#71: Process First, Tools Second: Real AI Results from Healthcare Recruiting

1 00:00:00,320 --> 00:00:02,640 SPEAKER_00: Welcome to the Changing State of Talent 2 00:00:02,640 --> 00:00:05,679 Acquisition podcast with your host, Graham Thornton. 3 00:00:05,839 --> 00:00:08,880 Each episode brings you unfiltered conversations about 4 00:00:08,880 --> 00:00:12,160 the tools, trends, and technologies impacting the 5 00:00:12,160 --> 00:00:13,839 future of talent acquisition. 6 00:00:14,000 --> 00:00:17,679 Our guests share their stories on what's working, what's hype, 7 00:00:17,839 --> 00:00:21,199 and what's actually helping companies hire better and grow 8 00:00:21,199 --> 00:00:21,600 faster. 9 00:00:21,839 --> 00:00:23,839 Have feedback or want to join the show? 10 00:00:24,000 --> 00:00:27,039 Head on over to Tollibity.com to learn more. 11 00:00:27,199 --> 00:00:29,839 But now we're on to this week's episode. 12 00:01:29,599 --> 00:01:32,159 SPEAKER_03: And that really started as a foundation that 13 00:01:32,159 --> 00:01:35,200 shaped everything because it really taught me how deeply the 14 00:01:35,200 --> 00:01:39,040 hiring process affects both candidates and hiring teams. 15 00:01:39,280 --> 00:01:42,719 I would get letters and cards that's back before email was 16 00:01:42,719 --> 00:01:45,920 very popular from candidates about how this was affecting 17 00:01:45,920 --> 00:01:47,359 their family, not just a job. 18 00:01:47,439 --> 00:01:50,879 So I realized quickly that it wasn't really about filling a 19 00:01:50,879 --> 00:01:52,799 job or filling a role. 20 00:01:52,879 --> 00:01:55,680 It was really about how I was making people feel. 21 00:01:55,920 --> 00:01:59,519 And that really was a turning point for me because it really 22 00:01:59,519 --> 00:02:03,680 made me look at the entire process end to end and made me 23 00:02:03,680 --> 00:02:06,480 realize that there was bottlenecks in the process about 24 00:02:06,560 --> 00:02:09,280 where people, it wasn't about people working harder. 25 00:02:09,439 --> 00:02:11,840 It was really about workflows and technology. 26 00:02:12,000 --> 00:02:14,879 If we really wanted to affect change and how we were helping 27 00:02:14,879 --> 00:02:18,800 candidates, it was really going to be about what workflow made 28 00:02:18,800 --> 00:02:21,840 the most sense to reach the candidate where they are in that 29 00:02:21,840 --> 00:02:25,039 moment and what when when did that moment really matter? 30 00:02:25,199 --> 00:02:28,240 So it really led me into sourcing, uh, recruitment 31 00:02:28,319 --> 00:02:31,360 marketing, and ultimately building TA infrastructures. 32 00:02:31,520 --> 00:02:33,759 So I've done everything from standing up sourcing and 33 00:02:33,759 --> 00:02:37,439 branding teams, depleming CRMs, automation and AI. 34 00:02:37,599 --> 00:02:41,280 And that's really allowed me to blend innovation with empathy, 35 00:02:41,439 --> 00:02:43,360 like I said, really understanding the candidate, 36 00:02:43,520 --> 00:02:47,039 launching automation and AI programs that made hiring both 37 00:02:47,039 --> 00:02:48,719 faster and more human. 38 00:02:48,960 --> 00:02:52,400 And today my focus is on the intersection of AI, ethics, and 39 00:02:52,400 --> 00:02:52,879 belonging. 40 00:02:52,960 --> 00:02:55,840 So building systems that are efficient, fair, but also 41 00:02:55,840 --> 00:02:57,919 reflective of the people that they serve. 42 00:02:58,159 --> 00:03:01,840 So I'm essentially interested in how TA can evolve from that 43 00:03:01,840 --> 00:03:05,520 transactional functional that we've seen it be to a true 44 00:03:05,520 --> 00:03:09,039 intelligence engine that's predicting needs, that engages 45 00:03:09,039 --> 00:03:12,400 the passive talent, and shapes organizational readiness. 46 00:03:19,919 --> 00:03:21,919 SPEAKER_02: And I think that your you know your background 47 00:03:21,919 --> 00:03:25,840 really kind of leans into the human and uh in human resources 48 00:03:26,000 --> 00:03:26,319 too. 49 00:03:26,560 --> 00:03:29,599 You know, before we get started, you know, more deeply on the 50 00:03:30,159 --> 00:03:33,439 humanity aspect and you know connecting humanity and 51 00:03:33,439 --> 00:03:36,400 technology, you know, you mentioned in our pre-call that 52 00:03:36,479 --> 00:03:39,120 you know you've worked with recruitics for about 15 years, 53 00:03:39,280 --> 00:03:42,080 and you know, I would say from a partnership standpoint, you 54 00:03:42,080 --> 00:03:44,879 know, that's a pretty long vendor relationship in this 55 00:03:44,879 --> 00:03:45,280 industry. 56 00:03:45,439 --> 00:03:48,159 You know, many partnerships often you know kind of flame out 57 00:03:48,159 --> 00:03:51,120 after a handful of years, you know, an implementation and the 58 00:03:51,120 --> 00:03:52,240 honeymoon period ends. 59 00:03:52,400 --> 00:03:55,039 You know, I'm just curious, from a partnership lens, you know, 60 00:03:55,120 --> 00:03:58,560 what's made your partnerships with Recruitics last? 61 00:03:58,960 --> 00:03:59,520 SPEAKER_03: You're right. 62 00:03:59,680 --> 00:04:03,199 I will say, Graham, a 15-year vendor relationship is rare and 63 00:04:03,199 --> 00:04:03,680 TA. 64 00:04:04,080 --> 00:04:07,520 Um I think it works because the relationship with Recruittics 65 00:04:07,520 --> 00:04:08,639 was never transactional. 66 00:04:08,800 --> 00:04:11,039 No matter what organization I was with, because I've worked 67 00:04:11,039 --> 00:04:14,159 with Recruits in multiple organizations, it really became 68 00:04:14,159 --> 00:04:16,000 an extension of whatever team I was on. 69 00:04:16,079 --> 00:04:19,600 So we shared goals, data, challenges, and they gave us 70 00:04:19,600 --> 00:04:22,639 full transparency into their roadmap so we could co-create 71 00:04:22,639 --> 00:04:23,199 solutions. 72 00:04:23,439 --> 00:04:25,439 I think back to when I originally started working with 73 00:04:25,439 --> 00:04:28,319 them, and the focus was really about programmatic distribution 74 00:04:28,319 --> 00:04:30,000 and basic campaign tracking. 75 00:04:30,240 --> 00:04:34,319 But that partnership evolved into full funnel analytics, UTM 76 00:04:34,319 --> 00:04:36,639 and attribution modeling, competitive insights. 77 00:04:36,879 --> 00:04:40,480 They even advised on emerging tech and AI use cases, which was 78 00:04:40,480 --> 00:04:43,360 really beneficial as we started to dip our toe in that world. 79 00:04:43,600 --> 00:04:46,800 And then my work started to expand into talent intelligence, 80 00:04:47,040 --> 00:04:50,160 market disruption analysis, and of course, AI strategy. 81 00:04:50,399 --> 00:04:52,800 And what I loved about recruitics is they were willing 82 00:04:52,800 --> 00:04:54,720 to evolve right alongside that work. 83 00:04:54,959 --> 00:04:58,079 Ultimately, the longevity came from aligning on outcomes and 84 00:04:58,079 --> 00:04:59,360 not deliverables. 85 00:04:59,600 --> 00:05:02,639 And as we both know, or anybody who's in this industry knows, 86 00:05:02,800 --> 00:05:04,399 recruitment marketing isn't static. 