Revolutionizing HR: Unveiling the Latest AI-Driven Trends

Jeff Hayward: So hello everyone and thank you for joining us. I'm Jeff Hayward, CTO for TriNet, and it's my pleasure to introduce Jill Kesler, the senior vice president for Employ, where she leads partner strategy, and she actually covers all of the partners at Employ, including TriNet, which I'm very excited for. So, Jill, you have a kind of an exciting career experience, and prior to Employ, you were at ADP for about 15 years and you won about 18 awards for being just an innovator.

You were very key for helping and played a big role in growing ADP's marketplace. And one of the things that I'm excited about as a technologist is that you've always been a thought leader at the intersection between HR and technology, which makes you very qualified for the conversation today.

And as a technologist, AI is something that we hear about everywhere that we go these days. It's probably the number one question that I get. Oh, by the way, congratulations. I was reading the other day that in Forbes Advisor, that JazzHR, one of your products that you cover, actually won a couple of awards and was recognized for, one, being the applicant tracking system that is most suited for startups. And the other one was being the best recruiting software for companies with fewer than 500 people.

Jill Kesler: Absolutely.

Jeff: So, congratulations.

Jill: Thank you.

Jeff: So to get started, maybe you could tell us a little bit more about yourself.

Jill: All right. Well, thank you and thank you for the introduction. So yes, very happy to be here. Appreciate the opportunity. So yes, like he was sharing, I run the partnerships across all of Employ, which if you're not familiar and not to get into branding, but it is several, multiple ATSs that cover all size organizations, right? We have JazzHR, Lever, Jobvite and we do have a RPO solution called NXTThing. So hopefully if you haven't heard of them, check them out.

But we've been a long-term partner with TriNet, as far as leveraging our solution whenever, maybe, their recruitment needs are more than what TriNet might have to offer. So they're good at bringing in other partners to help out there. So very excited to be here today.

Yes, as we shared, I don't get to watch the news or even the Today show at home a lot. From St. Louis, but when I travel and I don't have my children, I always turn the Today show and literally was the first thing on about AI. But it had to do with about children in school cheating, right?

That was like a little bit different topic than today. So I'm excited to be here. We have some interesting insights into recruitment and AI and some of the trends that we're seeing across, whether it's our different solutions along with our clients, some in the market. So thank you.

Jeff: Absolutely. And you talk about AI and the Today show. Last night, I was watching the football game and I think I counted six times that AI was referenced in different commercials. It was everything from Allen Iverson, AI, all the way to IBM Watson. So you just can't escape it right now. But at the same time, we're also witnessing how AI is really transforming the world around us and how pervasive it's become, and really, AI is everywhere. For example, in my technology team, we don't write lines of code anymore.

Now we actually have the AI suggesting entire blocks of code that we can implement into our applications, which just creates an order of magnitude improvement in how much code we can write and how productive our developers are. We also recently helped our revenue team deploy some new AI technologies that helps with sales coaching and understanding the interaction between customers and our teams, which is really important to really improving our sales process.

We use AI in our marketing, in our treasury and of course, in HR. And I think that AI in the HR landscape has really matured in recent years. We now see AI in recruitment, we see it in employee development, and beyond. There's a lot of different use cases. And if you start to look at some of the statistics, 59% of HR leaders that were benchmarked by Gartner said that this is one of the most important technologies that they see, one of the most important use cases.

And another Gartner 2023 survey, 31% of the respondents rate AI as being the top emerging use case for HR. But at the same time, HR can also be controversial. I think for some, it's kind of scary; for others it's thrilling. As a technologist, for me, it's thrilling. But 41% of HR leaders are concerned about things like compliance issues.

So it's something that we really have to take seriously. And at the end of the day, there's a lot of misinformation out there. There's a lot of confusion and there's a lot of unknowns. But even despite that, the statistics tell us that 76% of HR leaders know that it's critically important for them to start implementing AI, HR, or they're really going to start to fall behind competition, and not really have the kind of organizational success.

And they really see the time window to deploy these types of technologies as 12 to 24 months. Clearly, this is top of mind for the large majority of HR leaders. So, today let's go ahead and dive right in and let's look at some of the ways that we're seeing AI technology impacting HR. So, let's start with recruiting.

