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Artificial intelligence is no longer a thing of the imagination. If anything, it’s quickly becoming a part of daily life. 63% of AI users are satisfied with generative AI tools in assisting decision-making, and 42% of those who don’t currently use AI plan to in the coming year. For any strong HR leader, staying on the cutting edge of AI trends is essential. One main area where HR professionals incorporate AI into workflows is talent acquisition. However, there are also ethical considerations when using AI to find candidates.
Tune in to the panelists to hear them discuss AI and recruiting. You will leave with answers and insights about using AI at your organization to find your best talent.
Note: This content originally appeared as part of HR Daily Advisor’s virtual “HR Technology Week 2024” on August 12, 2024.
Responsible use of AI in talent acquisition requires careful consideration of data privacy and security, understanding biases in AI algorithms, and clear communication with candidates. Speakers discussed the importance of refining AI technology for recruiters and candidates, tailoring messages to resonate with skeptics and enthusiasts, and addressing ESG concerns. They also emphasized the crucial role of transparent communication in ensuring AI’s ethical and effective use in hiring processes.
Erika Randell 00:01
Welcome everyone. Thank you so much for joining us for this panel discussion during HR Daily Advisors, HR Technology Week. My name is Erica Randall, and I’m the content director for HR Daily Advisor, and I’ll be moderating the panel discussion today. And I’m also here with Maddie, who is our CO moderator. She is on the phone, and I’ll let her introduce herself, Maddie,
Madeleine Collins 00:25
Yeah, hi everybody. Thank you for joining. I’m Maddie Collins, and I’m a content specialist for HR Daily Advisor.
Erika Randell 00:31
Great to have you here, Maddie. And so I’ll tell you in just a minute why Maddie is going to be co hosting with us, but so that our audience can participate in today’s discussion too. Please listen for questions that I’ll be directing to the audience throughout the panel discussion. Maddie will be overseeing our attendee chat box and letting us all know what you’re saying. We would love to hear your thoughts and insights on this topic as well. So look for the attendee chat widget in your console, and please make sure to interact with us before we dive into our panel discussion today, finding your best workforce with AI. I’d like to give a huge shout out, and thanks to our sponsor, eightfold for this panel discussion. Thanks for being with us. And now I have a few housekeeping notes. First, the console that you’re seeing in front of you offers multiple widgets that you can use during our session. There’s a widget called the media, excuse me, Player, Player widget which will allow you to control the volume of today’s session. Please note there is no dial in number for attendees, and so the audio is streaming directly from your computer speakers, so you just want to make sure that they’re on and they’re up so you can hear us, and you also don’t want to miss any part of today’s great session. But if you have to, or you have to step away for any reason, we are recording today’s session, and we’ll be sending a copy out to each of you via email in about 24 hours, if anyone on the line experiences any type of technical difficulty, please feel free to let us know by using the Q and A widget on the left side of your screen, and our team will be happy to assist you. And those questions should just be about audio or video quality. Speaking of that Q and A widget, we are excited to hear again from you today during our live Q and A session at the end of this presentation, which Maddie will be hosting and time permitting, please feel free to submit any questions that you have on that on our topic today and as we go through the discussion, but just know we probably won’t get to your questions until the very end. And on that final note, if we run into any technical difficulty, just don’t go anywhere. Hang on. We have lots of great content to share, and we’ll be sure to dial right back in. So with that, let’s dive right into our panel discussion, finding your best workforce with AI and I want to introduce our panel for this session. I’m so excited to welcome our expert panelists today. We have Leanne Legas, who is the owner HR and people ops consultant and speaker. Welcome Leanne. We have Jenny, great Jenny. We have Jenny Newhart, who is the director for talent centered transformation at eight fold. Welcome Jenny and Jacob Proust, who is the director of compliance at BC forward. Thank you all so much for being here today. So just to give some context to the audience, AI has quickly become a part of our daily life. And for any strong HR leader, it’s essential to stay on the cutting edge of AI trends. One main area where HR professionals are incorporating AI into workflow is in talent acquisition, but there are ethical compliance and communication considerations when using AI to find candidates. And so this is what we’re going to discuss today. And we’ll kick off the discussion with the following question. And Jenny, Leanne and Jacob, feel free to just tell the audience a little bit about yourself and your work as you answer this first question. And Jenny, I’m going to direct the first question to you. But why is AI not a check the box strategy for the future of talent acquisition. So Jenny, I’m going to let you answer that first.
Jenny Neuharth 04:27
Yeah, so thank you again for having me here today. My name is Jenny Neuharth. I’m Director at Eightfold, and I’m on the transformation team, so my role is to come alongside organizations who are truly undergoing transformation, which is not doing the same things we’ve historically done faster, it’s looking at what we’re doing and changing it up entirely. And so when it comes to AI, not why it’s not a check the box strategy, or why it shouldn’t be a check the box strategy is because with AI, it’s something that you choose to begin and what I mean by that is. The people who are doing this right and being very successful with it are typically starting with one specific problem that they have within their organization, and that’s kicking off kind of their journey into AI. But then I guess HR has historically been more project based, so it’s like, we start and we finish a project and we go on to the next thing. When it comes to AI, this is program based. It has a comma, it doesn’t have a period. And this is something that you’re continuously going to sharpen your strategy on. And the reason for that is because AI is a different right, we have to make sure that we’re constantly putting in the right guardrails and barriers so that we are doing AI right. So that would be my, my answer on that, I love to kick it back to anybody else who’s on the call.
Erika Randell 05:45
Great. Thanks. Jenny, Jacob, what are your thoughts?
Jacob Pruis 05:48
Yes, thanks for having me again. Jake. Person, the director of compliance at VC Ford. We are an IT consulting and contingent labor company based out of Indianapolis, Indiana. I think one of the things, and really kind of building off what Jenny already said, is that to harness the power of AI has to be seen as an evolving component of a much broader talent acquisition strategy. So it’s going to involve understanding what’s the specific challenge that we’re trying to address here, what is the overarching goal of the organization, and that could be things like reducing time to hire, improving candidate quality, enhancing diversity, you know, any one of those things, but again, very targeted towards a specific challenge. And then we can tailor AI to address these specific needs by offering tools, you know, that’ll come along with it, like predictive analytics, automated resume screening, and a whole host of items. So it’s one of those. I always forget if it’s inductive or deductive thinking, thinking, but we’re starting with a very small and then we eventually broaden it out.