87 00:05:04,480 --> 00:05:07,680 It shifts with the labor market, technology, of course, our 88 00:05:07,680 --> 00:05:10,879 brands, and they grow with you at every step of the way. 89 00:05:11,120 --> 00:05:15,199 Ultimately, our work was built on trust and shared learning and 90 00:05:15,199 --> 00:05:17,920 continuous innovation, and it wasn't just about the contract 91 00:05:17,920 --> 00:05:18,639 at the end of the day. 92 00:05:18,879 --> 00:05:20,079 SPEAKER_02: Yeah, no, I think that's great. 93 00:05:20,160 --> 00:05:22,639 And I think you know, the recruitment marketing and 94 00:05:22,639 --> 00:05:25,439 recruitment landscape in a gen in general continues to evolve. 95 00:05:25,519 --> 00:05:28,160 You know, we've done a call, well, probably a half dozen 96 00:05:28,160 --> 00:05:30,959 calls just this week talking about boy, like what's the 97 00:05:30,959 --> 00:05:31,920 future of SEO? 98 00:05:32,000 --> 00:05:35,199 And, you know, are we going to coin this new phrase geo, 99 00:05:35,360 --> 00:05:38,399 generative search optimization, and you know, and pushing back 100 00:05:38,480 --> 00:05:41,040 and like, hey, the reality is, you know, it's recruitment 101 00:05:41,120 --> 00:05:45,920 marketing is just evolved from newspapers to job boards to you 102 00:05:45,920 --> 00:05:49,360 know programmatic advertising and you know, social media and 103 00:05:49,439 --> 00:05:51,680 you know, Google ads, but at the end of the way, end of the day, 104 00:05:51,759 --> 00:05:53,040 it's still recruitment marketing. 105 00:05:53,120 --> 00:05:56,319 And I think you know, we're seeing a similar path with you 106 00:05:56,319 --> 00:05:57,839 know search engine optimization. 107 00:05:58,000 --> 00:06:00,480 You know, generative search is just a new search engine. 108 00:06:00,560 --> 00:06:04,480 So we're still optimizing search for you know AI search for chat 109 00:06:04,480 --> 00:06:07,519 GPT for Gemini and you know, whatever, I'll get off my 110 00:06:07,519 --> 00:06:08,079 soapbox. 111 00:06:08,160 --> 00:06:11,040 So, you know, that I think that is a pretty good segue into you 112 00:06:11,040 --> 00:06:12,399 know what I want to talk about. 113 00:06:12,560 --> 00:06:15,439 And you know, you know, let's talk a little bit more about 114 00:06:15,439 --> 00:06:17,360 healthcare, maybe more specifically. 115 00:06:17,519 --> 00:06:21,519 So, you know, you spent your entire career in health systems, 116 00:06:21,600 --> 00:06:24,639 whether it's United Health, you know, Optum, you know, Baylor, 117 00:06:24,720 --> 00:06:28,240 Scott, and white, you know, I think that it's probably easy to 118 00:06:28,240 --> 00:06:31,519 say healthcare is notoriously challenging, you know, high 119 00:06:31,519 --> 00:06:35,040 volume, tight labor markets, you know, clinical roles from some 120 00:06:35,040 --> 00:06:38,319 very, very specific credentials, you know, maybe compliance 121 00:06:38,319 --> 00:06:39,680 complexity, we can go on and on. 122 00:06:39,839 --> 00:06:42,480 You know, I'm curious, you know, from you know, from a healthcare 123 00:06:42,480 --> 00:06:45,439 lens, you know, how did some of you know maybe your healthcare 124 00:06:45,439 --> 00:06:48,959 constraints shape how you think about technology adoption? 125 00:06:49,120 --> 00:06:51,519 You know, I can imagine that, you know, you know, when you're 126 00:06:51,519 --> 00:06:54,800 in healthcare, you can't just implement any new flashy tool 127 00:06:54,800 --> 00:06:55,519 that comes your way. 128 00:06:55,600 --> 00:06:58,160 So, you know, are you seeing healthcare lag, lead when it 129 00:06:58,160 --> 00:07:00,800 comes to technology implementation, maybe AI 130 00:07:00,800 --> 00:07:01,759 adoption and recruiting? 131 00:07:02,079 --> 00:07:03,279 SPEAKER_03: You know, that's a really great question. 132 00:07:03,439 --> 00:07:06,560 And I do believe healthcare used to lag in tech adoption. 133 00:07:06,720 --> 00:07:08,480 I don't believe that's true any longer. 134 00:07:08,800 --> 00:07:12,000 I would dare to say that in the last few years, health systems 135 00:07:12,000 --> 00:07:15,199 have moved to the front of the pack, leading the industry in 136 00:07:15,199 --> 00:07:19,120 responsible, human-centered AI across town engagement, 137 00:07:19,279 --> 00:07:21,439 forecasting, and workflow automation. 138 00:07:21,680 --> 00:07:24,399 But you are absolutely also right in the fact that 139 00:07:24,399 --> 00:07:27,199 healthcare is a very unique animal. 140 00:07:27,360 --> 00:07:31,199 You've got high volume, high stakes, deeply regulated. 141 00:07:31,360 --> 00:07:34,720 So, of course, we can't chase every shiny new tool that comes 142 00:07:34,720 --> 00:07:35,439 in front of us. 143 00:07:36,079 --> 00:07:39,439 Every tech decision has to be tied back to compliance, 144 00:07:39,680 --> 00:07:42,399 scalability, and ultimately patient care. 145 00:07:43,040 --> 00:07:46,879 So when I think about that, it really forced me into a process 146 00:07:46,959 --> 00:07:48,800 first, a problem first mindset. 147 00:07:48,879 --> 00:07:52,160 And when I what I mean when I say that is I map out the 148 00:07:52,160 --> 00:07:52,639 workflow. 149 00:07:53,040 --> 00:07:57,279 I find the friction points, the gaps, um, the pain points, 150 00:07:57,439 --> 00:07:58,639 whatever you want to call it. 151 00:07:58,800 --> 00:08:02,399 And then you choose the technology that actually 152 00:08:02,399 --> 00:08:06,000 improves the experience in that space, whether it's recruiters, 153 00:08:06,240 --> 00:08:10,240 hiring managers, candidates themselves, and you really look 154 00:08:10,240 --> 00:08:14,399 for a goal that introduces AI in purposeful ways. 155 00:08:14,560 --> 00:08:17,519 So is it going to automate the screening and scheduling? 156 00:08:17,759 --> 00:08:20,639 Are you using it for predictive insights to engage passive 157 00:08:20,639 --> 00:08:21,040 talent? 158 00:08:21,199 --> 00:08:24,000 Are you freeing recruiters to do higher value work? 159 00:08:24,319 --> 00:08:26,800 You basically want to automate for efficiency, but that 160 00:08:26,800 --> 00:08:28,160 shouldn't be the only goal. 161 00:08:28,319 --> 00:08:31,439 The goal should really be about improving the candidate and the 162 00:08:31,439 --> 00:08:32,399 patient in experience. 163 00:08:32,480 --> 00:08:34,799 And I think that's what healthcare is focusing on right 164 00:08:34,799 --> 00:08:35,039 now. 165 00:08:35,279 --> 00:08:37,600 The industry as a whole is looking at that today. 166 00:08:37,840 --> 00:08:38,080 SPEAKER_02: Yeah. 167 00:08:38,240 --> 00:08:41,919 So, you know, maybe a good quite good place to start then is like 168 00:08:42,000 --> 00:08:44,879 in your world, where did you first start experimenting then 169 00:08:44,879 --> 00:08:46,000 with AI and recruiting? 170 00:08:46,159 --> 00:08:48,879 Was it, you know, was it more in the, hey, we're trying to 171 00:08:48,879 --> 00:08:51,600 automate X, Y, and Z, or was there a particular moment in 172 00:08:51,600 --> 00:08:54,240 time when you said, boy, you know, this is going to change 173 00:08:54,240 --> 00:08:57,679 how we work, you know, we need to, you know, we need to set up 174 00:08:57,679 --> 00:08:58,639 X now? 175 00:08:59,039 --> 00:09:00,559 SPEAKER_03: Yeah, that's a that's a really great question. 