So, year after year, recruiting is really the top of mind, top challenge that we hear from small and medium-size businesses. So, I'm wondering, with AI, is there anything that we can look forward to help us out here?

Jill: There's a lot. It's already happening. So, I want to reflect on a few things too before we get started. You know, when it comes to the recruitment process, it's not a matter of, we hear this, but I like to look at the broader picture of it's not necessarily taking the jobs, right? Or this is not going to replace. It really is. It's going to give the edge on the individuals that are using AI in the recruitment space, the right way, right? So if you look at the bigger picture, there is—you have to have your people, right? That's key. Then you want to have the right technology when it comes to recruitment. But then how do you build the AI into that, is what's important, what part of the recruitment process? When you think of it, there's many steps into recruiting.

I believe, and we talked about this, as we were preparing for this, we can't lose the people aspect of it, right? No matter what we believe the generations want, losing that people aspect of it is what's very important to keep. But at the same time, you also have to be able to figure out that candidate and how you're recruiting what's important to them, right?

So that's where, as we kind of dive in into the conversation today, we'll talk through different areas within recruitment and different businesses, organizations have different areas that they need to be leveraging AI and we'll kind of talk through some of those different areas.

Jeff: Excellent. I actually did a podcast last week with another one of our partners and that whole generational aspect. And one of the things that they were stressing is that you can use AI to kind of meet people where they are. And I think that's such an important aspect because we are seeing this generational shift. So that's all about recruiting. What about hiring? Are you seeing any successes or any data on how AI has improved hiring?

Jill: Yes. Oh, definitely, definitely. So speed. We all know that, right? So if we look at the top four reasons that we've seen, the stat show, the number one is speed, right? Like they're able to do more, quicker. Number two is the sourcing side of it. Number three is bias, right? So when they're getting the applicants and they're hiring and bringing them on board, really being unbiased and number four, which I was actually shocked this was number four. I thought it would be a little bit higher up was diversity, but it was the fourth one when it comes to hiring and making sure they're covering all those different realms of the hiring process.

Jeff: Excellent. So we were also talking the other day about biometrics, and I think we both are fans of using biometrics in our training and in our fitness regimen. And I know that you have a passion for fitness and for personal growth. So how do you think about AI and how it can contribute to really employee development and wellbeing in the workplace?

Jill: Well, that goes back to you knowing what I enjoy, right? But if we back this up and think about the recruitment and leveraging the AI, when you understand when you immediately—because even though there's a larger pool of candidates out there than normal, right? It was crazy because if we were talking three years ago, it was completely switched.

But knowing and leveraging the AI to understand and what data you can find out to be relatable to those candidates that you want to recruit truly is key, right? Relating it back to fitness, we were talking about Peloton. I'm not dropping names here, but just we both enjoy it, right? We were talking about the data that it gives you, right?

And it intrigues me every week. It's feeding me, "You should consider this workout. Have you considered this? Oh my gosh, you're going to break your streak," right? And if you can start that with the recruitment process of understanding what that candidate likes, what they're looking for. We gave some examples last week when we were preparing for this, as we start to look at the, I don't even want to call it generation because sometimes you'd be surprised, age, anything they might if you can immediately pick up on—do they prefer to text? Do they prefer to email? I mean you can literally apply for a job through text, right, like texting on your phone. You don't have to log onto a computer. That works for some. Then there are others are like, "I need to sit down. I want to fill out the application," right? And have it done. So really understanding that and leveraging is what I think is important.

Jeff: And it's so interesting to see that diversity. I'm actually a father of four kids and I'm not sure that they even know that you can talk on a telephone, right? They just have to use the application.

Jill: You said they use, all your kids use different ways?

Jeff: Different. Like my oldest will only use Facebook. My next will only use Instagram. They can only communicate. They can't talk to each other because they're on different platforms. Yeah, it's a challenge, but we have to meet. We have to meet the new applicants where they are. So as I talked about in the introduction, there's good and bad to this, right? There's things that we have to really watch out for. So in your experience, what are some of the common pitfalls and the challenges that organizations will face in implementing AI and how do we mitigate some of them?

