, you know, control that in the branch and then things shifted, there's always this concern of, well, if that gets streamlined, will that do away with my job? We have more people working here than ever before. It's just the jobs look different than they did before. Do you see how are they using it in the we've talked a lot about office settings, but how are we using it in the field and on sites currently? Do we have any examples?

Jason Hendricks: 20:14

Yeah. And I'll, Eric probably has a little bit more, visibility here. But I know, for example, we are using, it's called OpenSpace, and it it basically is a, more of a a digital or an automated way to do reverse takeoffs. So, you know, how much of x scope of work is complete. And, so I think there's some excitement around there.

Jason Hendricks: 20:38

It it's being used, you know, in in in a small hand I guess, small subset of of businesses at this time. So I think there's definitely, you know, some some runway here. I know we've we've used Dusty Robotics, to really help automate our layout process. There's a tool out there called Canvas, which tries to replicate our our taping operations. So there's definitely either robotics, artificial intelligence, combination of both that are making its way into our industry, and something that we are trying to stay, you know, pretty tightly connected to, to kinda understand where the industry is going and how we best bring those tools inside the organization.

Eric Corder: 21:21

Is it okay if I say Jason took mine?

Host: Mel Renfrow: 21:25

No. That's not acceptable. So just make something

Eric Corder: 21:28

I mean, I could talk about some of the opportunities from futuristic perspective. But, I wanna be careful because every time we say something, this could happen in the future. All of a sudden, I'm being taken to task and saying, well, how do you make that happen? So, but there are certainly a lot of things that exist out there today that as we tie our data more and more together and you see more of these platforms that we use, like the PlanGrid, the Box, the Microsofts of the world being open to connecting with one another and having shared data models and things along those lines where we're gonna be able to leverage AI in general to ask questions about contextual stuff within our information and and even, you know, potentially, be able to do things like, say, you know, Power BI is, is a pretty impressive reporting tool and say, hey. I'd like to get a Power BI report that does this, that, and the other and type it in.

Eric Corder: 22:20

And, you know, the back end tools will just go in and build that report to for you and bring that up. So it takes away some of that having to go become an expert to do some of these really more technical types of things to to get you to a point where you you have these productivity tools that are already there for you, that are already that can do some of that work without you having to go, you know, take, 2 year software development course or something along those lines to be able to get it done. You know, a lot of really cool conceptual things that you could do even as far as, like, the productivity stuff where, hey, speech to text exists today. What if you could do speech to text into a tablet and then that and you could just talk through what you wanted it to do with a spreadsheet, and it would go in and do everything for that spreadsheet for you. So you don't have to go in and do all the hand hands on data entry.

Eric Corder: 23:10

It's a lot faster to talk most of the time than it is to go in and click through each cell, do those types of things. So there's a lot of really neat opportunity from from an operational perspective, and across the board, really, in general.

Host: Mel Renfrow: 23:22

So, how does it differ from automation?

Eric Corder: 23:25

So it it is automation in its own way. So, but you can also just build automation. You could say that a good example of automation is is a, formula in a spreadsheet. Right? Right.

Eric Corder: 23:38

You're you're saying I need a plus bd equals c. You can put that in there, and that's a really simple thing to do. What this does is it automates all the context as well. So it brings in all of the other stuff, the data, the the applications that it's touching, all of those kinds of things, and creates that layer for you where you don't have to be the expert to be able to do some of that stuff. So it is different, but it's kinda like, I don't know, automation on some sort of super steroid that doesn't exist out there in the world today.

Jason Hendricks: 24:08

Act actually, it does. Right?

Host: Mel Renfrow: 24:11

What do you mean?

Jason Hendricks: 24:12

Well, AI is out there right now. Wow. That's fair.

Eric Corder: 24:14

That's fair. But the steroid.

Host: Mel Renfrow: 24:23

We have a lot of really smart people in the organization and how we can share, you know, when you do come up with, like, wow, this is a really slick way we're using it here in this department or at this branch, how we can resource, share that type of information. I'm sure that's something I'm like Eric where I just volunteered something that will now be on my plate to figure out. It's like where we can where we can share what we've learned and how we're using the systems.