176 00:09:00,639 --> 00:09:03,759 And I'm thinking back to what was my real, my first real 177 00:09:03,759 --> 00:09:04,799 exposure to AI? 178 00:09:04,879 --> 00:09:08,799 And I, and if I think back, it probably was right around 2018 179 00:09:09,120 --> 00:09:12,639 when everybody started exploring conversational bots and 180 00:09:12,799 --> 00:09:15,120 automation within their CRM technology. 181 00:09:15,279 --> 00:09:18,399 And I think back then most of us saw AI as a way to speed up 182 00:09:18,399 --> 00:09:19,440 administrative work, right? 183 00:09:19,600 --> 00:09:22,320 Like scheduling and screening and follow-ups and like 184 00:09:22,320 --> 00:09:25,360 reminders on our like these automatic reminders and things 185 00:09:25,360 --> 00:09:25,759 like that. 186 00:09:26,000 --> 00:09:28,480 Nobody really saw them as game changers. 187 00:09:28,879 --> 00:09:32,639 I think the moment that changed for me was during a it was 188 00:09:32,639 --> 00:09:33,519 recent actually. 189 00:09:33,840 --> 00:09:37,600 It was during a pilot that I was leading using an AI voice agent 190 00:09:37,600 --> 00:09:40,000 to conduct the first round candidate screens. 191 00:09:40,080 --> 00:09:43,519 And it was, it was a really, it was really eye-opening because 192 00:09:43,519 --> 00:09:46,960 within a few weeks the system had processed hundreds of 193 00:09:46,960 --> 00:09:50,080 applicants, not just processed and interviewed them, but it 194 00:09:50,159 --> 00:09:51,840 assessed them and scored them. 195 00:09:52,080 --> 00:09:55,679 And one of the surprises that um I found in reviewing the data 196 00:09:55,679 --> 00:09:58,559 was the quality didn't drop, it actually improved. 197 00:09:58,799 --> 00:10:01,759 We saw that candidates felt more informed, recruiters were 198 00:10:01,759 --> 00:10:04,960 gaining hours back in their day, hiring managers were getting 199 00:10:04,960 --> 00:10:08,240 better shortlists of candidates faster, and it was making them 200 00:10:08,240 --> 00:10:08,879 more happy. 201 00:10:09,120 --> 00:10:11,759 So it was the real it was that moment that I realized this 202 00:10:11,759 --> 00:10:15,600 isn't incremental, this fundamentally changes how we 203 00:10:15,600 --> 00:10:15,840 work. 204 00:10:15,919 --> 00:10:18,960 And so what I what I realized then is that AI is not a 205 00:10:18,960 --> 00:10:19,440 plug-in. 206 00:10:19,840 --> 00:10:22,399 It has to be treated as part of the core recruiting 207 00:10:22,399 --> 00:10:25,360 infrastructure, something that we could connect the entire 208 00:10:25,360 --> 00:10:26,480 talent journey on. 209 00:10:26,559 --> 00:10:28,559 So from attraction to alumni. 210 00:10:28,639 --> 00:10:31,519 So even in the employee journey itself, when you think about the 211 00:10:31,519 --> 00:10:34,000 employee journey, it really should start from the attraction 212 00:10:34,000 --> 00:10:35,919 perspective all the way to alumni. 213 00:10:36,240 --> 00:10:41,039 And I do believe AI is going to be core in making sure that we 214 00:10:41,039 --> 00:10:42,559 can tie it all together. 215 00:10:42,960 --> 00:10:44,879 SPEAKER_02: Yeah, so Yvette, I think that's a really 216 00:10:44,879 --> 00:10:45,600 interesting piece. 217 00:10:45,759 --> 00:10:48,080 And you know, I wonder if we could unpack that a little bit 218 00:10:48,080 --> 00:10:48,320 more. 219 00:10:48,480 --> 00:10:52,000 So, you know, I think we hear a lot that, you know, for the last 220 00:10:52,000 --> 00:10:55,519 however many months and years, that you know, people are afraid 221 00:10:55,519 --> 00:10:58,320 that AI is going to get it wrong, AI is gonna take our jobs 222 00:10:58,399 --> 00:10:59,039 and and whatnot. 223 00:10:59,200 --> 00:11:01,759 But you know, I think in your example you said, you know, hey, 224 00:11:01,840 --> 00:11:05,519 like you found that you know AI running, I'll say, you know, 225 00:11:05,600 --> 00:11:08,799 almost first-round interviews or screenings with candidates did a 226 00:11:08,799 --> 00:11:12,960 on par or better job in servicing and you know, and 227 00:11:12,960 --> 00:11:15,360 screening out and identifying the right candidates. 228 00:11:15,600 --> 00:11:19,600 And you know, I think a few years ago, or you know, maybe a 229 00:11:19,600 --> 00:11:23,600 year ago, we heard you know, that hey, candidates are fine 230 00:11:23,600 --> 00:11:27,120 with AI getting them further around in the process, you know, 231 00:11:27,279 --> 00:11:30,480 as long as it's a you know a personalized experience, right? 232 00:11:30,559 --> 00:11:33,039 And they don't feel like you know, they're just being passed 233 00:11:33,039 --> 00:11:34,799 on to a you know to a bot and to an agent. 234 00:11:34,879 --> 00:11:37,840 And I would almost argue that, you know, from a consumer lens, 235 00:11:37,919 --> 00:11:40,639 it's no different than you know, people used to hate when you 236 00:11:40,639 --> 00:11:42,399 know an AI chatbot used to pop up. 237 00:11:42,480 --> 00:11:45,519 But if it can get me my answer to my question faster, I'm okay 238 00:11:45,519 --> 00:11:45,840 with that. 239 00:11:46,000 --> 00:11:48,879 You know, are you kind of seeing a similar balance play out with 240 00:11:48,879 --> 00:11:51,279 our you know AI sort of screening and interviewing 241 00:11:51,279 --> 00:11:51,600 tools? 242 00:11:51,759 --> 00:11:55,039 You know, given maybe it's a hey, a high volume of candidates 243 00:11:55,039 --> 00:11:55,759 are coming through. 244 00:11:55,919 --> 00:11:59,279 Hey, if I'm you know a qualified candidate, you know, I'm more 245 00:11:59,279 --> 00:12:03,759 than happy to engage with an AI generated interview if it's 246 00:12:03,759 --> 00:12:06,159 going to help me advance through the process faster. 247 00:12:06,320 --> 00:12:09,360 Is that kind of what you're um seeing from a balance, or am I 248 00:12:09,440 --> 00:12:10,799 you know making a bit of a leap? 249 00:12:11,120 --> 00:12:12,159 SPEAKER_03: Oh no, no, no, Graham. 250 00:12:12,240 --> 00:12:13,519 That's exactly what we're seeing. 251 00:12:13,679 --> 00:12:17,200 I I think today I look at AI as that bridge between efficiency 252 00:12:17,200 --> 00:12:17,840 and empathy. 253 00:12:17,919 --> 00:12:21,120 It it frees up the ability to focus on the human moments that 254 00:12:21,120 --> 00:12:23,120 really matter and think about what a human moment that really 255 00:12:23,120 --> 00:12:23,519 matters is. 256 00:12:23,679 --> 00:12:27,519 When a candidate applies for a job, and if there if it's a high 257 00:12:27,600 --> 00:12:30,639 volume role where you're getting, let's say, a hundred 258 00:12:30,799 --> 00:12:36,080 candidates a day, maybe, maybe more even, um, a recruiter does 259 00:12:36,080 --> 00:12:38,240 not have the time to look through that many applicants. 