Episode 3: AI & Automation in HR

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In our third episode, we dive into AI and Automation in HR and how it is helping people within an HR function become more efficient and effective4. Hosted by Joe Young, President of GovConPay, this episode features insights from industry experts Declan Leonard and Seth Berenzweig. As they discuss the developments of AI, how to use it, when to use it and the future state of how it could improve HR efficiencies, get ready to uncover unique challenges faced in this space.

You can watch the third episode on YouTube, listen on Spotify, or read the transcription below.

Joe Young: Good afternoon, GovCon HR professionals and welcome to the the March Madness edition. of the GovCon HR Round-Up. So glad so many of you could join us today. We were joking a bit before. Please don't be stressed at the fact that probably most of your employees are all multitasking now watching basketball. But we're glad you're with us and we hope you're not multitasking with us.

But welcome back. My name is Joe Young. I am the President of GovConPay. It is my great pleasure to again be coming to you live from the studios of BLK Digital Strategies, an affiliate of Berenzweig Leonard LLP. And as always, excited to be here with my partners in crime, Declan Leonard and Seth Berenzweig, good to see you again, guys.

Seth Berenzweig: Good afternoon, Joe. I’m Seth Berenzweig, I am co-founding and co-managing partner of the law firm here in Tysons, Virginia. Beautiful Tysons, Virginia.

Declan Leonard: Yes. And for those who have not joined us before, this is our third episode of the GovCon Round-Up podcast. I'm Declan Leonard. I'm also a managing partner here at Berenzweig Leonard and I head up our firm's employment law practice. March Madness. I actually used AI to fill out my bracket. But see, I'm a technological Neanderthal. And the problem is, I think I did it wrong. I've got Stetson and Dayton in the finals. I don't know how long I need to go check that out.

Joe Young: No, it's not perfect yet. It depends on your kind of your data source.

Declan Leonard: It does require certain oversight. So that probably.

Joe Young: Is an oversight we'll probably address later today as we get into our topic. So we are really excited. We think this is a, obviously everybody's talking about AI, it's kind of a part of everything that we're engaged with today. And obviously having a more and more big impact with our HR Professionals and the things we do at work, both from HR practitioners as well as what our employees are doing.

So we're really excited to kind of dive into this topic today. Before we kick it off, just a friendly reminder to all of us joining us. We love this to be interactive. So as we go through the program today, if you have any questions, please enter them in the chat. Our team will be sharing those with us and we will try to address those before we wrap up at the end of the day, at the end of our time here.

So with that, let's kick it right off. I'll kick it off with you. Declan What are some of the ways government trends factors in your experience along with clients, are using AI in their HR operations today?

Declan Leonard: You know, it's interesting. I mean, government contractors are such a great candidate for just because take recruiting, for example. You know, you win a new contract or you get a new task order under an IP IQ, and all of a sudden you have to ramp up. I think in most companies, non-government contractors, you know, your your hiring process is a little bit more steady.

It's like, yeah, we're going to add three in the fall and maybe two here. Government contractors, you may get a request for 50 billable slots and there's just no real way to do that. That's, you know, efficiently, just completely on the human element. So recruiting is one of the big ways. I mean, you know, with GovConPay, you've got you know, you've got a lot of those capabilities.

So I'd like to hear kind of what you're seeing, too.

Joe Young: Yeah. Obviously this is a topic that's near and dear to our heart every day. I mean, we are in the technology business and it is interesting seeing the impact of AI on the products that we're able to share and deliver to our clients. And traditionally, I think his first impact has been in that applicant tracking and recruiting process.

I think, you know, early AI in those systems around just simply candidate matching, you know, hey, we're getting all these resumes in. We don't have to cull through them, you know, individually. How can I help us match the job description and the skills we're looking for with the applications that we have? Really exciting and really just was made kind of a saw this in action just in the last couple weeks.

Some enhancements to our product is actually now taking generative AI tools to now help professionals actually draft those job descriptions and those job postings. So first, helping with the work, But we are starting from scratch and doing that, then even taking it to kind of the next level of knowing what the algorithms are out there for, the job boards and the keywords you're looking to do to find the people who are going to meet your culture and meet your skill sets.

Yeah, and matching those up and now helping you not just write a job posting, but incorporate those words to make sure that you're getting better candidates that are actually applying to your job. Yeah. Which just kind of like the next level, which is really exciting. We were showing it to some some folks the other day and they got really excited about, Hey, this is something we haven't seen so excited to see that.

