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

You know, before we get started, you know, more deeply on the humanity aspect and you know connecting humanity and technology, you know, you mentioned in our pre-call that you know you've worked with recruitics for about 15 years, and you know, I would say from a partnership standpoint, you know, that's a pretty long vendor relationship in this industry. 00:03:45.439 --> 00:03:52.240 You know, many partnerships often you know kind of flame out after a handful of years, you know, an implementation and the honeymoon period ends. 00:03:52.400 --> 00:03:58.560 You know, I'm just curious, from a partnership lens, you know, what's made your partnerships with Recruitics last? 00:03:58.960 --> 00:03:59.520 You're right. 00:03:59.680 --> 00:04:03.680 I will say, Graham, a 15-year vendor relationship is rare and TA. 00:04:04.080 --> 00:04:08.639 Um I think it works because the relationship with Recruittics was never transactional. 00:04:08.800 --> 00:04:16.000 No matter what organization I was with, because I've worked with Recruits in multiple organizations, it really became an extension of whatever team I was on. 00:04:16.079 --> 00:04:23.199 So we shared goals, data, challenges, and they gave us full transparency into their roadmap so we could co-create solutions. 00:04:23.439 --> 00:04:30.000 I think back to when I originally started working with them, and the focus was really about programmatic distribution and basic campaign tracking. 00:04:30.240 --> 00:04:36.639 But that partnership evolved into full funnel analytics, UTM and attribution modeling, competitive insights. 00:04:36.879 --> 00:04:43.360 They even advised on emerging tech and AI use cases, which was really beneficial as we started to dip our toe in that world. 00:04:43.600 --> 00:04:50.160 And then my work started to expand into talent intelligence, market disruption analysis, and of course, AI strategy. 00:04:50.399 --> 00:04:54.720 And what I loved about recruitics is they were willing to evolve right alongside that work. 00:04:54.959 --> 00:04:59.360 Ultimately, the longevity came from aligning on outcomes and not deliverables. 00:04:59.600 --> 00:05:04.399 And as we both know, or anybody who's in this industry knows, recruitment marketing isn't static. 00:05:04.480 --> 00:05:10.879 It shifts with the labor market, technology, of course, our brands, and they grow with you at every step of the way. 00:05:11.120 --> 00:05:18.639 Ultimately, our work was built on trust and shared learning and continuous innovation, and it wasn't just about the contract at the end of the day. 00:05:18.879 --> 00:05:20.079 Yeah, no, I think that's great. 00:05:20.160 --> 00:05:25.439 And I think you know, the recruitment marketing and recruitment landscape in a gen in general continues to evolve. 00:05:25.519 --> 00:05:31.920 You know, we've done a call, well, probably a half dozen calls just this week talking about boy, like what's the future of SEO? 00:05:32.000 --> 00:05:53.040 And, you know, are we going to coin this new phrase geo, generative search optimization, and you know, and pushing back and like, hey, the reality is, you know, it's recruitment marketing is just evolved from newspapers to job boards to you know programmatic advertising and you know, social media and you know, Google ads, but at the end of the way, end of the day, it's still recruitment marketing. 00:05:53.120 --> 00:05:57.839 And I think you know, we're seeing a similar path with you know search engine optimization. 00:05:58.000 --> 00:06:00.480 You know, generative search is just a new search engine. 00:06:00.560 --> 00:06:08.079 So we're still optimizing search for you know AI search for chat GPT for Gemini and you know, whatever, I'll get off my soapbox. 00:06:08.160 --> 00:06:12.399 So, you know, that I think that is a pretty good segue into you know what I want to talk about. 00:06:12.560 --> 00:06:17.360 And you know, you know, let's talk a little bit more about healthcare, maybe more specifically. 00:06:17.519 --> 00:06:39.680 So, you know, you spent your entire career in health systems, whether it's United Health, you know, Optum, you know, Baylor, Scott, and white, you know, I think that it's probably easy to say healthcare is notoriously challenging, you know, high volume, tight labor markets, you know, clinical roles from some very, very specific credentials, you know, maybe compliance complexity, we can go on and on. 00:06:39.839 --> 00:06:48.959 You know, I'm curious, you know, from you know, from a healthcare lens, you know, how did some of you know maybe your healthcare constraints shape how you think about technology adoption? 00:06:49.120 --> 00:06:55.519 You know, I can imagine that, you know, you know, when you're in healthcare, you can't just implement any new flashy tool that comes your way. 00:06:55.600 --> 00:07:01.759 So, you know, are you seeing healthcare lag, lead when it comes to technology implementation, maybe AI adoption and recruiting? 00:07:02.079 --> 00:07:03.279 You know, that's a really great question. 