Jill: Yeah, we're going to keep this one pretty level, right? But this one is a loaded question because there is a lot to it. Keeping it when you are recruiting a candidate, the information, number one, that's out there that you can find, and what you know and what you don't know, what is correct and what's not correct.

You really have to come up with those boundaries within your organization. And you can do a lot of that through systems of what you want to see. And as an example, there's certain things on resumes you can mask. So if you are the recruiter, you're recruiting, you're not able to see that. So you're not having a bias towards that.

I think that's important, an important piece to look at. And it really is based on the company and coming up with where are our boundaries, to what extreme or to what minimal amount are we going to use the AI to make the right decisions and sticking to that across the entire organization during the recruiting process.

Jeff: Yeah, I think it's so important when we look at any kind of AI project that we take a responsible AI kind of approach. And I think it's also really important to be very transparent when you're using some of these technologies. So, ethical concerns, I think, are significant when it comes to AI and HR. And the big ones are some of the obvious ones. It's data and privacy and security. You mentioned this a couple times already—it's bias and discrimination, and compliance issues that we all have to deal with. So what are some of your thoughts on how we can ensure that we achieve that fairness and we really minimize the bias in AI throughout the entire hiring process?

Jill: Yep. So it goes back to the technology that you're leveraging. Whether it's TriNet, it's Employ, it's really starting with that foundation. And I think having a technology in place is important, right? And again, not just because I'm with a SaaS technology company, but it truly can set the foundation.

So I believe that how you set that up, because that can automate a lot of the process, making sure you are keeping compliant, everything legal set up. Obviously, you're able to consult with your TriNet, right, whomever you're leveraging to get some best practices for them. But I think it's a matter of the information's out there. Before AI, right, everything, I mean, I joke, but like we Googled everything, right? We believed Google was always true, right? You always, "don't go to Google." Well, you don't want it to be like that with AI. You just have to know your boundaries and make sure it's set up in a streamline across the entire organization.

Jeff: Makes a lot of sense. So I know you're also passionate about community engagement.

Jill: You didn't tell me this one the other day. You really did look me up. All right.

Jeff: So how do you see AI impacting our ability to build a strong workplace culture and really a sense of community within the workplace?

Jill: Well, I think you hit the nail on the head. So yes, I'm very involved in my community in St. Louis with some nonprofits and you're able to find that out rather quickly. And I think that's where you make the connection. So I'm gonna drive it back to recruitment, right? When you find those candidates that you want, even though there's a bigger pool now, it's finding the right one.

That's right. When two years ago, we were talking about there's not enough. It's on the employer. But even when you find the right one, if you can give them the feeling that you know them, you know what's important to them, you're starting off from day one, that you're giving them an amazing first impression from the minute they see your job posting, or it stalks them and finds them right and they then apply, giving them that really good experience that you know them and you know what's important to them and the person interviewing them also has a good understanding of what's important. And then based on the information that they're able to gather through the recruitment process.

Jeff: Excellent. So there's a lot of fear, uncertainty, doubt. There's a lot of excitement, but there's also a lot of unknowns. So in terms of AI and HR, what unknowns or uncertainties do you think that we really should be prepared for as we continue to kind of implement and innovate around this AI technology?

Jill: You know, going back to—it's not going to replace, it's the ones leveraging it are going to do extremely well with it. So I think that's a fear. And I think we need to understand that across. And I'm sure you see that the most. It's not going to replace. It's a matter of how you leverage it. The biggest thing is not believing everything you see, everything that comes across, that's out there. But I also think it can give a very, very competitive edge. So it's really based on the organization, what they see as important, how much they want to leverage it, whether it's a lot or a little and having good starting points with it and how they introduce it to the organization, and same with how you're including it throughout your process of recruiting and onboarding.

Jeff: And I think that's so important across the board. I know, as a technologist, I was frustrated one day when I picked up the Wall Street Journal and I read 'here's this high paid Silicon Valley developer that's now working delivering pizzas because he was replaced by AI.'