Erika Randell 06:50
Awesome, great. Thank you for broadening out that you know Jenny’s answer, and also broadening that out too. That’s great. That’s very helpful. And then Leanne, what are your thoughts?
LeAnne Lagasse 07:01
Well, hi everyone and Erica, thanks so much for having me. So my name is Leanne Legas, and I am an HR consultant and speaker and trainer, so I bring a little bit of a different lens to our conversation today. The work that I do is helping organizations think through their employee experience strategy and also their internal communication. And so I love you know, Jacob and Jenny, to your point, what I really kept, what I’m taking away from, what both of you just said, is it’s not a it’s not a check the box strategy, because this requires continuous improvement and iteration. And so a big piece of the work that I do is sort of helping organizations listen to their employees, or their potential employees, right? And iterating based on the feedback that we’re getting, what’s working, what’s not working. And I think that’s what I’ve seen a lot of organizations maybe miss the mark when they try to launch something like this, is they they get what they think is kind of like a cookie cutter strategy, and then try to plug and play without iterating based on the feedback that they’re getting along those along that journey, that candidate journey. And so that pumped me up to hear you both share that, because I think that’s very aligned with the work that I do, just with a little bit of a different angle. So excited to be here. Great. Oh, I
Erika Randell 08:21
appreciate that perspective Leanne, and that’s the part I was thinking about too. As far as that question, right? It cannot be cookie cutter, and you have to have that human touch. You can’t just, you know, say, Okay, we have the technology. Okay, let it go. Well, what about the human that has to work with that tool? So, great points and a great way to start off the discussion. Let’s move on to all right. Now that you have the technology you’re adopting, how do you optimize it for your recruiters and the candidates themselves? So Jenny, what do you think about that?
Jenny Neuharth 08:58
So I’m a project manager by trade, and so my first step, but when we’re talking about adopting or optimizing, is first to collect the dots of what’s working, what isn’t, what we change, because I don’t want to lead into any sort of adoption or optimization kind of journey if I’m not checking my own design bias that says, I need this, right? And so it’s really, really important. Take a cross section of your users. Take a cross section, you know, that’s candidates, and on the side, it’s like your end users within your organization, so who’s actually using the technology, and ask them, what’s working, what doesn’t, what do we change? And then, based on that feedback, we’re going to glean some insights, and then we’re going to calibrate those insights in terms of order of importance. And that’s, that’s typically where I say, choose to begin, but don’t, don’t go into this thinking with your gut instinct of like, oh, I need to fix this, because so often our gut instincts can be off. And so we’ve got to take this data driven approach that I’ll. I’ll kick it back to my peers in the call, sure.
Erika Randell 10:02
Um, Leanne, I saw you, I was taking notes, and I saw maybe that you were taking notes. Why don’t you answer? Because it seems like you have some good, good insights there.
LeAnne Lagasse 10:11
Yeah. Again, you know, Jenny, to your point, I think that anytime we’re as an organization thinking about adopting anything, right? It could be AI, it could be anything that is going to impact our employees, or, again, our potential employees. We have to lean in and do really, really good work on the audience analysis side of things. So, for example, unique to AI, you know, I will talk to you, to people who will tell me, you know, I’m still really skeptical of AI. I feel very anxious about how, again, how my dad is being used. I feel weird interacting with a chatbot on a, you know, on an interview or something like that. So I think what one thing I’ve seen, one mistake I’ve seen leaders make, is sort of assuming that everybody is going to be as pumped up about the bells and whistles here as we are, you know, and especially when you talk about maybe an HR leader who’s thinking, this could change my life, you know, for me to be able to streamline and and, you know, automate some of these things, these processes have just been eating up my time. And so we get so pumped up about it. And so, Denny, I love your point there about design biases. You know, well, there’s the problems that it solves for us, but then there’s also very important work to be done, or work to be done on the audience analysis side. How do we send messages that resonate with the skeptical and with the enthusiastic? You know? So I think that’s a big piece of the puzzle too.
Erika Randell 11:37
Absolutely. Jacob, what are your thoughts?
Jacob Pruis 11:41
No, I loved hearing Jenny talk about the project management aspect of it, because it really makes me think about kind of the Agile frameworks that I work in a lot, and the idea of kind of constantly identifying who your stakeholders are, figuring out what their value stream is, that you’re trying to enhance here, and then making sure that the product that you’re selecting and how you’re going about it is really hitting the mark for them. So you’re really co creating that value from an AI perspective, along with your HR, sharing your stakeholders and with your candidates. So again, it’s really all about that, that customization and just understanding that customer need, whether that’s an internal customer or an external customer,
Erika Randell 12:26
awesome. And I think Jenny had an example that she wanted to share, so let’s hear it.
Jenny Neuharth 12:31
Yeah, no, I just when Leanne says something about chatbots, it kind of brought up an example in my history that I think is very applicable here. And so in a formal role, we were building a conversational AI product to be used with my end users who were candidates in the salon industry or hiring managers in the salon industry. And we went into this thinking like, Okay, this is what’s gonna work. And there’s all these features, but my internal users, right? So the people who owned the franchisees for where I worked had a design bias that said people aren’t going to want to talk to an AI bot. And it was so interesting, because we ended up taking a couple weeks just to analyze this with the candidates, and we actually found the complete opposite. They preferred to talk to an AI instead of talking to a human and felt more comfortable being able to ask their questions, and so it was just this unique piece, and they could ask it in the middle of the night when there wasn’t anybody available, so it could meet them where they’re at. But just wanted to show that as an example of like, sometimes we have a design bias that says X isn’t going to work for whatever reason, and that that piece that should be a signal that we go and then we kind of dig into and figure out, like, is there something behind that? Because, to Jacob’s point, you want to co create kind of what this experience looks like. So that was the example. I just want to
Erika Randell 13:52
share any, any thoughts further Leanne about that. I know you had some.