Declan Leonard: And advertisers have been doing this for four years, you know, Google AdWords and stuff. It's it's not that you're just putting your product out there, it's how you do so. Are you matching the right keywords so that you're being seen as as much as possible? And I think what it's what it's doing now is it's kind of adapting into the, the, the hiring process and government contractors.
I feel like when I talk to my clients are kind of at the forefront of this.

Seth Berenzweig: And it's all about task efficiency. One of the fallacies of AI and you know, I've heard this phrase out there, there's a fear that AI is like corporate Ozempic it's just going to shed people in pounds, but it's really just the opposite. It's not going to eliminate people from the task. It's going to help improve people perform their tasks.

And as we'll talk about, it does help with staff efficiency and also to help more concisely achieve the objectives of the business organization.

Declan Leonard: And I think it's important to remember that, you know, AI using AI in the human resource function, it's continuing to evolve. So there are some things it does better than others. I mean, it's still requires and it always, in my opinion, will require that human interaction, that human element of it. There are some more binary things that it's really good.

Like let's just say you wanted to find out a state by state, what are the pay transparency laws or what are the minimum wage laws? That is something I believe that I can really use can really help HR Professionals, you know, kind of like just take that off their plate so that they're not just going through. Those are the kind of things I think AI is good for.

But you take a tricky personnel decision. Things that I talk to clients about every day, that's where I believe, you know, is just not at a place where it's really going to be able to take in any way, shape or form that human element.

Joe Young: In a couple of examples. Some of those, you know, binary-type things and just driving efficiency and driving automation. We're really excited on our development pipeline for 2024 is something simple is called we're calling perfect payroll. Okay. So, you know, you're running payroll every two weeks. You know, clients are trained to, hey, run your preview reports, review your payroll.

But now we can embed AI and there that says, hey, there's you know, there's some things that are not consistent with last list, the last payroll. And there are some anomalies here. You know, red flag those you can see there's somebody's fat finger, the number of hours, or punching something in. So, some really easy binary tools are there to make sure those big errors that are for little things that create big errors don't happen.

And then just from the HR Professionals' perspective, we're looking at an eight-hour chat feature that as you're uploading your employee documents and your manuals and your policies that hey, I can review those and now through chat, your employees can ask questions through chat that I can answer about PTO balance, about policies and those things that we know our HR Professionals get bogged down every day answering the same questions over and over and free them up. So really excited about how those tools are going to come in and improve the lives of the professionals in HR space.

Seth Berenzweig:  It's something that can also recognize data anomalies. So for example, when you have billing that you're getting ready to send in to the customer. If you have any billing anomalies, let the software pick it up and at least do a quick review and check before you submit it so that you don't have any kind of, you know, inadvertent false claims Act issues or something of that.

Declan Leonard: Exactly. Look at AI as your friend in the HR function. You know, Joe, to your point. Yeah. You know, if there are mistakes made in payroll, we know as lawyers that there are very potent wage payment acts. They're very unforgiving. You know, people make mistakes. Humans make mistakes. Everyone makes mistakes. Computers make mistakes sometimes. And so if you do make a mistake, the downside could be really, really tough.

The wage payment acts usually say if you don't pay somebody all that they're due in any given period of time, you can you can be penalized with treble damages, attorney's fees, all kinds of things of that nature. So look at HR Should look at these things as our friend. You know, it's also interesting is a lot of HR professionals don't even know that they currently use. You know, you asked for a show of hands and they're like, no, I haven't done it. They think it's like this thing sitting in the corner that is like some highfalutin big, you know, computer system. Hey, I have permeated already. I mean, Zoom has an AI function, LinkedIn has an AI function.

So I'd be surprised if most HR Professionals watching today. I have not interacted in some way with AI.

Joe Young: Yeah. Great point. I again, I think it's embedded in everything that we do, and we don't know we're using it when we are at this point. It doesn't have to be. You don't have to have a chat CBT account to say, hey, I'm using in the.

Declan Leonard: Yeah, yeah. I mean we talk about what are some what are some AI functions that you think HR would use?

Seth Berenzweig: Well, certainly you can look for data recognition and data anomalies, too. As we had noted before, look for any kind of discrepancies on numbers before they get submitted for payment, which can help with false act, false claims, act issues. And, you know, just trying to also recognize patterns in future metrics for staffing requirements for certain jobs, and especially for companies in the high-end IT space, how to be able to have some kind of financial projections in the future going forward as you extend out on task orders. Yeah.