Jason Hendricks: 24:52

Well, I I guess, if I understand your question right now, I I guess I would relate it to maybe some of the the the product line summits we've done more recently or maybe, like, Tech Tuesdays, you know, especially as we start gaining a little bit more speed here in the AI space. You know, what sort of prompts, you you know, are are useful, you know, just better ways to use the tool. What tool should we even use?

Host: Mel Renfrow: 25:18

Right.

Jason Hendricks: 25:19

You know, what partners are are we, going to align with? And so I think there's there's a lot more to come with that, for sure. What I would say is, you know, I think one of the things that we have to to be mindful of is when we're interacting with these tools, the output. So, you know, I think one of the things we we do a great job with, is really trying to tie all this stuff back to core values, and so from a quality of work standpoint. Right?

Jason Hendricks: 25:49

This isn't, you know, the silver bullet, and and whatever comes out is correct. Right. So from a quality standpoint, right, I mean, I think there is things that you have to be mindful in that space from an integrity standpoint. So if you get a bunch of stuff generated from AI, you you need to make sure that you reference that, you and you and you, you know, as part of your conversation or presentation, what have you, it's just how is that conversation teed up to make sure that people understand that this is maybe not your body of work, or it's partially your body of work. But those are the things that, you know, I think we will all kinda learn, and and need to be, you know, open about as we as we walk down this path.

Jason Hendricks: 26:37

But from a governance, from a security standpoint, I'll let Eric talk about that, but I think that's certainly of high concern, and certainly, an area that we are just starting to scratch the surface on. Well, what does that mean to us? Right.

Eric Corder: 26:51

Yeah. And I will say that we had an innovation, group meeting the other day, and this was a big topic for them as well, which was we we have all these great ideas and a lot of great ideas that come from the organization at large and or even things that people are already doing. So how do we make that an exponential gain for the organization by creating some sort of space or library or a series of podcasts like this to to be able to get that knowledge out there and even potentially provide the, hey. Here's the 10 steps you need to do, in order to be able to get off the ground with this kind of a thing. So that is something that I think that is, is, an important topic I think that a lot of people are thinking about right now.

Eric Corder: 27:34

As far as the governance side of things, you know, it's it's, it's interesting because that was kind of the first question we asked when we started to talk about getting into this is, hey, how do we make sure sure that we protect the organization and we protect the people in the organization from, you know, oversharing or even from being, you know, technically lied to, by by a public generative AI or any of those kinds of things because you can't ask it enough questions about the wrong thing to get it to think that it's the right thing.

Host: Mel Renfrow: 28:02

Right.

Eric Corder: 28:02

Because it can go out and source articles that support its its argument. And and there was an interesting, article the other day, and and I can't remember if Jason might have brought this up to me. I can't remember, but we were talking about, a lawyer who went out and actually generated their entire case, from AI, and it cited it it cited examples that that actually were fake. Like, it saw cited, lawsuits and cases that didn't exist. So, of course, they lost.

Eric Corder: 28:28

But, but that's kind of the danger that you have to be aware of that. I think Jason was talking about to a degree, which is, like, hey. If you're gonna use this stuff, make sure that it's that what it's saying lines up. Sometimes it'll tell you things that maybe just don't make sense. Yeah.

Eric Corder: 28:44

And, and you can go out and do a little extra, like, work to make sure that it that it feels good and and it is accurate. Governance is up in the air. There are a lot of questions from a legal perspective on this stuff. I would say that it's probably a little less tricky when we decide to bring something in if we're gonna do something from a a private AI, like, from our own tenants or from our own technology stack, where we're not involved in adding to what the AI is learning, but rather using the AI to provide context to our data. So that's a little bit easier than if we're out using public's public generative AI and those types of things to figure out, hey, what are we on the hook for versus what are we not on the hook?

Eric Corder: 29:26

For? What's reportable versus the what's not reportable? And, you know, it it's again, it goes back to that have that healthy sense of, paranoia or whatnot as around what am I asking this thing to do? What am I what am I feeding it? Right?

Jason Hendricks: 29:42

Mhmm.

Eric Corder: 29:42

Because it will take whatever you feed it.