13:58
Yeah, no. I mean, I, I think that’s, I think that’s a really good example, because it’s, it’s easy for us, on whichever side you know, of the project that we’re on, to sort of make assumptions, and that’s why the listening piece is so important. So you wouldn’t have been able to execute and implement had you not leaned in and done the listening work, right and and I think, you know, we’re so used to doing this when it comes to our customers or our clients, and we’ll, we’ll spend hours and hours building out these, you know, robust customer and client journeys, and then we won’t take the time sometimes to do that with, you know, our employees, with our applicants, and really think through what, what’s going to move the needle, what are the barriers? And then on the backside of that knowledge is, how do we build communication to ramp up, you know, excitement, or to decrease uncertainty or to overcome objections, right? That that communication piece is, is to me, and I’m biased. My design bias is the most important piece. Yeah, yeah. Yeah,
Erika Randell 15:00
I’m excited we’re going to dig into that a lot about communication in just a little bit. You know, we had something else that we were going to discuss a little bit later on, but I think it really does apply to this discussion, is buy in from leadership. I would love to talk about that a little bit more, because we’ve already touched on that a little bit. So, Jacob, how do you get your leadership to buy into using this technology?
Jacob Pruis 15:25
Yeah, a lot of times it comes down to, you know, demonstrating the ROI behind it. You know, when you’re presenting to executive stakeholders, and you want to get them to you to make investments in something like AI, especially something that’s, you know, let’s, let’s be on the cutting edge at this point, you’ve got to be able to deliver and understand what that return on investment is so really developing the business case behind it, and presenting that to your stakeholders, I think, is crucial. Anytime you can identify, you know, folks that are similarly situated to yourself, and if you’re able to get your hands on you know, even if it’s anecdotal data, but anytime you can get true, objective kind of statistical improvements, that is always a positive as well. So I think that is really one of the key things, is really defining what is the business case. How are we going to improve? You know, whatever problem we are going to try and solve? And then I think another big part of it kind of harkens back to the very first question. First question we talked about here was identifying what the problem is that you’re going to solve. You can’t go to your executive leadership and your stakeholders and just say, I want to bring AI into HR. It’s got to be what are we going to do with it? How is it going to make our business processes better?
Erika Randell 16:39
Absolutely. Jacob. Jenny Leanne, anything to add to that?
LeAnne Lagasse 16:45
Well, first off, what I will say is Jacob stole all of my very best points that I was about to make that I have written down here. And number one there is that you have to when you’re communicating to really any internal stakeholders. But the the number one, kind of, the very first thing that has to happen, I think, is you have to go in knowing how you’re going to communicate around the specific problem we’re solving for and so this is, this is bigger than it sounds, because a lot of times when I talk to HR leaders, I mean, I will tell you when I do a lot of training on a lot of different topics, and it is always like, the number one question that I get asked is around buy in. It could be about any topic. It’s okay. This sounds great, but what about buying in? And what I have found is that the hardest, hardest arguments to make are often what I’ll call like, Good to Great arguments, where you know your internal stakeholders, your leaders, are kind of going. I mean, like, things seem to be fine, right? Things seem to be operating just status quo, business as usual. It seems like a lot of thinking that I would have to expand to really explore that. So the good to great initiatives, which I think AI is absolutely a good to great, you know, you know? And I love even the idea of, like, starting small and then kind of building and people getting bought in and seeing, you know, oh, there is this is. This is helping us get traction in these areas, right? But solving a unique problem has to be step one. And then the only other thing I would add about getting buy in is we know that. So in my former life, I was a communication professor. Actually I still teach one class for Missouri State University, if there’s any Missouri State fans in the room, but I used to teach persuasion classes, and one of the things I would always tell my students is that the most persuasive messages are what we call two sided messages. And two sided messages are when you actually point out, and then, of course, refute the counter argument, though, that’s why in advertising, I mean, you see people directly compared to a competitor, right? That’s a two sided message. Two sided messages are typically much more persuasive than one sided messages, where we’re just trying to say, Hey, we should adopt AI, right? But if I take the time as an HR leader, as a people leader, you know, to to say, look, these are, these would be the reasons not to do this, you know. Or here’s, here’s what the objections are, here’s what the limitations are, however, and then I’m refuting and I’m overcoming those objections, those messages are going to be more persuasive, typically. So that’s the only thing I would add to Jacob’s other, otherwise perfect answer is what I would say.
Erika Randell 19:26
It was pretty perfect. That’s true. But I love, I love what you added, Leanne, I think that’s great. Jenny, what can we add that’s a little bit different.
Jenny Neuharth 19:33
I was right, so similar to Leanne. I had my answer, which was very, very similar to Jacob’s, and that is an indication y’all who are listening that there’s something behind it, right? You have three people who are considered experts in the field who had the same answer, right? Very, very similar answer, revolving around what buy in and budget, like being able to go through those things but in order to add a little bit. More to that. So this is an important thing. So I hope all of you, all that are back at home are tuning into this. You need to speak the organization’s language, and specifically, you need to speak the leadership language. What’s in it for them, right? So speak to that with them. To go back to my communication studies kind of training, because I was also a Communication Studies major. There’s a theme here. But and then additionally being able to make that business case from a dollars and cents standpoint, so sometimes we don’t always have this, but being able to figure out what are the numbers that I can create in that equation, so that I can be the neck that turns the head to where the problem is and get ideally, I want leadership to see like, Oh, that’s such a huge problem. We have to act. But then, if I pair that data driven argument with here’s the cost of an action, which is an important piece too of like, if we did nothing, this is what could this is what we’re opening up to in terms of risk. It really ends up being kind of just a different ball
Erika Randell 20:59
game. Excellent. Oh, I feel like we could talk about this for a long time just this subject. Thank you so much. I do want to go over to our attendee chat for just a second. Maddie, you had asked the audience a question. Could you just repeat that question and then tell us what some of the responses have been? Yeah.