That's not happening. It's not. It's sensationalism in the media. And the reality is, throughout my career, I've been in technology for a very long time, and throughout my career, there's been many times where we were going to be replaced, where we're no longer going to need developers. Cobalt came out when I was at university and that was going to be the business language.

So all the business people could write their own. Then there was case tools. Then there was no code, low code. Then there was SaaS. I'm still a developer. I'm still here. So with this latest evolution, the way I think about this is just another level in productivity. So all of those innovations before, they didn't replace me; they just made me quite more productive.

And that's the same thing with our teams. And I think this is so important because at the end of the day, we need our teams and ourselves to be able to embrace this technology and recognize that it's going to make us productive. And I think from that standpoint, it's really important to enforce that this helps us make better decisions, helps us make decisions faster. It's not here to replace us. And I think that's important things to be sharing.

Jill: And I wanted to add too, there's so much room for growth with AI. So the studies are showing within businesses and their recruitment process, right, their recruitment and onboarding, if you look at enterprise, and I'm going to refer to enterprise right now, 5,000 plus, right, or size organizations. They're leveraging AI about 84% of the time. When you get into mid-market and SMB, it's only between 15 to 24%. So think of the advantage if the enterprise type organizations are using it and using it properly, especially in the recruitment process, the advantage and the growth opportunity that our mid-size and SMB organizations have by really starting to leverage it, too.

Jeff: Yeah, I think that's so important.

Jill: I think that in the SMB, it's almost like they're scared to start with it. Of course, the larger organizations, they've invested, they have the time, the people to really dive into it. I think in the SMB and the mid-size, there's a little bit of fear around it, but there's so much opportunity if we use it correctly.

Jeff: And I think that's a great recommendation for SMBs. If you leverage this technology, like in the technology space, there's technologies like GitHub Copilot, which can take a developer and they can become an order of magnitude better. Well, think about that from a competitive advantage perspective. Now, the ability to level the playing field for SMBs to be able to compete with the much larger players, the technology is out there to enable that.

Jill: You're right.

Jeff: Go out there and be a disrupter, right? Create a new capability. Like Burton said on stage today, it's never a better time to launch a new company because the technology is out there to support us. So from your perspective, what are some innovative ways that we can use AI to enhance our services in the HR space and remain competitive? So, like TriNet as a PEO, what are some things that we should be considering?

Jill: So it goes back, really taking a look into how you build it into the platforms that you're using and how you can leverage the data. And that's where I'm related a lot back to recruitment. It's what I know the best right now. But if you think of one-click sourcing or if you're able to post a job to one site and it's going out to hundreds of thousands of different job sites and it's pulling back that information, really giving you that to dive into.

If you're leveraging AI, I think communicating with the candidate or the potential candidate. And then as they're onboarding, the communication and AI, right? That's okay. Right. That the way it replies, but it's that immediate knowing someone is acknowledging you. I think that's really important too. It gives more of that handhold and that coddling feeling throughout the process.

That's where I would be leveraging it. And it all starts with the recruitment and then I know you get into and you hire them. There's different areas of the LMS that you can leverage some of the data—where are their skill sets? Where can they be more enhanced leveraging that data? And then using the AI for that.

Jeff: Excellent. So you talked about skill sets. I'm going to address that for a little bit. And we talked about this just a second ago, but one of the things that often gets raised when we talk about AI is really job displacement and how we can ensure that AI is really empowering our HR professionals, empowering our technology professionals, rather than replacing them. And I think one of the important aspects of this is really understanding what their current skills are and contemplating how we go through reskilling efforts. How would you approach that?

Jill: Exactly like you just said, actually. It's understanding, it's knowing. If you think back, I know it's weird when you just talk about five years, because so much has changed even in three to five years, right? But a lot of the skills that we understood was all based on what a manager might put in a review or what we thought the employee knew or understood. And now it's going so much deeper into really taking the time to assess the employee, whether it is through assessments, right, that can go more deeper than ever.