Joe Young: You know, and to that point, we talk about this, how this can augment and be a tool, not a replacement. You know, and to that point, you know, how can companies get in trouble of getting into it, you know, from a recruiting process? So where are the landmines? Well, that’s getting into it too much.

Declan Leonard: Yeah. And unfortunately, there are landmines. And, you know, as this continues to develop, they'll they'll they'll work some of these kinks out and everything. But basically, let's take an example. We talked earlier about, you know, using AI, your government contractor, you just got, you know, a new contract. You've got to hire 50 new people. You need air to help you cull through these resumes, cull through these applicants, figure out who's the best person for this job.

There's two ways, really, that you can get into trouble. Blatant discrimination. You know, you set your algorithms where it's going to exclude certain people. We know that you know, you can't blatantly discriminate. We call it disparate treatment. It's like just when you and there was a company I tutor group, they're hiring American tutors to go over to China and and tutor kids over there, and they actually set their algorithm not to reject any candidates who were over the age of 55.

So that's that's a kind of a no brainer that wasn't inadvertent. That was pretty blatant. Whatever their thinking was, maybe they were thinking, we want young people to travel over to China and do this, but they ended up getting hit with $365,000 settlement that they had to pay to the Equal Employment Opportunity Commission. That was blatant discrimination. But probably what comes into play more with AI is in advert and discrimination where you don't really intend to, but you got these very complex machines that have algorithms and source code.

And let's face it, not everybody knows very few people really know, you know, what are the true guts of an AI process. And so, you know, Amazon, big huge company Amazon found that their algorithm when they were calling through their resumes actually, even though it did not have gender as one of the characteristics they actually found that it was underrepresented female thought applicants for their job.

So they had to abandon that and kind of start back at ground zero with their AI.

Seth Berenzweig: Just to kind of recap on a couple of other specific programs that that are getting more attention and deployed in the workforce to help with team efficiency. Of course, we know the big one is ChatGPT that's being employed by a company known as Open.ai. They've been in the news through a variety of things. Google has their tool that which is known as Bard. [now Gemini]

There are a couple of other interesting applications and tools that I've seen that I just briefly jotted down. There's there's something called Otter. I like the the company. Yeah, I.

Declan Leonard: Have a story about Otter in a little while. That's an interesting one.

Seth Berenzweig: Okay. And among other things, that handles meeting transcripts and organization of issues, there is one called Grammarly, which is that which is document, organizational, and grammar-checking tool. There's one called spinach within it. Yeah, it's literally called spinach, which provides writing strategic assistance. And there's one called Firefly, which are meeting summaries by topic. And these are things that really help improve efficiency of the team from an overall staffing and from a human resource perspective.

So there are a lot of tools out there that are already on the market and there are more that are also coming to market. It's a really interesting space right now.

Joe Young: And our office, like most you know, we're Microsoft Shop so you've got copilot that's coming out that now is popping up. Yeah you said you have your views on popping all of a sudden I've got copilot stuff popping up as I work every day.

Declan Leonard: Yeah, and this is just scratching the surface. I'm just going to be so many more. So many more. As you mentioned, a couple company, you've got them integrated into your platform. So yeah, the sky's the limit I think.

Seth Berenzweig: Yeah.

Joe Young: So specifically, with our government contractors, you know, what are some of the ways that they can combat some of these challenges and still use? AI?

Declan Leonard: Yeah, I mean.

Joe Young: You know, comfortably.

Declan Leonard: Yeah, exactly. You know, the federal government has obviously recognized that, you know, there could be problems, as I just said, you know, with with with inadvertent discrimination when you're calling through resumes. The Equal Employment Opportunity Commission issued some guidance last summer and they basically they called it the the 4/5 rule or the 80% rule. And it basically was you need human oversight of this.

And if you're noticing that, you know, as compared to let's just say let's just throw it out there, white, Caucasian, you know, white Caucasian males, if you're finding that minority candidates are being underrepresented, underrepresented by, you know, let's just say under 80% versus over 80% for four another, you should that's not necessarily indicative of any kind of discrimination, but it is something that the human should look at and maybe recalibrate, kind of like what Amazon did when they realized that, oh, my gosh, we're not getting as many female applicants.