Madeleine Collins 21:19
So I’ve actually asked two questions so far. First, I kind of got a pulse on everyone on how they’re feeling about the adoption and implementation of AI in their organization. A lot of people are feeling excited, but also sort of like knowing that AI isn’t going anywhere, so you have to get on board with it no matter what. And everyone seems genuinely concerned about the ethical and the compliance issues, you know, ensuring that there is a human touch in this process the entire time. And the same can be said while communicating this technology and getting leadership on board too, just making sure that there’s a multi faceted approach with using AI with strategic goals.
Erika Randell 22:00
Great. Thank you to our attendees for, for you know, giving us your responses and what you’re hearing and seeing, it’s really important. So thank you so much, and we’ll continue to ask some more questions of you, because we’re interested to hear what you have to say. All right, so we’ll definitely move. Thanks, Maddie. All right, so let’s actually Maddie say a word that we’re going to go ahead and target right now. It’s what compliance issues do HR leaders need to keep in mind when using AI. And how do you work through these issues? So Jacob, I’m going to start with you on this and tell us. Tell us what you think.
Jacob Pruis 22:39
Yeah, so I’ll put a brief. You’ll kind of notice out there, the EEOC has published some guidance on use of AI within, you know, within hiring, within human resources. So if you haven’t checked that out, I would highly recommend you go take a look at it. It does get a little technical, but definitely worth the read nonetheless. You know, when we’re integrating, integrating AI into recruitment, it is going to introduce a number of compliance challenges. I’m a firm believer that those challenges do not outweigh the benefits of implementing AI. It is still definitely a very good thing to do if we want to continue to modernize HR. But I think one of the most pressing issues we have to look at is the design and implementation of ethical algorithms within, you know, our AI systems. You know, AI systems are only going to be as unbiased as the data that they are trained on. So we have to make sure that any data sets that were used when we’re developing those ethical algorithms were based on unbiased data sets. Now, some of that can be done through kind of due diligence processes when you’re evaluating different vendors, getting legal involved and sorts of that. But that’s, I think, one of the biggest things that we have to look at from a compliance perspective. I think another one is just generally governance, and it even boils out into a broader sphere of you know, just when are we allowed to use things like chat, GPT, your other solutions like that and so really setting policies in place, working with your IT teams, working with your legal teams, to understand kind of, how are we going to use AI as a company, developing a policy behind that? But it’s not good enough to just develop a policy. We’ve got to train our users on it, and we’ve got to enforce it as well. So I think those are probably two of the really critical things from a compliance perspective that I’d encourage everybody kind of be mindful of.
Erika Randell 24:35
Yeah, great. Thank you. Jenny, what do you think? So
Jenny Neuharth 24:40
Once again, Jacob, You took the words out of my mouth, which is a great, good problem to have. So I think the only thing that I would add to what Jacob is saying is become a student of the different compliance and regulatory bodies that are out there. So. So one of my friends is Keith Sonderling, Commissioner of the EEOC, I think, until the end of this month. But like one of the things when, if you ever hear Keith speak about the compliance and regulatory aspects of this kind of topic, he’ll refer to the fact that the laws that govern it are the same laws that have been in place for a long time. They actually have blanket applications to these areas. And so one of the really best ways that you can do is to start to become a student and start to ask the questions, what are the different regulatory pieces? What if I’m in a specific state, right? What is my state bringing forward? If you’re in California, for example, you guys have some legislation that’s coming forward that’s going to be very similar to the EU AI act, right? Like, there are a lot of different pieces that are coming here, and having some sort of awareness for that is really, really important, because it’s going to help you be able to, again, deliver and drive that business case to leadership when they have those questions, because they should have these questions about like, how do we, how do we regulate it? How do we, you know, how do we make sure that we’re not doing the wrong things right and and bias? Again, this was said earlier, but this is not a check in the box thing. These are things that need to be done on a regular basis, because the way that some of these algorithms work is that they can learn based on historical data, and we always need to make sure that we are training it based on the right data, right? Because if we haven’t historically done the right things in our organizations in terms of who we promote or who we hire, right? And then we go and use that as a template for what success looks like, and we’re coding our algorithms with that, we’re going to get closer to us, and it’s more the same thing. And so we want to make sure again, have that awareness, become a student and figure out again governance, where you’re going to be able to check and do this on a regular basis. And a lot of you out there probably have a benefits broker, or somebody who might have experts in this field, or you might partner with it in or a tech vendor, right? They often are going to have some sort of stance on this topic, or additional ways that you can dig in and learn more, and so also be that owl. And that’s like always asking, who does this, right? Who can I learn from? Who might have free resources? And you’re looking at that 360 degree view, because, again, this is something that you choose to begin with, you should always be trying to sharpen your approach to this, if that makes sense.
Erika Randell 27:22
Yeah, it sure does. Jenny, I’m so glad you mentioned those resources. And you know, because people, I could just hear them saying, I don’t have time to collect all this information. I don’t have time to dig into this. So these are great resources for people to go to. I will put a plug in for an HR daily advisor. We also write on this topic as well. So please come to our website and check out our articles. Leanne, what is your response?
LeAnne Lagasse 27:48
Yes, well, so while I am a 0% expert on the compliance side of AI usage, what I do, what I’m hearing there is, okay. We are on the inside internally. We need to be checking our biases. We need to be figuring out these frameworks. When I help organizations with their employee listening and so whether that’s employee engagement surveys or focus groups or stay interviews, one of the biggest weaknesses that I often see is employees saying we really wish communication was more open. So when we dig a little bit, what we find is that it’s not that employees want to know everything, or candidates want to know everything, it’s that they want to understand frameworks and decisions, you know, decision making frameworks. So I was just thinking kind of brainstorming as you two were sharing that I would imagine one way to really overcome some of the hesitancy or some of the skepticism would be once your organization has a pretty good sense of how you’re using and how you’re not using and I do realize that you’re always iterating, but is why not communicate that to your candidates? Hey, everybody, this is how we are, this is how we use this technology. This is how we don’t use it. I mean, this is how your data is, I mean, I told myself that that’s the next step in really building out a more robust candidate journey. Is, not only are we going to use these tools and technology, hopefully ethically, right and legally and all the things, but how can we communicate it and in a way that increases trust and decreases that uncertainty that candidates may feel about the process. So that’s just my little plug. There communication,
Erika Randell 29:28
no, and it’s, it’s so welcome. Thank you so much. Leanne for that, that extra piece. Maddie, anything coming from the attendees, on, on their take, or any questions on the compliance area.