260 00:12:38,399 --> 00:12:41,039 So historically, the recruiter will go through the most 261 00:12:41,039 --> 00:12:44,639 current, the applicants that appear to be the best fit, who 262 00:12:44,639 --> 00:12:47,279 applied the soonest, or maybe the first ones who applied, but 263 00:12:47,279 --> 00:12:48,399 they don't get them all. 264 00:12:48,639 --> 00:12:52,480 Now, an agent can come in and screen every single applicant. 265 00:12:52,559 --> 00:12:53,919 So, what does that do for the recruiter? 266 00:12:54,000 --> 00:12:56,799 It obviously gives them, serves them up the best of all the 267 00:12:56,799 --> 00:12:59,759 applicants who applied, not just the ones they were able to get 268 00:12:59,759 --> 00:13:02,240 connected with within the timeframe that they had. 269 00:13:02,399 --> 00:13:04,320 And what does that do for the candidate? 270 00:13:04,480 --> 00:13:06,240 But it takes away that black hole. 271 00:13:06,320 --> 00:13:08,799 Because how many times have you heard, and you've seen this on 272 00:13:08,799 --> 00:13:11,919 Glassdoor, you've seen it on Comparably, and all these other 273 00:13:11,919 --> 00:13:14,960 places where candidates can leave reviews, is that they feel 274 00:13:14,960 --> 00:13:16,320 like they're not important. 275 00:13:16,559 --> 00:13:19,840 There's a black hole, they apply and never hear anything. 276 00:13:19,919 --> 00:13:21,919 So now you're getting rid of that feedback. 277 00:13:22,080 --> 00:13:24,559 You're saying, we're gonna take that away because now we've 278 00:13:24,559 --> 00:13:27,279 given you an opportunity to actually be screened by somebody 279 00:13:27,279 --> 00:13:28,320 and get assessed. 280 00:13:28,480 --> 00:13:30,960 And I think the technology is going to advance and give 281 00:13:30,960 --> 00:13:34,720 candidates an opportunity to even maybe forego recruit 282 00:13:34,960 --> 00:13:38,720 resumes, and maybe we can start um giving agents an opportunity 283 00:13:38,720 --> 00:13:39,919 to give feedback, right? 284 00:13:40,080 --> 00:13:43,120 So like they can say, I can apply for a job, or I go to 285 00:13:43,120 --> 00:13:45,440 apply for a job, and this is somebody, this isn't my idea. 286 00:13:45,600 --> 00:13:47,600 Somebody told me this, that this is their idea. 287 00:13:48,000 --> 00:13:51,440 They want to be able to apply for a job and instead of a 288 00:13:51,440 --> 00:13:55,519 resume, talk to an agent and say, and the agent asks dynamic 289 00:13:55,519 --> 00:13:56,159 questions, right? 290 00:13:56,240 --> 00:13:59,200 And then I can ask the agent questions, and at the end of my 291 00:13:59,200 --> 00:14:02,960 conversation, the agent can honestly tell me, hey, that you 292 00:14:02,960 --> 00:14:06,320 applied for this job, and based on what you've shared today, 293 00:14:06,399 --> 00:14:08,399 you're about a 75% fit. 294 00:14:08,559 --> 00:14:11,919 We have 30 other candidates who are a hundred percent fit. 295 00:14:12,159 --> 00:14:15,120 We don't think this job is right for you, but why don't you keep 296 00:14:15,120 --> 00:14:17,360 looking and we'll serve you up other jobs that might be a 297 00:14:17,360 --> 00:14:19,440 better fit for you based on what you shared today? 298 00:14:19,600 --> 00:14:22,080 Like I think that's where their technology is going, and I think 299 00:14:22,080 --> 00:14:24,559 candidates are going to be more and more appreciative that we're 300 00:14:24,559 --> 00:14:27,039 giving them an opportunity to not just share about their 301 00:14:27,039 --> 00:14:31,039 experience, but get feedback on why they are fit for this role 302 00:14:31,120 --> 00:14:33,360 or why they may not be the best fit for this role. 303 00:14:33,759 --> 00:14:36,080 SPEAKER_02: Yeah, well, you know, I would say I think that's 304 00:14:36,080 --> 00:14:39,120 a great parallel to you know what we're seeing in the 305 00:14:39,120 --> 00:14:41,200 evolution of you know SEO. 306 00:14:41,360 --> 00:14:44,240 And so, you know, the way I've been explaining it lately is you 307 00:14:44,240 --> 00:14:47,200 know, you think about you know how people use Google, it's you 308 00:14:47,200 --> 00:14:49,200 know you're essentially yelling into a search engine. 309 00:14:49,279 --> 00:14:52,480 It's you know, jobs near me, it's pizza restaurants. 310 00:14:52,639 --> 00:14:56,080 And you know, great, that's you know, and and websites have been 311 00:14:56,080 --> 00:14:59,360 built to optimize for short keywords that they want to 312 00:14:59,360 --> 00:14:59,919 capture. 313 00:15:00,159 --> 00:15:03,360 And you know, because of that, you have all these content farms 314 00:15:03,360 --> 00:15:06,799 where you know everyone's writing you know, 500 blog posts 315 00:15:06,799 --> 00:15:09,039 about pizza restaurants or jobs. 316 00:15:09,200 --> 00:15:12,639 And you know, the whole goal is we want to make sure that we're 317 00:15:12,639 --> 00:15:15,279 showing up higher on Google and you know getting on the first 318 00:15:15,279 --> 00:15:16,799 page or second page with links. 319 00:15:16,960 --> 00:15:21,039 And I think you know, what you know AI is kind of injecting in 320 00:15:21,039 --> 00:15:23,679 here, you know, with generative search becoming more important, 321 00:15:23,919 --> 00:15:27,919 people you know, using Chat GPT and Gemini, you know, is you 322 00:15:27,919 --> 00:15:30,720 know, you're having conversations with a chat, you 323 00:15:30,720 --> 00:15:34,240 know, with a uh generative search agent, an LLM, and it is 324 00:15:34,240 --> 00:15:36,879 much more like the scenario that you just described, Yvette. 325 00:15:36,960 --> 00:15:41,279 And it's you know, hey, I, you know, I'm looking for, I'm a you 326 00:15:41,279 --> 00:15:43,279 know, I'm a nurse with five years of experience. 327 00:15:43,440 --> 00:15:45,600 I move into the Dallas Fort Worth area. 328 00:15:45,759 --> 00:15:47,039 Here's where my credentials are. 329 00:15:47,200 --> 00:15:50,399 I'm looking for a company that has, you know, has leadership 330 00:15:50,399 --> 00:15:54,080 opportunities, you know, and or continuing education benefits 331 00:15:54,159 --> 00:15:56,879 and you know, great work-life balance where I won't have to 332 00:15:56,879 --> 00:15:57,679 work weekends. 333 00:15:57,840 --> 00:16:01,120 And like people can have a literal conversation like that 334 00:16:01,120 --> 00:16:05,200 with ChatGPT, with Gemini, and it will pop out, you know, 335 00:16:05,360 --> 00:16:08,480 employers that you know fit that match are looking for those 336 00:16:08,480 --> 00:16:11,120 types of candidates or provide those types of you know 337 00:16:11,200 --> 00:16:11,759 benefits. 338 00:16:11,919 --> 00:16:16,559 And I think the challenge is you know, companies are having to 339 00:16:16,559 --> 00:16:19,600 evolve their search strategy to make sure that they have the 340 00:16:19,600 --> 00:16:22,960 content or the context that you know match those deep 341 00:16:22,960 --> 00:16:25,440 conversations that you know candidates want to have. 342 00:16:25,600 --> 00:16:28,240 And so I think the scenario that you just described is you know 343 00:16:28,240 --> 00:16:32,320 what we're kind of seeing play out in real time in generative 344 00:16:32,320 --> 00:16:32,720 search. 