Before, you all know, we all took those assessments and like we got this back and tell us who we are and what we are like. Great. What do we do now? Well, now you can line up, have a really great assessment. And then what is it doing? It's automatically starting to feed you back, "Here's some of your strengths. We're going to enhance your strengths. Here's some areas of opportunity. Let's work on those areas of opportunities," and it's feeding you what you need. Right? Whereas back in the day, you just read it and then you thought about it and what you could do. And then your manager would try to help you through how they could help improve you, but this is now leveraging—the AI can feed it right to you and instantly start to improve and help you, right? And that goes back to also helping you retain employees if they feel like they're constantly being improved. And again, it goes back to no matter the size of the organization, this is stuff that used to always be thought, "you have to have 5, 000 employees." Now you can have 20 employees and do the same thing with the technology that we have in place.

Jeff: I think that whole training and that reskilling aspect is so important right now. Technology is advancing faster than I've ever seen in my entire career. I mean, it's incredible—the leaps that we've seen in AI just literally in the last eight, nine months. So one of the things that we've instituted at TriNet to cross our technology teams is just we have more learning days, time specifically set aside so that our teams can come in and they can work with some of these technologies. We haven't made them mainstream yet in many of the areas because we're still learning, but it's really important for our teams to get exposed to this technology and have time and space to really learn about it.

So I think this whole reskilling effort is really important as we go forward, which kind of brings us to the next point is—I think continuous learning is just kind of crucial in our field. I'm just curious, what kind of strategies do you recommend that our HR teams adopt in terms of evolving AI technologies and helping our team stay ahead of that curve?

Jill: We know, as far as staying ahead of the curve, it really is understanding where your employees are at, where do they need to be, implementing the days where they can understand, take the time as an organization to learn the different things that are in place, cross pollinate.

What is this department doing? How can I learn from them? Right? I think it's really taking that broader picture instead of being so siloed into one area. It's really starting to understand across the organization sharing, because technology is evolving faster than it ever has. But guess what? It could be the person in the organization that may have never spoken, you know, spoken five words, right?

It might be the quietest person or the most outgoing person, could have some of the best ideas. I think organizations are starting to really evolve and think of—how do I leverage my organization as a whole and everyone I have in it? It's no longer, they came on board to do this, they're going to stay this route. But again, going back to assessments, understanding what are their strengths, what's their areas of opportunities and how can we leverage them as a whole?

Jeff: Yeah. And I think that's a really great point about what this technology enables. I mentioned in my introduction that we just recently helped our revenue team implement a new sales coach capability with AI. And one of the things that we found out is that's also a great resource for our product teams—to be able to understand and really understand that relationship and that interaction that we have with customers. It's not just in one department anymore. It allows us to understand, not only across our organization better, but it allows us to understand our customers better and I think that's very exciting. So we covered a lot today, a lot of different questions. Anything that we might not have covered that you think we should have?

Jill: Overall, I was going to hit on a point we were talking about. Don't be afraid to try it. You definitely can't hide from it. It's one of those, I know that we've had organizations we were talking about, you mentioned, thank you for acknowledging Jazz and the JazzHR and the awards that we've been given, but it's always been seen in the SMB space. "I have 10 employees. I don't need an ATS. I don't need a recruitment platform. I'm fine, right? I'm the owner. I'm gonna do the recruitment."

It's really starting to evangelize that no matter what size you are, whether you are the smallest startup and debating on, "Can I use AI to actually help my organization?" Maybe it's helping the product that you're creating or the widget you're developing, but can you also use it within your organization? I challenge you to do it. Go for it. Within reason. We talked about, but I think you're missing the boat if you're not initially just going after it and trying to have an understanding of it, because you don't want to get too far behind, right, and then you're behind the curve versus staying with it and growing with it.

Jeff: And that's really good advice because at the end of the day, I'm the technologist in the room and I can tell you one of the critical things about doing proof of concepts early, is that I guarantee you it's going to challenge your data infrastructure because you're going to be more hungry for data than you've ever been before.

You want real time information from all of your customer interactions, all of your employee interactions and the more that you can see, the better that these algorithms and this AI can really help. So it's going to stress your data platform. So it's important to experiment, learn early, get involved early and help your teams just get access to this kind of technology.

So one bonus question, what do you think is next in tech recruiting? Do you see anything?