Madeleine Collins 29:44
Um, not so much conversation about compliance beyond, you know, making sure that it’s ethical and has a human hand in the decision making process. We did get one question about how to get companies to budget for AI. So. Um, which I am saying out loud now, but could save for the Q A at the end of the session? Yes, yeah,
Erika Randell 30:06
Let’s save that for now. But thank you so much. Great. So um, let’s go into now, um, I think Leanne really kind of set the tone for that. Let’s dig into the communications part of this, because this is a big part of our discussion today. And so when you’re looking at when, when hiring teams are looking at adopting AI, how do you create that communication? What does that look like? So Leanne, I am going to start with you for this question. So tell us what you think on this topic. Yeah,
LeAnne Lagasse 30:47
Well, in truth, like consultant form, I’m going to say it depends which is always the worst answer, but it’s usually the true answer, you know. So my apologies for that, but, um, but it is true. So every organization is so unique and so different, and what your hiring team does with the function of that, what the role, you know, the scope of the role, all of those things are going to impact the way that you would answer this question. But what I would say is any organization should hopefully go through an audit of your processes to figure out, okay, what are, again, it’s this candidate journey. What is the journey by which this person is, you know, we’re spanning this workflow, right? What are all the tasks associated with, you know, the things that have to happen for us to move the, you know, move the ball along. But then, in addition to what are all those tasks, it’s asking, Okay, well, what are the messages that we want to send, and what are the messages that we need to facilitate, you know, or that we want to elicit and and when you start building out a more strategic communication plan unique to your organization, right, then you can go back and say, okay, where does it make sense for us to use this Technology to send messages, you know, where does it make sense for a human connection to take place? For this message exchange? Where? Where do people prefer to speak with a chatbot? And, oh, it seems like, based on our research, they prefer that up to this point. And then here they really want a human, you know? So it’s, it’s listening, it’s analyzing, but it’s building a robust journey and then iterating and assuming that we’re, you know, we’re going to change based on the feedback that we’re getting. To me, that’s the key. Is auditing your journey and then building out the messages that you want to facilitate and you want to, you know, receive from candidates.
Erika Randell 32:39
Excellent. Thanks for outlining that. Leanne Jenny, what about you?
Jenny Neuharth 32:46
Great, great points. Leanne, I think that the only piece that I would add is for the people who are on this call to remember that one of my first conversations, my first speaking engagement I ever did in this space, was a disruptive HR talk, and I talked about how blueprints don’t sell cars. And so it was this idea that in the HR world, we tend to lead with a blueprint instead of a brochure. And we need to remember that that’s not the right way, right way to go about it, because blueprints don’t sell cars. Again, brochures do, right? So being able to distill the change down like through the lens of that human who you’re impacting, whether it’s a hiring manager or a candidate or an internal recruiter, to almost like, sharpen that message to help it be through the lens of what’s in it for them, and why does that matter? And sometimes it’s like, what’s the why behind the what? Right? So being able to like, just be able to share like, so yeah, the most. And this is not how I would say to do it, but I’m just, like, the basic concept, the most impenetrable black box is the human brain, right? So like, when we talk about AI and being able to see responsible and, like, transparent AI and things like that, part of the reason for that is because our human brains, which are typically the ones that are making decisions about who fits or who doesn’t, they’re subjected to the experiences we’ve gone through in our lives. And we’re talking about somebody’s ability to get a job, and we’re relying on something where, if I haven’t had my coffee for the day, my decision might be different. That’s not a good thing, right? There’s subjectivity involved. And so when I explain this aspect of like, okay, yeah, AI can be scary. It can be bad. But also, if we don’t have any sort of objectivity about who works into who fits and who doesn’t, that’s opening us up to risk, and it’s preventing us from being inclusive as an organization. Like when I explain that, why behind the what? Typically, again, I can help to sell that change internally, because it’s not about finding the right product. It’s about how you message and how you sell that change, and you drive the adoption for that change. So that’s the only piece that I would add. That’s a good
Erika Randell 34:53
addition. Jenny, thank you so much. Love that point. Jacob, yeah,
Jacob Pruis 34:58
I think the only, the only thing. I would add it, you know, especially when we’re thinking about talking to our internal teams. And I think Jenny talked about this a little bit as well, you know, the idea that implementing AI can sometimes be scary for our internal employees. You know, we hear it in the news, sometimes about, you know, the fear that AI is taking jobs away from individuals. So I think it’s always important when we’re adopting AI, implementing it within our tech stack, to make sure that we’re messaging it correctly, and that look, this is not designed to replace anybody. This is designed to augment your current capabilities, make you more efficient, more productive, make the workday more enjoyable for you, kind of take over some of those repetitive tasks that maybe you don’t want to do, and you’ll allow you to really dive into the fun stuff of everyday work. So I think that’s a really important part about it as well. And, you know, maybe that’s the idea of, you know, summing it up, and then what’s in it. For me, that’s something I always like to think of whenever I met your doing Change management is, you know, what’s in it for me, for the audience,
Erika Randell 36:07
Wow, terrific. Any follow up on any of those points, because this is a terrific conversation too. Okay. Well, we’re going to continue with communication. The next one is, how do you communicate, or, excuse me, how do you use AI to communicate with talent throughout the hiring cycle? So Leanne, I’m going to jump back over to you. What are your thoughts on that?