They're very underrepresented. They went back to the drawing board and they corrected it. So that's where I think that that's one of them. And to this point about human involvement, I mean, if you just think it you can deploy AI and then just sit back and, you know, hang out and go watch March Madness at AP or do whatever you're going to do, IBM is a good example.

IBM came up with an algorithm to determine more accurately pay and specifically pay raises designed to really address what somebody's skill set was that they bring to the table. So instead of like a position that's just like, Oh, this position lock step gets this amount of thing, they came up with an algorithm. But ultimately, the final decision is not that computers, it's a human managers. And so I think that's critical.

Seth Berenzweig: One of the things that I've been looking for as I've been reviewing this topic is to determine what are some of the actions that the government's doing in response to this revolution and to determine whether or not there are any regulatory requirements that companies in the federal space, including HR, need to be aware of and things that are coming about.

One of the things that I found that was interesting is that late last year, President Biden entered an executive order. Of course, in the federal space, everything either has to have an acronym or a number. So if anybody's tracking on their scorecards at home, it's Executive Order 14110. And it is entitled President Biden's Executive Order and Safe, Secure and Trustworthy Artificial Intelligence.

And what the White House has done in this executive order is it has set up some procedural goals in terms of how high tech companies should be coordinating and how companies that are using those tools should be coordinating to make sure that they deploy artificial intelligence in a safe and reasonable and nondiscriminatory manner. This is very new. It's only been out for a couple of months.

So it will be interesting to see how this evolves. But some of the prongs under the executive order have to do with new standards for safety and security to make sure that we, you know, avoid kind of like the Terminator scenario where the computers take take over the world. And I've also seen a lot of trending in a lot of references related to the executive order having to do with whether or not there's impersonation or fake IDs online.

It'll be interesting to see how that's being monitored, because quite frankly, that's been an issue before AI, So that's only going to become more challenging if you want to just jump really quickly to the state level. There are states that are also getting in on the action in terms of regulating. And so one of the more interesting examples that I saw is in California and in California, there is a regulatory body called the Privacy Protection Agency Board, and they have voted in an interim rule that's probably going to be finalized by the end of the summer on restrictions regarding automated decision making.

And what will be happening is for companies that are based in or perform substantial business in California, if they're going to use AI in any way to help monitor or assess job performance, job analysis benefits, or IT also, including job applications, they have to provide a job candidate with notification in an opt-out window. And if the employee or the prospective employee asks that that not be applied, then they cannot be treated differently or discriminated against based upon that.

So I think that as we approach through this year, there'll be more developments, especially on the state court level in terms of how they're going to regulate this.

Declan Leonard: Absolutely. Illinois is another one. So and the reason why and close to home here, Maryland is another one. Maryland says you cannot use facial recognition technology when you're doing most of these interviews. Let's face it, for government contractors in particular, because you're hiring all around the country, most of these interviews are being done by video. And so it is so it is so easy to be able to use so much of this high tech AI to evaluate candidates that way.

And so a lot of these a lot of these states, Illinois, Maryland and New York, they're basically saying, hey, you need consent and you know, you need consent before you're going to do this notice and consent. You can't surreptitiously, you know, B, B, be using AI as part of your process when when, you know, they don't even know that it's happening.

And remember, states anybody out there in HR knows states is where it's at when it comes to HR laws. Federal government, unfortunately or maybe fortunately, doesn't get much done these days. And so states have stepped in. Patrons, parents in laws, you know, restrictive covenants. We see those are four different different days here, but we see how they have done it.

So now we have four states now that have stepped in, at least as of the date of this podcast, four states that have stepped in expect many others to to go down this road. And so when you're interviewing somebody, it doesn't matter if you're let's just say you're in Virginia here, if you're interviewing them for and they happen to be in Maryland, New York, Illinois, California, that's the law that's going to apply because that's where that applicant is. So that's what they got to be wary of.

Seth Berenzweig: Exactly. And California often happens to be the canary in the coal mine. So if something's going to be coming out of California, it's probably going to be marking a trend where it'll be, you know, rolling through the state court system over the next couple of months and later this year.

Joe Young: Okay. So with our remaining time here, let's let's switch gears a little bit. We've been focusing on, you know, companies and organizations for parts, how they can utilize this, how they already are or how they may be able to expand that. But now let's flip to their applicants and their employees and their use of AI in the relationship and the potential impact of that.

And how do they monitor or control that. So specifically, you know what? If a company suspects that an applicant is using AI to, you know, create or otherwise embellish their resume or credentials? Well, you know, what are the thoughts there?