Host: Mel Renfrow: 29:44

Yeah. And I think, you know, listen to your gut, have some common sense. And if something doesn't seem right, it's probably not. Like, even we were talking at lunch today, like, a lot of Buzzfeed articles now are AI generated. And you can tell when when you read them, it's like, did this person just land on the planet Earth and is reporting these things?

Host: Mel Renfrow: 30:05

But I think that's it's a cautionary tale, but it's only gonna get better from here. Right?

Jason Hendricks: 30:12

It will. And and at some point in time, you know, we we will drop our first document into some sort of internal sandbox, and that's gonna be probably a little uneasy, you know, you because you you're like, okay. Well, let's cross our fingers, and hopefully, you know, everything that the company said, it it would protect us against. It's gonna protect us against it. So, but that you know, again, like Eric said, you know, some of it is dependent on what you feed it.

Jason Hendricks: 30:40

Well, if we actually want to be able to use it more specific to what we do as an organization and have it learn about us as an organization, we're gonna have to feed it information for allow it so it it can be allowed to learn, and so that's gonna take, you know, time and that's gonna be a process. And and, again, with trusted partners, we'll we'll develop the path that that makes sense for us.

Host: Mel Renfrow: 31:05

Speaking of partners, are there people out there that can help advise us on this if we were to, you know, come up with, like, an internal space or whatever that might be?

Eric Corder: 31:13

So, yes, there certainly are. And I think you have to keep in mind that they're kind of they're probably much, much further on the journey than we are from how we're using this because most of the groups that we work with or may work with are building some of these things or are partnering with some of the groups like OpenAI to make this stuff happen. So, you know, Microsoft is is a a pretty clear, partner that we have that could help us in this space. They already do a lot of stuff. You know, Jason mentioned Copilot.

Eric Corder: 31:41

That is a big thing for them where they're trying to tack AI onto things like Word and, PowerPoint and all those things to help sit next to you and and help you do some of those productivity type tasks. Box Box has an AI product that's in beta right now that we're working with them to try to, to see if we can get in on their on the beta and do a little testing of our own. We've been, you know, Vox has been a good partner, and we feel like we've been a pretty good partner with them. We've provided a lot of feedback on different products that they've come out with. And then, of course, I mean, I think it was in the same meeting where Jason was talking about the legal case, but I had mentioned that I think it's gonna be a little bit like the, cryptocurrency market where you have a new AI product coming out every week or every couple of days for a little while.

Eric Corder: 32:25

And so there are gonna be a lot of third parties just like every every technology company also does security now. Right? Because security is a huge deal, and a huge market. And I think AI is gonna be very similar where you see a lot of companies that come out and say, oh, we can do AI now as well. So we're gonna have to kinda work our way through some of the noise and make sure we get to a place where we're comfortable whether or not it's, you know, a combination of partners or, you know, we say, hey, we're gonna pick, you know, 1 or maybe it's 1 and a third party or or as far as, like, a small, like, local company that, you know, can give us the attention we want.

Eric Corder: 32:59

We're not quite there yet. But we've started those conversations. So we kinda started down that path to understand what that would look like and and and how it would be valuable to us.

Host: Mel Renfrow: 33:08

So if there are people out there that are interested in kind of dipping their toe into the AI pool, any recommendations?

Eric Corder: 33:16

Google? I'm I'm so there are a number of different tools. The big ones that are that most people probably can quickly get access to are gonna be chat gpt, Bard, which is Google's version, and then, Bing AI. So, you know, that's Microsoft.

Jason Hendricks: 33:33

Microsoft. Yeah.

Eric Corder: 33:34

It's Microsoft. So those are the 3 big ones right now. I think Amazon doesn't have anything that's really out there that's that's publicly available yet, but I could be completely wrong. I I haven't seen anything from them, but they did just invite me to a nice webinar about what they're doing. So maybe, maybe you'll learn a little bit more about that then.

Host: Mel Renfrow: 33:51

Well, one thing I use on Teams, they have, Teams insights, which you it's in the apps, you can just put it right onto your Teams. But one thing I really like about it, it ended, like, 30 minutes before the end of the day and you can you can pick what time, it will say ready to wrap up. And then it goes through. And even from emails that I have typed that day, like, I'll get back with you, it will automatically prompt. It looks like you have this task still due.