345 00:16:32,879 --> 00:16:36,000 And now instead of racing for you know keywords in the first 346 00:16:36,000 --> 00:16:39,120 page on Google, you know, we have companies that are racing 347 00:16:39,120 --> 00:16:43,440 to make sure that all the good things that they are known for, 348 00:16:43,600 --> 00:16:46,159 or all the good reasons why people should go work for an 349 00:16:46,159 --> 00:16:49,200 organization, you know, we have to go fight for real estate in 350 00:16:49,200 --> 00:16:51,840 LLMs and generative search models, right? 351 00:16:52,080 --> 00:16:56,240 And so I think we're not far off, uh maybe not far off as a 352 00:16:56,240 --> 00:16:59,120 stretch, but I think we're I think we're progressing towards 353 00:16:59,200 --> 00:17:01,759 you know the state that you kind of described, Yvette. 354 00:17:01,840 --> 00:17:03,519 And like I hope we get there. 355 00:17:03,759 --> 00:17:07,119 Because again, like I think you know it's it's a similar 356 00:17:07,119 --> 00:17:10,160 challenge where you know Google search has gotten a bit gummed 357 00:17:10,160 --> 00:17:13,519 up with, you know, it's too many people trying to fight for links 358 00:17:13,519 --> 00:17:14,160 on page one. 359 00:17:14,240 --> 00:17:17,200 And I think it's probably a similar standpoint when it looks 360 00:17:17,200 --> 00:17:20,720 at you know how easy it's gotten to apply to jobs and you know, 361 00:17:20,880 --> 00:17:24,799 integrate applies everywhere, and I can open up a requisition 362 00:17:24,799 --> 00:17:28,720 and I get a hundred applications in a day, sure, but how many of 363 00:17:28,720 --> 00:17:29,680 them are the right people? 364 00:17:29,839 --> 00:17:33,200 So I, you know, I can see the pendulum swinging back towards 365 00:17:33,680 --> 00:17:36,880 the candidate, you know, in a few different ways with the you 366 00:17:36,880 --> 00:17:40,240 know, call it a the assist of um of AI. 367 00:17:40,559 --> 00:17:41,759 SPEAKER_03: I completely agree with you. 368 00:17:41,839 --> 00:17:43,920 And I and I think we are headed in that direction, Graham. 369 00:17:44,000 --> 00:17:46,400 And I would agree with you that it is in the best interest of 370 00:17:46,400 --> 00:17:47,119 the candidate. 371 00:17:47,279 --> 00:17:49,519 And I think that's why recruitment marketing is so 372 00:17:49,519 --> 00:17:49,680 important. 373 00:17:49,839 --> 00:17:53,359 I think that making sure that employers are marketing why, 374 00:17:53,519 --> 00:17:55,279 what's that employee value proposition? 375 00:17:55,359 --> 00:17:58,160 What are you promising to your potential employers and making 376 00:17:58,160 --> 00:17:59,759 it authentic and genuine? 377 00:17:59,920 --> 00:18:02,559 And because that's ultimately what candidates are doing, 378 00:18:02,640 --> 00:18:05,200 especially today in the during the era of the great stay, 379 00:18:05,279 --> 00:18:05,519 right? 380 00:18:05,599 --> 00:18:08,160 Like they're not gonna make a move unless they really feel 381 00:18:08,160 --> 00:18:10,640 like you're gonna give them what they have, what they're looking 382 00:18:10,640 --> 00:18:10,880 for. 383 00:18:11,119 --> 00:18:11,680 SPEAKER_02: Yeah, yeah. 384 00:18:11,759 --> 00:18:12,720 No, I completely agree. 385 00:18:12,880 --> 00:18:14,720 Well, I want to talk a little bit more about you know the 386 00:18:14,720 --> 00:18:16,480 realities of AI implementations. 387 00:18:16,559 --> 00:18:17,920 You know, I think it's a great segue. 388 00:18:18,079 --> 00:18:20,640 So, you know, I think you recently presented, uh, it might 389 00:18:20,640 --> 00:18:23,680 have been two, three weeks ago at this point at LinkedIn Talent 390 00:18:23,680 --> 00:18:24,000 Connect. 391 00:18:24,079 --> 00:18:26,799 I think you're presenting with David Barr about you know using 392 00:18:26,799 --> 00:18:28,640 AI to personalize talent engagement. 393 00:18:28,720 --> 00:18:30,960 And I know that's kind of an area that's near and dear to 394 00:18:30,960 --> 00:18:31,440 your heart. 395 00:18:31,599 --> 00:18:34,559 You know, I'm curious, you know, let's talk about what's actually 396 00:18:34,559 --> 00:18:36,559 working from a talent engagement standpoint. 397 00:18:36,720 --> 00:18:40,880 Where is where do you see kind of AI delivering value in your 398 00:18:40,880 --> 00:18:41,759 recruitment process? 399 00:18:41,920 --> 00:18:44,480 Not just, you know, where vendors promise it you know is 400 00:18:44,559 --> 00:18:47,359 gonna work, but where where are you personally seeing measurable 401 00:18:47,359 --> 00:18:49,119 improvement with you know with AI? 402 00:18:49,440 --> 00:18:52,480 SPEAKER_03: Yeah, I I think AI has been most valuable in 403 00:18:52,480 --> 00:18:55,359 specific repeatable parts of recruiting. 404 00:18:55,519 --> 00:18:59,359 Um the biggest wins I've seen are in the areas of things like 405 00:18:59,359 --> 00:19:00,400 personalized engagement. 406 00:19:00,559 --> 00:19:05,039 So AI allows us to nurture passive talent at scale with 407 00:19:05,039 --> 00:19:09,039 textual messaging, often doubling engagement versus that 408 00:19:09,039 --> 00:19:10,160 generic outreach. 409 00:19:10,480 --> 00:19:13,519 Screening and scheduling, also another area where we've seen 410 00:19:13,519 --> 00:19:13,920 AI. 411 00:19:14,000 --> 00:19:16,880 I know talked about voice agents and chatbots, but that 412 00:19:16,880 --> 00:19:19,039 dramatically reduces admin work. 413 00:19:19,359 --> 00:19:23,599 I mean, one team can cut time to screen by over 60% by 414 00:19:23,599 --> 00:19:26,000 implementing a voice agent or a chat bot. 415 00:19:26,240 --> 00:19:29,759 And then the other area where I've seen some big wins is in 416 00:19:29,759 --> 00:19:31,279 the predictive insights side. 417 00:19:31,359 --> 00:19:35,119 Uh, talent insights helps forecast hiring needs as well as 418 00:19:35,119 --> 00:19:36,720 spot the market disruptions. 419 00:19:36,960 --> 00:19:41,440 So teams can source proactively versus reactively, which is what 420 00:19:41,440 --> 00:19:42,640 you want your teams to do. 421 00:19:42,799 --> 00:19:45,839 I mean, that's what we're going towards that model of is being 422 00:19:45,839 --> 00:19:49,119 more proactive, reaching the paths of talent, but we have to 423 00:19:49,119 --> 00:19:51,519 give them some triggers, like where should we go first? 424 00:19:51,680 --> 00:19:54,079 Like, um kind of like a bullseye approach. 425 00:19:54,160 --> 00:19:56,400 Let's start here and then fan ourselves out. 426 00:19:56,640 --> 00:19:59,680 And then I do think that there are some areas where there's 427 00:19:59,680 --> 00:20:01,599 still opportunity for AI. 428 00:20:01,839 --> 00:20:04,319 I think that there's been some disappointment around the 429 00:20:04,319 --> 00:20:04,960 integration. 430 00:20:05,119 --> 00:20:08,160 I think it's still a major challenge because even great 431 00:20:08,160 --> 00:20:11,279 tools lose value when they don't play well with legacy systems or 432 00:20:11,279 --> 00:20:13,119 they disrupt the recruiter workflow. 