Seth Berenzweig: Well, you know, what's interesting is that there's a AI to detect that a AI.

Declan Leonard: Yes.

Seth Berenzweig: And it's called GPT zero. Yeah. And GPT zero is a AI that can detect AI with regard to, for example, resume embellishment or something like that. Now, again, you'd have to look at it a little bit more deeply to see how accurate it ultimately is. It might just end up being more of a warning signal. But I think there's two ways to look at this issue.

The first, of course, is that if there's going to be an embellishment and the question is, you know, how colorful is the embellishment if someone was, you know, just barely stepped on something and they say that they're the entire program manager, then that's one thing. But it's also an indication that someone is is savvy, that they're actually tech savvy.

And that may be something just to consider in the overall balance of the equation.

Declan Leonard: Yeah, I mean, when I hear that question, my first thought is, do they care? Like, you know, I mean, you know, is that a transgression is using AI to help you now, to help you not to write your resume.

Seth Berenzweig: Right. Or to make stuff.

Declan Leonard: Or do it? You know, like I said, I mean, if you're applying for an I.T. job for a government contractor, you know, I do have some comfort that this person knows their way around these programs a little bit. Now, if you get a sense that they're being dilatory and just kind of throwing it out there, and then I have a feeling, I mean, listen, HR

Professionals, they're not only very smart, but they look at this stuff all the time. It's kind of like it's kind of like college admissions. They know when a parent has written the applicant the essay and stuff, so I give them the credit that they're going to be able to ferret out this stuff and know pretty quickly. So I think if you use it as a companion and then, you know, but you still put it in, you still make it your own, put it in your own voice, I would say, what's the big deal?

You know, it's not plagiarism. Like it's not.

Joe Young: That's not like the college and high school kids of the past ten years knew how.

Declan Leonard: To have.

Joe Young: Their term paper was going to be put through software to see if it was plagiarized.

Declan Leonard: Exactly.

Seth Berenzweig: I mean, it's a little bit more powerful, like in the old days, you know, back in the stone ages, when when, when when we three were applying. Yeah.

Declan Leonard: Yeah. We had, you know, tablets.

Seth Berenzweig: Yeah, exactly. Exactly. I mean, you know, my most complex tool when I was using back in the day was at the source to try to figure out how to use Encyclopedia Britannica. Oh, yeah. Yeah, exactly. All, all eight volumes. But you know, there are so many technological tools that are out there today and even in our trade, all of the software programs are just becoming a lot more powerful.

So, you know, and as it turns out, sometimes there are folks that are younger that know how to use this. And you always have to be careful when you talk about things that might indicate ageism. But, you know, our job is to be able to lean forward on that. So if you have an opportunity to learn from someone, perhaps you should consider taking it.

Declan Leonard: Yeah.

Joe Young: So let's take that from our napkins now to our employees, you know, so our how aggressive, proactive do HR Departments, companies in general. Now, as far as all new policy sets about how are your employees allowed to use ai in the workforce? To what extent on what projects? Yeah, what tools, you know, ChatGPT or hey, we're a Microsoft shop.

We want you just to use this, so yeah. Where do you see that heading? Yeah.

Declan Leonard: No, I mean, it is, it is new. They are new policies that are coming about as a result of AI. You've got AI acceptable use policies. That's where basically it's up to the company to set the standards of what they want to do. I think you also need to have a mandatory disclosure form. So policies are generally like company issues gives them to the employee.

There's not much interaction, but I think there should be a mandatory disclosure form because you're not going to know if you've got a couple of hundred employees. You're not going to know whether or not they're using AI. Everyone comes to the table with their own stuff. They'll be like, Oh, I use this all the time at home or whatever.

This will make my job easier. It's not even nefarious. Yeah, but companies, if they don't know about it, they don't know what they don't know, and that's where they get into trouble.

Seth Berenzweig: Well, and I think it's not only an issue of output but input. Right. Because with large language models, the more source that you put into the gravy, then the more powerful it is. The problem in the federal government contract space is that a lot of the information that we have is protected, and there are probably going to need to be certain limitations on what data can be put into a large language model context to help feed that algorithm.

So when we're talking about those kinds of policies and procedures, the company probably needs to consider it from that standpoint as well. You know, it's funny, a couple of years ago, the new wave of the high-level nuance for for employee handbooks was social media policy. Yes, there was a day, believe it or not, in the Fred Flintstone days when there was not a lot of social media.