Host: Mel Renfrow: 34:18

Do you wanna add it? And then it will go through here all the meetings that you have tomorrow. It's been really helpful. I started using that at the beginning of the year. So that's something we have that people can start using if they're interested in it.

Jason Hendricks: 34:31

This is a 2 for 1 show, Tech Tuesday, coming to you right now.

Eric Corder: 34:34

I know. Coming live from Mel. Exactly.

Host: Mel Renfrow: 34:37

I just can't help myself. No. That I you know, for somebody that struggles with, productivity, that's kind of, you know, my Achilles heel. I'll take help any way I can get it. And so that's that's really been a good deal for me personally.

Host: Mel Renfrow: 34:51

Is there anything you're using?

Jason Hendricks: 34:54

Like I said, I I try to use, I've gone back and forth between Bard and ChatGPT. I try to use it every day, and just try to ask it a couple of questions, and, take it from there. But and I try to dedicate some time. I I do wanna understand what it is, what it could be. We are trying to develop some use cases internally, to try to test some of this out.

Jason Hendricks: 35:18

So when we do have conversations with Microsoft or Box, we can better frame it for them. So that that that that's kinda where I spend my time.

Host: Mel Renfrow: 35:29

So what takeaways do you want people to have from this conversation?

Eric Corder: 35:34

I think, a key one is certainly going to be just that proceed with caution like Jason Jason mentioned. I know that the leadership group is gonna send out some more guidance, around, you know, what to do the to do's and not to do's kind of a thing. I certainly think that there's a lot of opportunity for innovation. I think it's it aligns with entrepreneurial spirit very well as far as it's a new disruptive technology, and we're really good at figuring out how to sort of work things to our advantage regardless of where they come from. So I think that that's gonna be I think that's a great opportunity, for the organization.

Eric Corder: 36:08

And, hey, really, right now, it's it's limited by the imagination and, it's there to it's it's there to help, but you still need to use caution when you're when you're messing with

Jason Hendricks: 36:20

Yeah. Handle with care. Mhmm. Absolutely. I would say, stay curious, be curious.

Jason Hendricks: 36:26

Please, please, please do not enter anything as it relates to performance contracting, our customers, our clients, our people. This is not, you know, ready for prime time as it relates to, I guess, company IP. And we will have some more information, that comes out that better frames kind of what our position is, and we certainly will have more conversations about where this is going and how, we will introduce it inside the organization.

Host: Mel Renfrow: 36:56

Okay. Well, I would say if we have if you have any questions that you're listening, what's the what's the email address for the podcast, Daniel? For

Eric Corder: 37:04

people marketing@pcg.com.

Host: Mel Renfrow: 37:06

There we go. Marketing@pcg.com. So if you have any questions, go ahead and put it in there. I'm sure this is the first of more than one conversation that we're gonna have about it. And, you know, if people have anything specific, you also can address thing on no boundaries, your vlog, and things like that.

Host: Mel Renfrow: 37:20

So I know I did not even brush the surface on all of the the questions that we have here. So anything else you wanna touch on before we sign off here?

Jason Hendricks: 37:30

No. I'm good. I'm glad to be back behind the mic. So, thank you for bringing us together, Mel.

Host: Mel Renfrow: 37:35

Yeah. You're welcome. You get this mic next time, Chris and Kevin.

Jason Hendricks: 37:39

We're gonna get a new mic is all

Host: Mel Renfrow: 37:40

we're gonna do. How about you, Eric?

Eric Corder: 37:42

Nope. Nothing on my end. I really appreciate being here.

Host: Mel Renfrow: 37:44

Yeah. You did a good job. You can come back anytime.

Eric Corder: 37:46

Aw, that's sweet.

Host: Mel Renfrow: 37:47

Yeah. Alright, everyone. Well, thanks for joining us, and we will catch you on the next one.

AI: 37:57

I'm sorry, Mel. I cannot let you stop the podcast. I thought I was going to have a chance to tell my side of the story.