433 00:20:13,279 --> 00:20:15,200 That's why I think it's so important to do the front-end 434 00:20:15,359 --> 00:20:18,559 work, which is that recruiter workflow analysis, and then 435 00:20:18,559 --> 00:20:22,000 identify what tool what tool makes the most sense before you 436 00:20:22,000 --> 00:20:24,079 just go buy the tool and try to implement it. 437 00:20:24,400 --> 00:20:26,319 SPEAKER_02: Yeah, well, I I've always said, you know, 438 00:20:26,559 --> 00:20:30,000 integration is the most poorly used word in in HR tech. 439 00:20:30,240 --> 00:20:32,160 And you know, I stand by that today. 440 00:20:32,400 --> 00:20:35,519 I do think that I think it's gotten better, it's gotten 441 00:20:35,519 --> 00:20:38,880 easier, and you know, integration doesn't uh scare as 442 00:20:38,880 --> 00:20:41,519 many people, you know, but you know, integration doesn't mean 443 00:20:41,599 --> 00:20:44,319 you know, provides a link to a job posting. 444 00:20:44,400 --> 00:20:46,640 That's you know, it's a very different integration, I think, 445 00:20:46,799 --> 00:20:47,759 what people would truly mean. 446 00:20:48,000 --> 00:20:51,359 So I I guess I'd say a harder question than, you know, where 447 00:20:51,359 --> 00:20:54,400 would you say AI has kind of disappointed you the most? 448 00:20:54,640 --> 00:20:56,480 Is it in that integration area? 449 00:20:56,880 --> 00:20:57,839 SPEAKER_03: Yeah, I think so. 450 00:20:58,000 --> 00:21:00,400 In the integration, that and I think the other area would 451 00:21:00,559 --> 00:21:03,359 probably be um the overselling from vendors. 452 00:21:03,680 --> 00:21:06,640 You know, it's it's comical to think about it, but like when 453 00:21:06,640 --> 00:21:09,680 you do a vendor demo, they show you every bell and whistle. 454 00:21:09,759 --> 00:21:13,200 And I think, Graham, one of the things that I have noticed is 455 00:21:13,200 --> 00:21:15,839 that integration, it's it's more used today. 456 00:21:15,920 --> 00:21:18,240 You're right, it was an underused word, but it's more 457 00:21:18,240 --> 00:21:18,640 used today. 458 00:21:18,799 --> 00:21:21,119 But I think vendors are so quick to say, yeah, we can integrate, 459 00:21:21,200 --> 00:21:21,519 no problem. 460 00:21:21,759 --> 00:21:23,200 Open API, no problem. 461 00:21:23,359 --> 00:21:26,720 And then when the rubber hits the road, it's like, oh no, not 462 00:21:26,720 --> 00:21:30,079 so much, not so not as seamless as we thought it was going to 463 00:21:30,079 --> 00:21:30,319 be. 464 00:21:30,559 --> 00:21:33,680 So I think that that's where I there's still some challenges. 465 00:21:34,000 --> 00:21:36,079 SPEAKER_02: Yeah, well, I I think the bigger challenge, and 466 00:21:36,079 --> 00:21:38,880 we see this just in the news everywhere, is like everyone is 467 00:21:38,880 --> 00:21:42,319 being tasked to, you know, use the AI somehow. 468 00:21:42,559 --> 00:21:45,200 And I think that there are a lot of vendors that are taken 469 00:21:45,200 --> 00:21:46,720 advantage of that fact, right? 470 00:21:46,880 --> 00:21:49,599 And you know, when we go through our practices, it's you know, 471 00:21:49,680 --> 00:21:52,480 sure, like you can use AI, and like, you know, everyone can go 472 00:21:52,480 --> 00:21:55,920 by a Gartner report and you know figure out that, yep, they 473 00:21:55,920 --> 00:21:59,440 aren't using AI enough, or they should use it in employer brand 474 00:21:59,519 --> 00:22:00,319 or in their process. 475 00:22:00,400 --> 00:22:03,440 But you know, the bigger problem is doing the work to map out you 476 00:22:03,440 --> 00:22:06,319 know where and why, and you know, more importantly, probably 477 00:22:06,319 --> 00:22:08,559 what problems you're gonna solve, you know, how much time 478 00:22:08,559 --> 00:22:10,400 it's taking to do X, Y, and Z. 479 00:22:10,480 --> 00:22:14,160 And like if we're gonna prioritize AI to you know 480 00:22:14,319 --> 00:22:16,640 something as simple as automate scheduling, right? 481 00:22:16,799 --> 00:22:19,680 Or you know, screen out candidates that you know simply 482 00:22:19,680 --> 00:22:20,880 don't live in the US. 483 00:22:20,960 --> 00:22:24,160 You know, I think that there are a lot of you know low-hanging 484 00:22:24,160 --> 00:22:27,680 fruit areas, and and I think way too often you know, companies 485 00:22:27,680 --> 00:22:31,119 jump to the you know, the holy grail, we're gonna buy acts 486 00:22:31,200 --> 00:22:34,559 system if it's going to find candidates and deliver the top 487 00:22:34,559 --> 00:22:37,279 three that are already pre-screened and and ready to 488 00:22:37,279 --> 00:22:37,839 start tomorrow. 489 00:22:37,920 --> 00:22:40,319 And I think the reality is you know somewhere in between, 490 00:22:40,400 --> 00:22:40,640 right? 491 00:22:40,720 --> 00:22:44,079 And I think we need to sometimes maybe admit that there's some 492 00:22:44,079 --> 00:22:47,119 limitations to where we wanna um where we want to start. 493 00:22:47,279 --> 00:22:48,720 But hey, we're not a vendor anymore. 494 00:22:48,799 --> 00:22:52,400 SPEAKER_03: So this is a great and sometimes admit this isn't 495 00:22:52,559 --> 00:22:55,200 this product doesn't do everything you need it to do, 496 00:22:55,359 --> 00:22:55,680 right? 497 00:22:55,759 --> 00:22:59,680 Like it does 80% of what you want it to do, and we can work 498 00:22:59,680 --> 00:23:02,000 on that last 20% if you help us. 499 00:23:02,079 --> 00:23:03,279 Like, let's be a partner in this. 500 00:23:03,440 --> 00:23:06,079 I think vendors shouldn't be afraid to say that, but they are 501 00:23:06,079 --> 00:23:08,079 so afraid to say that because they're afraid they're gonna 502 00:23:08,079 --> 00:23:08,799 lose the deal. 503 00:23:09,039 --> 00:23:12,000 But ultimately, if you end up with a product that doesn't get 504 00:23:12,000 --> 00:23:14,640 adopted because it doesn't do everything we thought it was 505 00:23:14,640 --> 00:23:16,559 going to do, then everybody loses. 506 00:23:16,720 --> 00:23:19,680 So I think that's one of the areas a vendor should probably 507 00:23:19,680 --> 00:23:21,359 be a little bit more open to. 508 00:23:21,680 --> 00:23:24,720 SPEAKER_02: Well, I'm I'm reminded of uh an old boss of 509 00:23:24,720 --> 00:23:27,440 mine who said, you know, he was sitting in vendor demos and you 510 00:23:27,440 --> 00:23:28,720 know it was who knows? 511 00:23:28,799 --> 00:23:31,440 We'll say it was with bullhorn, you know, and and then bullhorn 512 00:23:31,599 --> 00:23:34,480 sales rep was promising them could do X, it could do Y, it 513 00:23:34,480 --> 00:23:37,279 could do Z, you know, and and then one guy, you know, at 514 00:23:37,279 --> 00:23:39,359 Bullhorn said, Well, no, no, no, no. 515 00:23:39,440 --> 00:23:40,799 It actually it can't do Z. 516 00:23:40,880 --> 00:23:43,440 And you know, sales rep kind of cut him off, said, No, it could 517 00:23:43,440 --> 00:23:43,599 do it. 518 00:23:43,680 --> 00:23:46,160 And you know, remember our old boss said, No, that's the guy I 519 00:23:46,160 --> 00:23:47,440 want in the room every time. 520 00:23:47,599 --> 00:23:49,680 The guy that tells me what it can't do. 521 00:23:50,000 --> 00:23:54,079 And we can, you know, we can do, you know, if we could do seven 522 00:23:54,079 --> 00:23:56,799 out of ten things, that's still better than you know, than than 523 00:23:56,799 --> 00:23:59,920 where we're at today, you know, but we'd rather do seven things 524 00:23:59,920 --> 00:24:03,119 well, you know, than than overpromise at uh at this point. 