00:07:03.439 --> 00:07:06.560 And I do believe healthcare used to lag in tech adoption. 00:07:06.720 --> 00:07:08.480 I don't believe that's true any longer. 00:07:08.800 --> 00:07:21.439 I would dare to say that in the last few years, health systems have moved to the front of the pack, leading the industry in responsible, human-centered AI across town engagement, forecasting, and workflow automation. 00:07:21.680 --> 00:07:27.199 But you are absolutely also right in the fact that healthcare is a very unique animal. 00:07:27.360 --> 00:07:31.199 You've got high volume, high stakes, deeply regulated. 00:07:31.360 --> 00:07:35.439 So, of course, we can't chase every shiny new tool that comes in front of us. 00:07:36.079 --> 00:07:42.399 Every tech decision has to be tied back to compliance, scalability, and ultimately patient care. 00:07:43.040 --> 00:07:48.800 So when I think about that, it really forced me into a process first, a

problem first mindset. 00:07:48.879 --> 00:07:52.639 And when I what I mean when I say that is I map out the workflow. 00:07:53.040 --> 00:07:58.639 I find the friction points, the gaps, um, the pain points, whatever you want to call it. 00:07:58.800 --> 00:08:14.399 And then you choose the technology that actually improves the experience in that space, whether it's recruiters, hiring managers, candidates themselves, and you really look for a goal that introduces AI in purposeful ways. 00:08:14.560 --> 00:08:17.519 So is it going to automate the screening and scheduling? 00:08:17.759 --> 00:08:21.040 Are you using it for predictive insights to engage passive talent? 00:08:21.199 --> 00:08:24.000 Are you freeing recruiters to do higher value work? 00:08:24.319 --> 00:08:28.160 You basically want to automate for efficiency, but that shouldn't be the only goal. 00:08:28.319 --> 00:08:32.399 The goal should really be about improving the candidate and the patient in experience. 00:08:32.480 --> 00:08:35.039 And I think that's what healthcare is focusing on right now. 00:08:35.279 --> 00:08:37.600 The industry as a whole is looking at that today. 00:08:37.840 --> 00:08:38.080 Yeah. 00:08:38.240 --> 00:08:46.000 So, you know, maybe a good quite good place to start then is like in your world, where did you first start experimenting then with AI and recruiting? 00:08:46.159 --> 00:08:58.639 Was it, you know, was it more in the, hey, we're trying to automate X, Y, and Z, or was there a particular moment in time when you said, boy, you know, this is going to change how we work, you know, we need to, you know, we need to set up X now? 00:08:59.039 --> 00:09:00.559 Yeah, that's a that's a really great question. 00:09:00.639 --> 00:09:04.799 And I'm thinking back to what was my real, my first real exposure to AI? 00:09:04.879 --> 00:09:15.120 And I, and if I think back, it probably was right around 2018 when everybody started exploring conversational bots and automation within their CRM technology. 00:09:15.279 --> 00:09:19.440 And I think back then most of us saw AI as a way to speed up administrative work, right? 00:09:19.600 --> 00:09:25.759 Like scheduling and screening and follow-ups and like reminders on our like these automatic reminders and things like that. 00:09:26.000 --> 00:09:28.480 Nobody really saw them as game changers. 00:09:28.879 --> 00:09:33.519 I think the moment that changed for me was during a it was recent actually. 00:09:33.840 --> 00:09:40.000 It was during a pilot that I was leading using an AI voice agent to conduct the first round candidate screens. 00:09:40.080 --> 00:09:51.840 And it was, it was a really, it was really eye-opening because within a few weeks the system had processed hundreds of applicants, not just processed and interviewed them, but it assessed them and scored them. 00:09:52.080 --> 00:09:58.559 And one of the surprises that um I found in reviewing the data was the quality didn't drop, it actually improved. 00:09:58.799 --> 00:10:08.879 We saw that candidates felt more informed, recruiters were gaining hours back in their day, hiring managers were getting better shortlists of candidates faster, and it was making them more happy. 00:10:09.120 --> 00:10:15.840 So it was the real it was that moment that I realized this isn't incremental, this fundamentally changes how we work. 00:10:15.919 --> 00:10:19.440 And so what I what I realized then is that AI is not a plug-in. 00:10:19.840 --> 00:10:26.480 It has to be treated as part of the core recruiting infrastructure, something that we could connect the entire talent journey on. 00:10:26.559 --> 00:10:28.559 So from attraction to alumni. 00:10:28.639 --> 00:10:35.919 So even in the employee journey itself, when you think about the employee journey, it really should start from the attraction perspective all the way to alumni. 00:10:36.240 --> 00:10:42.559 And I do believe AI is going to be core in making sure that we can tie it all together. 00:10:42.960 --> 00:10:45.600 Yeah, so Yvette, I think that's a really interesting piece. 