Jill: Oh, there's so much good stuff going on. I would say a lot of it is coming down to tightening up recruitment marketing, right, how you go about. It's not just putting a platform out there and putting a job posting out there, it's really—how do you market to these candidates? How do you target them? How do you target the candidate that's not even looking? Right? Like we said today, there's a larger candidate pool than usual out there, but maybe though that's not who you want to hire you. Maybe you want to hire someone that's not looking. So it's really leveraging that a lot of cool things are coming within the recruitment space, I think to tighten it up, to really help employers in the very near future. A lot of it has to with AI.

Jeff: Excellent. So we see a poll here behind us. Are you currently using AI in your recruiting practices? Looks like the majority of the audience is working on it, which that's exactly where I think we need to be right now, is—we need to be experimenting, we need to be learning. There's a lot of aspects that we talked about today in terms of potential challenges that you might encounter—some of the bias and some of the other things that these types of technologies are susceptible to. So very glad to see that people are working with it and currently using it. Looks like a pretty even distribution now.

Jill: Yeah, it is.

Jeff: So those of you that are on the nose, maybe this will help a little bit to bump you into the ‘yes’ category or the working category on it, but we'd definitely encourage that. So I think we have a few minutes left if we'd like to open it up to any questions from the audience. I think that there is an option to submit questions via the application. And also, we have a mic here available if you want to raise your hand and ask any questions.

Audience member #1: So, I'm on the novice side. We use TriNet. I was hoping to understand more about actual examples. So, I understand that we may be getting applicants who are creating resumes, right, through Chat GPT or whatever AI. And, I understand our ATS has some automated pieces, but how would I employ AI in recruiting? Do I talk to my tech person? Do I talk to TriNet? We're a very regulated industry, so I'm not gonna throw all the resumes into Chat GPT and say, "Who should I hire?" I was just hoping for some more examples of actual—what is happening that an individual can do, not on the back end of a tech.

Jill: Yeah, and are you referring to the TriNet cause you're actually using the TriNet platform?

Audience member #1: I am using TriNet, so I'm happy to hear what else is coming. You know, but if it's like, "Go out there and try it," like, "Where? What do I do?"

Jeff: As I mentioned earlier, we have a partnership with JazzHR. Maybe you could give an example.

Jill: It goes into our platform, the AI is built into the data that we're gathering, right? So knowing if you are aiming for the right target audience for the job, if how your job posting compares to others that have the same job posting. It's really a lot of the reporting and the insights that it's going to deliver to you.

That is helpful. It's not necessarily, like you said, putting out a pool and hoping it spits you back. I mean, it's going to do that through a filter and through those questions. But that is really where the data is more built in behind the scenes, that it's able to then help you with whether you're sourcing a candidate, as they start to go through the process, the communication, how you're communicating with them—that's how it's leveraged within our solutions particularly. Was that helpful?

Audience member #1: Yeah.

Jill: Okay, good. Yeah, it's not like you said. I know you're like, " I don't understand. Do I just go out to a website?" No. Within our technology, a lot of it is you might not even know that it's there and that it's being used, if that makes sense. There is a lot of it. We all, you can go to AI now and write your introduction or write your little essay. It's not necessarily like that. Now, it could help you, like within our platforms. It could help you write a posting, right? There's definitely areas with that where to help you write the posting. That's an example, but it's not necessarily where your mind was going with it—just throw it out there and see what comes back. A lot of it is built into the actual solution.

Jeff: I think we have one in the back.

Audience member #2: So you mentioned AI can help with helping with diversity and inclusion, but I can also see the flip side, because a lot of these models were trained, I'm sure, by not the most diverse group of people. We've already seen it with facial recognition. A lot of those technologies have historically not been able to recognize people of color's faces as easily, so what are your considerations when thinking about how these models are trained, what data sets they're pulling from?

Jill: That is going a little bit deeper than my knowledge of the data sets, to be honest. So yes, and I can follow up with you and get you some insight from Employ. But yes, there is data sets around. I don't have the answer for that one. I would be totally guessing. Maybe you can elaborate on that one.