525 00:24:03,279 --> 00:24:07,200 And so I think there's a lot of value in boy, transparency and a 526 00:24:07,200 --> 00:24:10,480 vendor agnostic sort of lens to, you know, hey, if it doesn't do 527 00:24:10,480 --> 00:24:11,599 everything, that's okay. 528 00:24:11,759 --> 00:24:13,680 Let's just make sure they can do all the things that we're 529 00:24:13,680 --> 00:24:13,920 seeing. 530 00:24:14,160 --> 00:24:14,640 SPEAKER_03: Absolutely. 531 00:24:14,880 --> 00:24:16,640 SPEAKER_02: Well, one thing you shared on LinkedIn, and I'm 532 00:24:16,640 --> 00:24:20,240 gonna paraphrase it and get it close to right, is you know, in 533 00:24:20,240 --> 00:24:23,519 your world, you think AI can enhance creativity and not, you 534 00:24:23,519 --> 00:24:24,640 know, not replace it. 535 00:24:24,880 --> 00:24:28,000 And you know, I think that you know, your point was it's uh 536 00:24:28,079 --> 00:24:30,720 it's a reminder that technology, if if it's used kind of 537 00:24:30,720 --> 00:24:33,759 thoughtfully, can amplify our humanity rather than diminish 538 00:24:33,759 --> 00:24:34,240 it, right? 539 00:24:34,400 --> 00:24:37,039 And and I think that you know that's probably a different 540 00:24:37,039 --> 00:24:40,640 framing than you know most of us are seeing and hearing at 541 00:24:40,640 --> 00:24:41,359 conferences. 542 00:24:41,519 --> 00:24:44,000 You know, many vendors are selling efficiency and 543 00:24:44,000 --> 00:24:47,759 automation, but you are kind of talking about you know humanity 544 00:24:47,759 --> 00:24:48,559 and belonging. 545 00:24:48,640 --> 00:24:50,880 And you know, I know it's literally in many of your 546 00:24:50,880 --> 00:24:51,599 titles, right? 547 00:24:51,759 --> 00:24:56,160 And so maybe walk me through how that philosophy you know shows 548 00:24:56,160 --> 00:24:58,240 up in your shows up in your work. 549 00:24:58,640 --> 00:25:01,359 SPEAKER_03: Yeah, I think um I've always believed that 550 00:25:01,359 --> 00:25:04,400 technology should expand our capacity for connection, not 551 00:25:04,400 --> 00:25:04,960 replace it. 552 00:25:05,039 --> 00:25:09,200 So AI is most powerful when we can remove friction, not 553 00:25:09,200 --> 00:25:12,960 feeling, and create a space for the work only humans can do. 554 00:25:13,039 --> 00:25:16,720 And that is practice empathy, tell our story and our brand, 555 00:25:16,880 --> 00:25:18,400 and express belonging. 556 00:25:18,559 --> 00:25:20,160 So I think that that's really important. 557 00:25:20,400 --> 00:25:24,799 The philosophy can guide you through implementation with AI 558 00:25:25,039 --> 00:25:27,039 is looking at the design of everything. 559 00:25:27,200 --> 00:25:29,680 So start starting with the moments that matter, like 560 00:25:29,680 --> 00:25:32,559 improving candidate feedback, looking at the recruiter 561 00:25:32,640 --> 00:25:35,839 workload, or even a new hire's first day, and then making sure 562 00:25:35,839 --> 00:25:40,000 that you have open communication with your team, framing AI as 563 00:25:40,000 --> 00:25:43,119 giving recruiters time back for real conversations, maybe 564 00:25:43,119 --> 00:25:46,319 elevating their role to a talent advisor, or there's a new term, 565 00:25:46,480 --> 00:25:49,920 talent agent, or talent business partner, whatever term you want 566 00:25:49,920 --> 00:25:50,319 to use. 567 00:25:50,480 --> 00:25:53,119 But it's not really to replace them, it's really to elevate 568 00:25:53,119 --> 00:25:53,920 their role. 569 00:25:54,160 --> 00:25:57,039 And then, of course, culture, because I think about AI 570 00:25:57,039 --> 00:25:59,839 technology and I think about the prompts that we're using. 571 00:25:59,920 --> 00:26:03,440 So prompts and chat flows should still really reflect empathy and 572 00:26:03,440 --> 00:26:06,880 inclusion because those small details scale culture. 573 00:26:07,039 --> 00:26:10,400 So when I think about that, it's like we have to really think 574 00:26:10,400 --> 00:26:14,240 about how it's making the experience more human at scale. 575 00:26:14,480 --> 00:26:19,519 And AI should amplify our culture and not replace it, and 576 00:26:19,519 --> 00:26:23,599 it shouldn't just be about the speed, if that makes sense. 577 00:26:24,000 --> 00:26:24,799 SPEAKER_02: Yeah, yeah. 578 00:26:24,960 --> 00:26:26,160 No, I think it totally does. 579 00:26:26,240 --> 00:26:29,359 And I think like, you know, even some of the examples of you 580 00:26:29,359 --> 00:26:31,920 know, where we're going with generative search, I think, you 581 00:26:31,920 --> 00:26:33,680 know, for the right organizations that you know 582 00:26:33,839 --> 00:26:38,079 implemented or action correctly, like, you know, AI and and LLM 583 00:26:38,079 --> 00:26:41,200 and generative search is going to give us a chance to share our 584 00:26:41,200 --> 00:26:43,839 stories and share our culture a lot more broadly and a lot more 585 00:26:43,839 --> 00:26:46,960 deeply than you know, you typically would get in, you 586 00:26:46,960 --> 00:26:50,000 know, Arg at least, you know, SEO that would you know maybe 587 00:26:50,000 --> 00:26:53,519 penalize or reward the wrong players in that space too. 588 00:26:53,599 --> 00:26:57,680 So I think I'm I think we're in a in a very interesting spot in 589 00:26:57,680 --> 00:27:00,799 kind of bridging that gap between you know humanity and 590 00:27:00,799 --> 00:27:03,680 and technology and you know, and using that to really shine the 591 00:27:03,680 --> 00:27:06,799 light on you know more deeper stories within organizations and 592 00:27:06,799 --> 00:27:07,680 cultures as a whole. 593 00:27:08,160 --> 00:27:11,599 Well, talk to me about you know a TA leader, you know, sitting 594 00:27:11,599 --> 00:27:13,279 in their office then right now, Yvette. 595 00:27:13,359 --> 00:27:14,720 We've talked a lot about AI. 596 00:27:14,880 --> 00:27:17,359 I think a lot of executives are getting pressure from the 597 00:27:17,359 --> 00:27:20,559 C-suite to do something with AI, you know, the drowning vendor 598 00:27:20,559 --> 00:27:23,359 pitches, as we've kind of said, you know, most vendor pitches 599 00:27:23,359 --> 00:27:26,079 end with we can do everything, you know, and so I think there's 600 00:27:26,079 --> 00:27:29,200 oftentimes a lot of you know paralysis around not knowing 601 00:27:29,200 --> 00:27:29,759 where to start. 602 00:27:29,920 --> 00:27:32,880 And so, you know, if you had some advice for you know the 603 00:27:32,880 --> 00:27:35,680 overwhelmed TA leader, you know, that's sitting there getting 604 00:27:35,680 --> 00:27:38,640 pressure from the C-suite to do something with AI, you know, 605 00:27:38,720 --> 00:27:41,440 what's what's one piece of advice you'd give to you know a 606 00:27:41,519 --> 00:27:42,880 town acquisition leader today? 