LeAnne Lagasse 36:34
Yeah. So again, it kind of depends on the uniqueness of your organization. But what we do, what we do know is, okay, when, when people are looking for a job, right? There’s just a host of factors that they’re considering. One of the needs that we know the candidate has is the need to feel pursued, right? That is, that’s, that’s a piece of it. In fact, you know, I was just talking to a director of a large Career Center at a university not too long ago, and they had just undergone this huge study on sort of the, you know, emerging workforce and college students. And he said one of the biggest surprises from the research that they found was how many of these college students said that if they’re the hiring process had too much automation in it that they would tune out because they wanted, at some point, to have some human to human contact, and to feel as though they were seen as a unique person and not just a number on a screen somewhere, right? And I think that’s back to our biases. I’ve heard people say, well, oh, you know, Gen Z or like young people, like they’re totally on board. And I say, Well, it depends. It really does, right? We’ve got to do good audience analysis, analysis and segment and so I think that that part of it is going okay again, back to the drawing board. How do we send individualized messages through different modalities? How do we use AI to send individualized messages in cool, creative ways, right? And also that saves us time and streamlines and does all sorts of positive stuff. But then, where can we individualize, you know, in more robust, you know, interpersonal ways? So I do think it’s, it’s going. How do we accomplish the goal of individualization or personalization? However, you want to say that using these different modalities, we know that another need that employees have during the very beginning of the life cycle is to reduce uncertainty. In fact, there are researchers that found that candidates are more likely to research the the organization, the job do all sorts of information seeking behavior after they have signed an offer letter, like after they’ve signed a dotted line, they’re more likely to do additional research, and that’s called post decision dissonance. It’s what happens when we make a big decision that we feel like it would be difficult to reverse that. That’s when people need to be sending more, you know, more informational messages. So, I do think it’s analyzing your workflows and finding opportunities to personalize and customize. And where do we need the human, you know, interpersonal touch to get to the outcomes that we want
Erika Randell 39:19
absolutely before we move on to Jenny and Jacob Leanne. Do you have any examples of that personalization or individualization that you can share?
Madeleine Collins 39:28
Yeah,
39:30
yeah. So a really, really good example, I think, is I was talking with one of my clients a couple of weeks ago, and they were talking about how as a part of their their hiring process, and just even application process, they were collecting some you know, quirky in for you know, information about employees, I say quirky, but just their favorite this, and their favorite that, and how they were using AI then to generate some really customized kind of, again, quirky messages. Back to employees, almost adding some humor into the mix about some of the things that their employees had shared and that they specifically said, we got some really good feedback about that, that the candidate said, Oh, that was really funny or quirky, you know. And so I think there are ways to get to those outcomes using different methods, but you do have to be strategic about it.
Erika Randell 40:20
Yeah, awesome. Thanks. Leanne Jenny, let’s go to you. What do you think about this?
Jenny Neuharth 40:26
So just to ground everybody, because I can sometimes lose track of what the question was. The question was, how do you use AI to communicate with talent throughout the hiring cycle? Yeah. And the one thing I just wanted to add on is to remember that AI is not just content generation. You can also leverage AI from a scheduling aspect. You can leverage AI from an engagement aspect, right? Like, there are a lot of different ways that you can leverage AI, and some of the best in class technologies that are out there, I know we have it baked into a lot of different things within eight fold. Is it like being able to identify, like, what does good look like? And how do we reverse engineer to use AI to help enable good to occur at scale? Right? That’s really kind of like, what I would say is, what are the best you know practices are using AI to communicate and again, checking your own bias that says, like, it’s just content generation. It’s not just content generation. There are a lot of different like touch points within your within your journey, like, for example, when you we leverage AI at the front end of our experience for our customers, so they upload their resume, and all of a sudden it’s going to analyze the skills that are involved with that human, create that skills picture. And then on the back end, it’s going to surface right the path for that candidate. So instead of them being the filter, their skills are actually a filter that are helping to surface these jobs. And so it’s a very, very, very different and almost like, enables you to choose your own adventure. And like, that’s a way that you’re using AI, right? So that would be my answer, not monologuing. So to flip it over to Jacob,
Erika Randell 41:57
sure. And I just wanted to say thank you for that example, Jenny, because that is exactly. It’s a great example of how you can envision somebody’s journey and how AI can be part of that. So thanks for that, Jacob. Tell us your thoughts.
Jacob Pruis 42:11
Yeah, no, I think Leanne hit the nail on the head there without where we need to make sure that we’re balancing, you know, kind of the automated communications with the personalized as well. So that’s a really important aspect of it. But I think, to Jenny’s point, we can also use AI to kind of help us come up with those more personalized communications as well. So it’s, it may seem a little dissonant when we think about it, using, you know, a chat bot or some sort of workflow, you know, to develop those, I think as we continue to see AI evolve, you know, it’s going to be harder and harder for us to be able to tell, you know, where was the individualized human contact versus, you know, where was the AI driven contact there. So I think we can use it across the board there, and then again, even outside of communication, you know, during your confirming receipt of application, scheduling those interviews, providing updates on the status of an application. You know, they all sound like really simple things, but I think if you talk to a lot of HR folks out there nowadays, that takes up a lot of time during the day. So if we can have a chat bot or, you know, some sort of AI tool to help us out with that. Again, I was thinking of it. It frees us up to do the fun things that we want to do within. HR,
Erika Randell 43:28
awesome. Great love. Love that. How you tied it all together. Thank you. Jacob Maddie, I’m just going to swing over to you for a second for any extra comments or things that the audience is saying.
Madeleine Collins 43:43
The audience has touched on a lot of things that our experts have been going over, just ensuring that you’re being transparent and having guidelines for your employees as well. Right before you started talking, Jacob, someone mentioned that updating candidates where they are in the process is a huge help, especially keeping candidates engaged along the way.
Erika Randell 44:06
Awesome, great. Well, I’m glad people are using that as well, so that’s great. Okay, we are getting close to winding down, but let’s go to how HR professionals can effectively integrate AI tools into their communication strategies to enhance the candidate experience while ensuring the authenticity and human connection. So we did talk about that a little bit. I was reading a study by Grammarly that, and this is not surprising, but 88% of people spend most of their entire work week communicating, and it was saying that 73% of workers say Gen AI helps them to avoid miscommunications. And I thought that was really interesting. So we’re really seeing this integration. So we’ll just talk a little bit about this. We won’t spend too much time because we’ve already. Touched on it, but let’s talk about communication strategies and enhancing that candidate experience. Maybe there’s something we haven’t touched on yet, so if there’s anything there that we can add to we’ll just talk about that for just a little bit.