Jeff: This is one of the areas, and this is why we're encouraging POCs, because, as we've mentioned a couple of times, the technology is susceptible to bias and it does matter what content you're training on and how you're training, and part of what we're working on at TriNet is making sure that we are training on a diversity of input, and that we're also focused on, and this is where I go back to responsible AI. The way we're approaching AI right now, is one—it's too critical to not have a focus on it. We talked about the competitive advantages. We talked about the importance, the productivity gains that we get from it. But also there are limitations to this technology if you're not using it properly and bias certainly is one of those.

So we're making sure that we're training on a diversity of content. And then we're also applying the human aspect to this. So when we think about AI and responsible AI right now, it's really human assist. So you'll notice I didn't say that the code was that the AI was coding for our developers. No, they're not. They're helping the developers. They're not answering the questions for our agents, they're helping our agents answer questions faster. And that's one of the ways that we're actually actively using the technology and allowing our humans to make the decision and our colleagues to make the decisions on, "No, that's a biased answer. That doesn't sound like an answer we would have given."

And that's the cycle that we're going through. GPT, generative pre trained transformer. The P is important in that, right? Pre-trained. This technology has to learn from us. It has to learn the correct type of bias or absence of bias. It also has to learn things like tone, right? So when you start using this in real world human interaction, the great thing about GPT type technologies is it's conversational, right? Any of us can use it. Any of us can become developers. The challenge with it, though, is if it's used improperly, it is susceptible to things like bias.

So I think it's a great question. And my answer to that is test, train, test, train and make sure you hit kind of one of the keys in your question itself. Make sure you're training on a diversity of content. That is important.

I think we have time for one more. We got one in the front.

Audience member 3: I can speak without the microphone.

Jeff: I'll just repeat it then.

Jill: Yep. Go ahead.

Jeff: Please.

Audience member #3: My name is Dimi Yar, founder of Boss Income and Equality Solutions. My question is something that the previous speaker alluded to. When applicants start using AI to enhance their resumes or enhance their answers, how do you view that? Do you view that as cheating or do you view that as the higher-level ability, thinking about them as the future employees that have mastered the technology? Do you draw the distinction between the human and the sort of enhanced version of that human? And do you take that seriously or is that a concern where you still want to understand what the human is capable of by themselves?

Jill: Yeah. If they're lying, right? Like if they're giving inadequate information about what they've done, their career, their skills, if it's not right, they could do that with AI in my mind or without it, if they're going to do it. I also think it's getting to a point, so one of our solutions is—we actually have recruiters, our RPO, right? And we've talked about this—a lot of that they can see, this goes back to the people aspect of not losing it, losing the people aspect. They can see through a lot of that. If it seems, I'm using the word fluffy, if it seems very fluffy right and almost too much.

But we have not seen it as a negative, right? If they're using, and we were walking over here today and we were talking about using it when they use it in school. If you use it to the ability to maybe increase the way you're writing something, but you're not completely copying it and pasting it, to us, it's not seen as a negative, right? It's just more enhancement using the technology they have around us, just like we used to use Google, things like that. It's just using it within means and that the items that are on the resume or what they apply for are facts. I think that's the important piece. Do you agree?

Jeff: And I think you framed the question very well, because at the end of the day, if you think about AI as a productivity enhancement and you just think about technologies we're already using. Today we could go out and use Google search and we can find a lot of very rich content and you could plagiarize that and actually use that in your resume.

We have those capabilities today. AI would let you do that a little bit better, a little bit harder to detect. But at the end of the day, if we think about it as a productivity tool, we think about it as a research tool. We think about it as a way to augment us as long as you're not going out and doing what we all know is not a good thing. Plagiarism is not a good thing. As long as you're not doing that, if you're actually using that as a tool and assisting, I think there are many positive uses of it, even in those types of scenarios and we are going to, as we talk about upskilling, we are going to be looking for leaders in our organizations that can understand and leverage this technology.

It's actually what we want, but like anything else, it could be used for good or for bad. Let's encourage, let's teach and let's have the thought leadership that helps all of our teammates understand how to use it for good. Well, thank you very much. Really appreciate this discussion.

Jill: Thank you.

Jeff: I think these kind of discussions are really important for us to advance HR in our company, so thank you very much.

Jill: Thank you.