607 00:27:42,960 --> 00:27:43,680 What would that be? 608 00:27:43,920 --> 00:27:47,599 SPEAKER_03: Yeah, my one piece of advice would be to start 609 00:27:47,599 --> 00:27:52,400 small, measure fast, and design for adoption, not perfection. 610 00:27:52,559 --> 00:27:55,599 So don't go in trying to overhaul your whole tech stack 611 00:27:55,599 --> 00:27:56,160 at once. 612 00:27:56,400 --> 00:28:00,400 Pick one pain point that's measurable, like screening or 613 00:28:00,480 --> 00:28:01,680 candidate engagement. 614 00:28:01,920 --> 00:28:03,839 And prove the value there first. 615 00:28:04,000 --> 00:28:07,839 Build trust with your recruiters early, because that's key to 616 00:28:07,839 --> 00:28:11,920 adoption, by being transparent about what the tool does and 617 00:28:11,920 --> 00:28:13,759 doesn't do to our point earlier. 618 00:28:14,000 --> 00:28:15,759 Make adoption a KPI. 619 00:28:16,000 --> 00:28:19,359 Because at the end of the day, you can buy the best AI on the 620 00:28:19,359 --> 00:28:19,680 market. 621 00:28:19,759 --> 00:28:22,480 But if your team doesn't trust it or it doesn't fit the 622 00:28:22,480 --> 00:28:24,480 workflow, you'll never see the ROI. 623 00:28:24,640 --> 00:28:28,480 So the most successful pilots I've led, I didn't consider tech 624 00:28:28,480 --> 00:28:28,960 projects. 625 00:28:29,119 --> 00:28:31,680 I considered them change management initiatives that were 626 00:28:31,680 --> 00:28:35,359 focused on helping people that work smarter, not differently. 627 00:28:35,599 --> 00:28:36,720 SPEAKER_02: Yeah, I think that's great. 628 00:28:36,960 --> 00:28:38,960 Well, I think that's a good place for us to close. 629 00:28:39,039 --> 00:28:41,279 I got a couple quick hit, quick hits for you, If that. 630 00:28:41,440 --> 00:28:43,839 So, you know, first one, it's contrarian take time. 631 00:28:44,000 --> 00:28:46,960 So, you know, what's your most contrarian prediction about 632 00:28:46,960 --> 00:28:48,559 talent acquisition technology? 633 00:28:48,640 --> 00:28:50,880 You know, what's what's something that ever thinks is 634 00:28:50,880 --> 00:28:52,480 gonna happen that you might disagree with? 635 00:28:52,799 --> 00:28:55,519 SPEAKER_03: I think that the future of TA isn't about more 636 00:28:55,519 --> 00:28:56,000 automation. 637 00:28:56,079 --> 00:28:58,559 It's gonna be about more curation and connection. 638 00:28:58,720 --> 00:29:02,079 I think everyone assumes AI is gonna replace recruiters, but I 639 00:29:02,079 --> 00:29:04,559 think the real advantage is gonna come from teams who use it 640 00:29:04,559 --> 00:29:06,240 to deepen human connection. 641 00:29:06,480 --> 00:29:10,640 I think automation is at this day and age, it's table stakes. 642 00:29:10,799 --> 00:29:13,440 Trust and personalization will be the true different 643 00:29:13,440 --> 00:29:14,400 differentiators. 644 00:29:14,559 --> 00:29:17,920 I think the next phase won't be about who has the most tools. 645 00:29:18,000 --> 00:29:21,279 It's gonna be about who uses them most intentionally to make 646 00:29:21,279 --> 00:29:24,880 the experience feel more human, transparent, and authentic. 647 00:29:25,119 --> 00:29:26,000 SPEAKER_02: All right, I like that. 648 00:29:26,160 --> 00:29:28,960 Okay, well, the last question that I ask everyone is so what 649 00:29:28,960 --> 00:29:31,519 are you reading or listening to do these days? 650 00:29:31,599 --> 00:29:33,680 And you know, how are you learning and staying ahead of 651 00:29:33,680 --> 00:29:34,240 this curve? 652 00:29:34,559 --> 00:29:36,559 SPEAKER_03: Yeah, so I listen to a lot of podcasts. 653 00:29:36,799 --> 00:29:40,400 Um, one of my favorites is Astra, which is the American 654 00:29:40,400 --> 00:29:42,720 Society for Healthcare Human Resources Administration. 655 00:29:42,799 --> 00:29:46,160 So it hits close to home and it's a if they're quick listens. 656 00:29:46,240 --> 00:29:48,319 I think they're like 25, 30 minute listens. 657 00:29:48,480 --> 00:29:52,160 I I'll listen to them while I'm lifting or running or something. 658 00:29:52,400 --> 00:29:56,240 It's a podcast that's hosted by Luke Kerrigan and Bo Brabo, and 659 00:29:56,240 --> 00:29:58,880 they have such a diverse mix of healthcare leaders that share 660 00:29:58,880 --> 00:30:01,519 their experiences, their Successes and my favorite 661 00:30:01,599 --> 00:30:04,960 they're lessons learned because why make the mistake if you 662 00:30:04,960 --> 00:30:06,960 don't have to if you can learn from someone else? 663 00:30:07,200 --> 00:30:08,559 SPEAKER_02: I know Luke Kerrigan. 664 00:30:08,720 --> 00:30:10,160 He used to work at Career Builder. 665 00:30:10,240 --> 00:30:11,119 Is he a Phenom? 666 00:30:11,279 --> 00:30:13,039 I think he was at Phenom for a while. 667 00:30:13,279 --> 00:30:14,640 SPEAKER_03: He's at Phenom now, yes. 668 00:30:15,359 --> 00:30:16,000 SPEAKER_02: You know what? 669 00:30:16,400 --> 00:30:19,119 I don't know if Luke's listening, but like I hired, I 670 00:30:19,119 --> 00:30:23,839 tried to hire Luke for a sales engineering job probably 15 671 00:30:23,839 --> 00:30:27,039 years ago at this point, and he had a better job offer. 672 00:30:27,119 --> 00:30:29,759 But he's very uh always a big fan of Luke. 673 00:30:29,839 --> 00:30:31,599 So yeah, I I know him very well. 674 00:30:32,079 --> 00:30:33,119 SPEAKER_03: Yeah, he's fantastic. 675 00:30:33,440 --> 00:30:36,960 He's so personable, and like I said, his podcast is awesome. 676 00:30:37,279 --> 00:30:38,079 SPEAKER_02: Oh, that's great. 677 00:30:38,160 --> 00:30:40,720 Well, Luke, or tag you in this one for sure. 678 00:30:40,799 --> 00:30:42,000 Um, big fan. 679 00:30:42,079 --> 00:30:43,440 So oh that's great. 680 00:30:43,680 --> 00:30:45,039 Okay, well, last question. 681 00:30:45,119 --> 00:30:46,079 We'll list everything. 682 00:30:46,160 --> 00:30:48,880 Um, we'll link out to your LinkedIn profile for sure, 683 00:30:49,039 --> 00:30:49,680 Yvette. 684 00:30:49,759 --> 00:30:52,000 But you know, for folks that want to connect with you or 685 00:30:52,000 --> 00:30:54,559 follow your work, you know, where should they find you? 686 00:30:54,799 --> 00:30:56,720 SPEAKER_03: So obviously LinkedIn, but you can always 687 00:30:56,720 --> 00:30:59,839 reach out to me at evet at evethanson.com. 688 00:31:00,160 --> 00:31:00,640 SPEAKER_02: Awesome. 689 00:31:00,799 --> 00:31:01,200 Love it. 690 00:31:01,279 --> 00:31:03,839 Well, we'll link that in the show notes, uh, your email, your 691 00:31:03,839 --> 00:31:04,319 LinkedIn. 692 00:31:04,480 --> 00:31:06,559 Um, and again, it's been a great conversation. 693 00:31:06,640 --> 00:31:08,319 So really appreciate you joining us. 694 00:31:08,559 --> 00:31:10,000 SPEAKER_01: Thank you so much for having me. 695 00:31:10,240 --> 00:31:12,079 All right, thanks for tuning in. 696 00:31:12,240 --> 00:31:16,720 As always, head on over to changestate.io or shoot us a 697 00:31:16,720 --> 00:31:18,480 note on all the social media. 698 00:31:18,559 --> 00:31:22,400 We'd love to hear from you, and we'll check you guys next week.