Jenny Neuharth 45:15
I think the only thing I’d want to double click on is something that Leanne had said, which is making sure to audit your existing processes from high to post higher, right? So what are those candidate touch points? What are those journey points? What is your existing experience today, and making sure that you’re not just doing that on your desktop, but also doing it on your mobile phone, right? Like, what does that look like, being able to again analyze where we’re at before we start to reverse engineer where we want to go, because that’ll help you be able to understand, right, like, where are those points that we might be able to, you know, to sharpen or to get better on? And so that auditing piece is, is really, really an important one that I just wanted to double click
Erika Randell 45:57
on. I’m glad you did, Jenny, it’s true. That is a great point. Anything else, otherwise we’ll move on. Okay? And then our last question, how do you get leadership? Oh, I’m sorry we went over that one already. So actually, we are. We have gone through all of our questions. You guys have done such a great job explaining our topic today. So with that, I’m going to move us over to our Q and A session. Maddie has been watching our Q and A chat, and maybe some of them came in through the attendee chat as well. So Maddie, you’re on the phone, I’m going to probably take myself off camera, and I’ll let you speak, and you can go ahead and start with the Q and A session, but I just wanted to remind the audience that your please use the Q and A widget to type in your questions, and they will be anonymous. We won’t call out your names or anything, so feel free to ask your three experts and Maddie over to you.
Madeleine Collins 47:00
Yeah, so we’ve already gotten a couple of great questions into that chat, so everyone who’s still watching make sure you add in any other questions you might have thought of along this whole conversation. But one thing that was asked of us is a topic that we haven’t quite touched on yet, which are fake or ghost candidates. So what sort of insights do you guys have in helping these illegitimate candidates out of the hiring process or identifying them, and what role does AI play in that? Jenny, it looks like you notice you recognize the term ghost candidates.
Jenny Neuharth 47:39
Off mute. I apologize. I have a 150 pound Mastiff who’s in the corner of my office right now. And I don’t know if you guys can hear her snoring, but I have, like, tossed stuffed animals at her trying to get her to wake up, and she is not. And so if you hear snoring, it’s not me breathing heavily. It is my dog ‘s horse in the corner of the room. But I think this is such a good, good topic. And as you can see, I have no poker face, so you can always know what I’m thinking, because my face has subtitles. But when it comes to this topic, like, remember generative AI is being utilized by your candidates at scale now. So there are technologies that are out there that are helping to, like, reverse engineer an application or a cover letter based on your job advertisement, right in order to try to get through the town acquisition process. The thing, I just want to remind you all of this, it’s not necessarily always about getting more candidates at the top of your funnel. It’s about making sure that you’ve got the right filters to be able to sort through the noise for who is the right type of person, and that’s where, again, you know, in my world, I help enable people to like on the basis of skills. So instead of those external characteristics being able to identify, like, what are the skills that are needed? Because it helps to be a better filter. So the data shows, but again, figuring out, what are the ways that I can knock those out? Because it’s not going to be one size fits all for your organization, but you’re going to have to think more diligently about, how do we fill in the blank? I know that I talk to organizations on a daily basis, and I’ve had some who are like, we get 17,000 applications for a specific role. 17,000 applications is a lot of applications, y’all and like, how do I, from the EOC standpoint, like, equitably go through all of those applications, right? Like, I probably can’t, but of those applications, my guess is a lot of them are, again, ghost candidates, or there’s some sort of RPA in the background that’s like, mass applying to people. And again, my answer is going to be like, you have to figure out that better filter, and it’s something that you choose to begin with and it’s something that you’re always going to have to sharpen your strategy on. As it relates to this,
Madeleine Collins 49:54
definitely. Leanne Jacob, what do you guys think ?
Jacob Pruis 50:00
This all you, Jen, okay, sure. So, yeah, I mean, AI and data analytics, I think, is gonna, you know, play a huge role in helping us in kind of identifying and filtering out those, those fake candidates. You’re just like Jenny mentioned, you know, as as it kind of continues to evolve, and as it continues to improve, you know, we’ll see things like machine learning algorithms that can potentially analyze patterns and candidate behavior and application data to potentially flag for suspicious activities, detecting anomalies, looking at the resumes themselves. So think resume parsers. We’re all familiar with resume parsers, you know, within our HR stacks, you know, put those on steroids, you know, and we’ll be able to see a lot more benefit out of things like that by leveraging AI. But I think Jenny made a really good point, just like we’re using AI, all of our candidates are now using AI as well. You know, I see it in the news all the time about, you know, teachers and students having to deal with, you know, a very similar issue. So I think it’s something we can continue to use AI to help out, you know, with that. But I would also say that I think the prevalence of fake candidates is not a new problem. So in addition to using things like AI, there are also some old school, kind of tried and true methods, you know, that have to go along with that as well. You know, when we’re doing interviews with folks you know, making sure that you know the person you’re interviewing is the same person who submitted the application and things like that. So I know we’re very focused on the technology side, AI site here, but there are still some kind of old school, tried and true methods that help us out with that as well.
51:49
Yeah, definitely. One
Jenny Neuharth 51:50
An additional thing that I wanted to add to that is it’s really important to make sure that whatever filters or changes you put on to that process are reviewed by somebody legally to make sure that you’re not also putting filters in place to actually open yourself up to risk. I know there was a huge thread on LinkedIn about, oh, somebody used a generative AI bot to be able to create their resume or to create their cover letter, right? Because they had two of the same cover letters that were out there, and they were identical, so they automatically decided that those two people shouldn’t be considered for the job. Think back to being able to create an equal employment opportunity, right? I am now saying that if you use generative AI, you cannot be considered for this role, but I haven’t given awareness to my candidate. I’m actually opening myself up to risk. Like, I know Leanne’s a professor. I do a lot of conversations with professors and universities, because they’ll often come to me and be like, how can we, how can we regulate that? You know, the use of AI? I’m like, You’re asking the wrong question. Y’all, how do I teach it ? How do I teach my students how to fish with AI, right? But another thing that people don’t always understand is that when it comes to content creation, often, there was a big study that came out people who were exchange students from other countries, their content actually got flagged as being Gen AI when it wasn’t, because the methods for how people were writing were very similar to the Gen AI, right? And so sometimes you can put regulatory pieces in place to try to prevent this, but it’s actually preventing, you know, the quality of your hiring process.