00:10:45.759 --> 00:10:48.320 And you know, I wonder if we could unpack that a little bit more. 00:10:48.480 --> 00:10:59.039 So, you know, I think we hear a lot that, you know, for the last however many months and years, that you know, people are afraid that AI is going to get it wrong, AI is gonna take our jobs and and whatnot. 00:10:59.200 --> 00:11:15.360 But you know, I think in your example you said, you know, hey, like you found that you know AI running, I'll say, you know, almost first-round interviews or screenings with candidates did a on par or better job in servicing and you know, and screening out and identifying the right candidates. 00:11:15.600 --> 00:11:30.480 And you know, I think a few years ago, or you know, maybe a year ago, we heard you know, that hey, candidates are fine with AI getting them further around in the process, you know, as long as it's a you know a personalized experience, right? 00:11:30.559 --> 00:11:34.799 And they don't feel like you know, they're just being passed on to a you know to a bot and to an agent. 00:11:34.879 --> 00:11:42.399 And I would almost argue that, you know, from a consumer lens, it's no different than you know, people used to hate when you know an AI chatbot used to pop up. 00:11:42.480 --> 00:11:45.840 But if it can get me my answer to my question faster, I'm okay with that. 00:11:46.000 --> 00:11:51.600 You know, are you kind of seeing a similar balance play out with our you know AI sort of screening and interviewing tools? 00:11:51.759 --> 00:11:55.759 You know, given maybe it's a hey, a high volume of candidates are coming through. 00:11:55.919 --> 00:12:06.159 Hey, if I'm you know a qualified candidate, you know, I'm more than happy to engage with an AI generated interview if it's going to help me advance through the process faster. 00:12:06.320 --> 00:12:10.799 Is that kind of what you're um seeing from a balance, or

am I you know making a bit of a leap? 00:12:11.120 --> 00:12:12.159 Oh no, no, no, Graham. 00:12:12.240 --> 00:12:13.519 That's exactly what we're seeing. 00:12:13.679 --> 00:12:17.840 I I think today I look at AI as that bridge between efficiency and empathy. 00:12:17.919 --> 00:12:23.519 It it frees up the ability to focus on the human moments that really matter and think about what a human moment that really matters is. 00:12:23.679 --> 00:12:38.240 When a candidate applies for a job, and if there if it's a high volume role where you're getting, let's say, a hundred candidates a day, maybe, maybe more even, um, a recruiter does not have the time to look through that many applicants. 00:12:38.399 --> 00:12:48.399 So historically, the recruiter will go through the most current, the applicants that appear to be the best fit, who applied the soonest, or maybe the first ones who applied, but they don't get them all. 00:12:48.639 --> 00:12:52.480 Now, an agent can come in and screen every single applicant. 00:12:52.559 --> 00:12:53.919 So, what does that do for the recruiter? 00:12:54.000 --> 00:13:02.240 It obviously gives them, serves them up the best of all the applicants who applied, not just the ones they were able to get connected with within the timeframe that they had. 00:13:02.399 --> 00:13:04.320 And what does that do for the candidate? 00:13:04.480 --> 00:13:06.240 But it takes away that black hole. 00:13:06.320 --> 00:13:16.320 Because how many times have you heard, and you've seen this on Glassdoor, you've seen it on Comparably, and all these other places where candidates can leave reviews, is that they feel like they're not important. 00:13:16.559 --> 00:13:19.840 There's a black hole, they apply and never hear anything. 00:13:19.919 --> 00:13:21.919 So now you're getting rid of that feedback. 00:13:22.080 --> 00:13:28.320 You're saying, we're gonna take that away because now we've given you an opportunity to actually be screened by somebody and get assessed. 00:13:28.480 --> 00:13:39.919 And I think the technology is going to advance and give candidates an opportunity to even maybe forego recruit resumes, and maybe we can start um giving agents an opportunity to give feedback, right? 00:13:40.080 --> 00:13:45.440 So like they can say, I can apply for a job, or I go to apply for a job, and this is somebody, this isn't my idea. 00:13:45.600 --> 00:13:47.600 Somebody told me this, that this is their idea. 00:13:48.000 --> 00:13:56.159 They want to be able to apply for a job and instead of a resume, talk to an agent and say, and the agent asks dynamic questions, right? 00:13:56.240 --> 00:14:08.399 And then I can ask the agent questions, and at the end of my conversation, the agent can honestly tell me, hey, that you applied for this job, and based on what you've shared today, you're about a 75% fit. 00:14:08.559 --> 00:14:11.919 We have 30 other candidates who are a hundred percent fit. 00:14:12.159 --> 00:14:19.440 We don't think this job is right for you, but why don't you keep looking and we'll serve you up other jobs that might be a better fit for you based on what you shared today? 