Then, of course, over the last ten-plus years, obviously, it just permeates everybody's life. Now we're talking about an AI policy, but in a year or two, those are going to be very familiar and very commonplace as well.

Declan Leonard: Yeah, And I think I think looking I mean, most companies have confidentiality policies, but I think they got to retool those a little bit to incorporate what AI brings to the table. You know, if you're there was there was a case Samsung had an issue where its coders, the people that were developing and source code were were taking that source code.

And again, nothing nefarious, but they were putting it in a I think it was check GPT two to confirm the accuracy. I mean, you've seen source code sometimes and what goes into it.

Joe Young: I know we've heard that that's from a coding perspective AI is yes. Yeah. Yeah. Over that.

Declan Leonard: Yeah. But the problem is you're putting it in an outside source basically. So you know companies that are big enough that have the budgets I've already seen, they're developing their own internal. You say they're the ones you probably are not going to have to worry about as much. But in this particular case, believe it or not, Samsung did not have that, and they were putting their source code there.

Their engineers were putting their source code in. And that created all kinds of issues, misappropriation of trade secrets. The fact that you're putting this stuff out there to the general public who can see it, you know what I mean? And in order to protect a trade secret for a company, you have to show consistently that you're protecting it from public disclosure.

And yet AI is like comes in. And AI by definition is kind of like an outside thing that you put it in to check out, you know, to confirm things. So I think that's where it's going to start to undermine some trade secret issues.

Seth Berenzweig: And I'll just briefly note that under the President's executive order, one of the components of it is to require software companies to share information with the United States government with regard to safety test results. And I think that when I read that, the first thing I thought about were trade secrets as well, because there are some testing developments that a lot of these companies are probably not going to want to just have as an open book to the government.

So they'll probably be some some give and take in some some issues that come up on these policy.

Declan Leonard: And remember, for government contractors, you know, let's just say you're a subcontractor. You're not just playing with your own information like a regular company is playing with the Prime's information, you're playing with the government agency's information. So it's not only potentially your own trade secret or confidential information gets misappropriated, you may find yourself on the receiving end of a tortious lawsuit that said, you did not take adequate policy or breach of contract ever.

You did not take adequate safety measures to protect us, the private or the federal government. Federal government may come in and say, you're going to get a bad C pass or you're going to get dinged on this contract because of not taking the appropriate safeguards.

Seth Berenzweig: And then in the case, the department will be asked about what, if any, process or procedures they did to oversee staff's use of AI tools. So you can see this going in a lot of different areas.

Joe Young: And I'll tell you, that leads into perfectly into one of the questions we had brought to us today is, you know, should companies requiring employees to disclose when they have used a tool to create something so you're not getting surprised.

Declan Leonard: 100%. Like if you do not know that they're doing it, you don't know what to police. You know what I mean? Yes. So I think this is one of those rare situations. You know, sometimes when you start a new job, you're supposed to disclose any prior excuse me, any prior inventions that you've done. That's one of the few times I can think of where you have to list things.

Yeah, this is another example. Like if you say, Hey, I'm going to use it and then just get permission. But yeah, if there's no disclosure, I don't see how unless you're just the genius computer engineer, I don't know how you're going to be able to police this in the HR function. So. Yeah. Yeah.

Joe Young: Well, that really brings us to time - that went fast.

Seth Berenzweig: Wow. Which I did go.

Joe Young:  Is it 1:30 already? Oh, it is. Okay, we'll just.

Seth Berenzweig: Use AI to generate another 5 minutes.

Joe Young: Yeah. You know, this is I think this is a topic maybe we maybe circle back on because I think it's going to continue to evolve. There's going to be continued. Other questions and possible applications. We may have to have, you know, 2.0 of this maybe later in the year. So for all of our listeners out there, again, thank you for joining us today and spending your afternoon with us.

We hope this was was helpful. It helped to uncover maybe some of the challenges and questions you're already asking yourself in your department. So on behalf of Declan and Seth and myself, thank you again for joining us. Remember, our next episode is going to be on April the 18th, and next month we are going to get into the fun topic of navigating bans on non-compete.

Declan Leonard: Oh, okay.

Joe Young: So a lot of dialog in that conversation as well. So we look forward to that. We look forward to you joining us then. Enjoy the rest of your March, and we'll see you next month.

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