Madeleine Collins 53:40
That’s a really solid point. And speaking of the hiring process, do you guys have any advice for budgeting, for AI technology, or if you have a small budget, where to focus that those resources
Jenny Neuharth 54:01
here? But yeah, look, Jacob, you go first.
Jacob Pruis 54:04
Okay, so I would say, so the first question, I’ll start with. The second question, if you have a small budget, where do you start with? I think I would look at there, you know, what’s your biggest pain point? Then where, you know, where can I get the most return on investment for a small budget? So I think that is where I would start in terms of budgeting. From there you’re going to be likely, very reliant on, you know, engaging with, you know, external partners who are going to help you identify, you know, the type of solutions that you’re going to need, and what’s going to be best for your specific environment. Rely on their expertise, and they can help you with that, and they’ll likely help you with building out that business case as well for presentation to executive stakeholders. So I think you know again, figuring out the problem you’re trying to solve, working with some external partners to identify what is great. Solutions are. And then back to one of the questions we talked about earlier. You have to build out that business case for executive stakeholders and show that you’re going to deliver the results you need and how it’s going to benefit the organization at large as well.
Jenny Neuharth 55:15
Yeah. And the only thing that I would add on to that is one thing that I’ve always done in my I guess, experience, because I was a former HR tech leader prior to joining April and then HR leader, one thing that was always my go to, and granted, I worked for sec, regulated companies, typically, so like, they’re they’re regulated on the New York Stock Exchange, right? And part of that means that there are disclosures that are out there, like proxy statements and 10 Ks, that you can actually go and see what’s, what’s the concern for my organization at the top right now that you have generative AI tools out there too. You could actually download your proxy statement, upload it and say, what are the, what are the aspects that relate to human capital management that are in here that I could be able to build my business case towards. Every time that I have, like gone for a budget, I typically haven’t had a budget, and so I’ve had to make a really compelling business case that explained my why behind my what and how to translate to the CEO or to the CFO to explain why this matters. And so when I do that, I can create, again, that really compelling storytelling that’s making them not just think we have to do this, but we have to, and we can’t not do this like that’s ideally what you want to do. But when you can frame it back to the top right of your organization, your board of directors, what are they looking into? Right? A lot of organizations have ESG goals. So environmental, social governance. A lot of those ESG goals include human capital management aspects, right? So being able to create more opportunities in my organization, like if you’re able to then go understand what those are and say, Hey, I don’t want this just to be performative. Here’s how we can actually operationalize what you said to our investors or to the street, that can help to, again, make a really compelling business case. The only other thing that I would remind people of is it’s so important not to just point out the problem, but point out the solutions to the problem, right? So we’re going to figure out what that problem is. And then one of my things I always do when I’m working with, like, executive leadership, is I’ll give them three different options for how to solve the problem, not because, again, they’re they hire me to solve problems, not to bring them problems. And so then I allow them to make the choice of, like, how we’re going to go about this, right? But I’m not just bringing problems to them. I’m bringing solutions to them, and then I have all the data in the back end to support why there’s a problem. And so just remember, it’s not just about problem spotting. It’s also about being able to be that strategic partner, helping to solve the problems.
Madeleine Collins 57:51
That’s awesome. That’s really good advice. But unfortunately, we are approaching the end of this session, so I’m going to hand it back to Erica to close us out.
Erika Randell 58:04
Thanks so much Maddie and Jenny, Leanne and Jacob. Thank you so much. I have loved talking with you today. Thank you for your expertise. You’ve given us some great advice. If I give you each like 10 to 30 seconds, what is the one thing you want the audience to take away today, Leanne, what would you say?
58:25
I would just say, as is the case with all communication, step one is leaning into audience analysis. And the more you lean into your audience analysis, the better equipped you’re going to be to bring the solutions to the table that are going to move the needle for you. So audience analysis is, is number one for me,
Erika Randell 58:44
perfect. All right, Jenny, what do you think?
Jenny Neuharth 58:50
I think the big problem that I would just reiterate is figure out what your problems within your organization are. Be very crystal clear what those are. And then once I figure out what that reverse engineer is to solve that, right? And so sometimes that reverse engineering aspect doesn’t necessarily, ideally, it shouldn’t be the way that we’ve always done it, because we’re trying to make things sick. But that is way more than 10 seconds so that my face would be able to understand what the problem is with absolute clarity, and then a pressure test to make sure that it’s not just you that thinks there’s a problem, but your organization thinks there’s a problem, and then reverse engineer anticipate. Awesome.
Erika Randell 59:24
Thanks, Jenny and Jacob.
Jacob Pruis 59:27
I think the key takeaway it’s AI is a powerful tool. It’s a powerful enabler for talent acquisition within HR, but its true value is always going to lie in how it’s implemented and how it’s integrated within your existing business processes. So just, you know, make sure, again, I feel a bit like a broken record here. We’re identifying the problems within our current organizations, and we’re figuring out how we can use AI to solve those problems.
Erika Randell 59:53
And that’s exactly the point of this conversation. So thank you all three. Um, I have just added a link to a conference, a one day event that HR Daily Advisor and HCI are putting on about AR, HR and AI, and it will address some of these same topics for our audience. It’s October 22 again. I have the link in the attendee chat, so please check it out. We’d love to have you come. We’ll be talking about all kinds of compliance and recruiting regulations. We’ll have attorneys there talking about that. So I just wanted to point that out and also again, thank you again to our experts, and thank you to the audience for joining us today. Great conversation. And thank you to our sponsor, eight fold. We just enjoy having you work with us. As I mentioned earlier in our introduction, the session will be available on-demand for you 24 hours from now, and you will receive a link to that recording, and one more time, I’d like to thank you all for attending and have a wonderful Day. Enjoy.
1:01:10
Thanks, everyone.