00:14:19.600 --> 00:14:33.360 Like I think that's where their technology is going, and I think candidates are going to be more and more appreciative that we're giving them an opportunity to not just share about their experience, but get feedback on why they are fit for this role or why they may not be the best fit for this role. 00:14:33.759 --> 00:14:41.200 Yeah, well, you know, I would say I think that's a great parallel to you know what we're seeing in the evolution of you know SEO. 00:14:41.360 --> 00:14:49.200 And so, you know, the way I've been explaining it lately is you know, you think about you know how people use Google, it's you know you're essentially yelling into a search engine. 00:14:49.279 --> 00:14:52.480 It's you know, jobs near me, it's pizza restaurants. 00:14:52.639 --> 00:14:59.919 And you know, great, that's you know, and and websites have been built to optimize for short keywords that they want to capture. 00:15:00.159 --> 00:15:09.039 And you know, because of that, you have all these content farms where you know everyone's writing you know, 500 blog posts about pizza restaurants or jobs. 00:15:09.200 --> 00:15:16.799 And you know, the whole goal is we want to make sure that we're showing up higher on Google and you know getting on the first page or second page with links. 00:15:16.960 --> 00:15:36.879 And I think you know, what you know AI is kind of injecting in here, you know, with generative search becoming more important, people you know, using Chat GPT and Gemini, you know, is you know, you're having conversations with a chat, you know, with a uh generative search agent, an LLM, and it is much more like the scenario that you just described, Yvette. 00:15:36.960 --> 00:15:43.279 And it's you know, hey, I, you know, I'm looking for, I'm a you know, I'm a nurse with five years of experience. 00:15:43.440 --> 00:15:45.600 I move into the Dallas Fort Worth area. 00:15:45.759 --> 00:15:47.039 Here's where my credentials are. 00:15:47.200 --> 00:15:57.679 I'm looking for a company that has, you know, has leadership opportunities, you know, and or continuing education benefits and you know, great work-life balance where I won't have to work weekends. 00:15:57.840 --> 00:16:11.759 And like people can have a literal conversation like that with ChatGPT, with Gemini, and it will pop out, you know, employers that you know fit that match are looking for those types of candidates or provide those types of you know benefits. 00:16:11.919 --> 00:16:25.440 And I think the challenge is you know, companies are having to evolve their search strategy to make sure that they have the content or the context that you know match those deep conversations that you know candidates want to have. 00:16:25.600 --> 00:16:32.720 And so I think the scenario that you just described is you know what

we're kind of seeing play out in real time in generative search. 00:16:32.879 --> 00:16:51.840 And now instead of racing for you know keywords in the first page on Google, you know, we have companies that are racing to make sure that all the good things that they are known for, or all the good reasons why people should go work for an organization, you know, we have to go fight for real estate in LLMs and generative search models, right? 00:16:52.080 --> 00:17:01.759 And so I think we're not far off, uh maybe not far off as a stretch, but I think we're I think we're progressing towards you know the state that you kind of described, Yvette. 00:17:01.840 --> 00:17:03.519 And like I hope we get there. 00:17:03.759 --> 00:17:14.160 Because again, like I think you know it's it's a similar challenge where you know Google search has gotten a bit gummed up with, you know, it's too many people trying to fight for links on page one. 00:17:14.240 --> 00:17:29.680 And I think it's probably a similar standpoint when it looks at you know how easy it's gotten to apply to jobs and you know, integrate applies everywhere, and I can open up a requisition and I get a hundred applications in a day, sure, but how many of them are the right people? 00:17:29.839 --> 00:17:40.240 So I, you know, I can see the pendulum swinging back towards the candidate, you know, in a few different ways with the you know, call it a the assist of um of AI. 00:17:40.559 --> 00:17:41.759 I completely agree with you. 00:17:41.839 --> 00:17:43.920 And I and I think we are headed in that direction, Graham. 00:17:44.000 --> 00:17:47.119 And I would agree with you that it is in the best interest of the candidate. 00:17:47.279 --> 00:17:49.680 And I think that's why recruitment marketing is so important. 00:17:49.839 --> 00:17:55.279 I think that making sure that employers are marketing why, what's that employee value proposition? 00:17:55.359 --> 00:17:59.759 What are you promising to your potential employers and making it authentic and genuine? 00:17:59.920 --> 00:18:05.519 And because that's ultimately what candidates are doing, especially today in the during the era of the great stay, right? 00:18:05.599 --> 00:18:10.880 Like they're not gonna make a move unless they really feel like you're gonna give them what they have, what they're looking for. 00:18:11.119 --> 00:18:11.680 Yeah, yeah. 00:18:11.759 --> 00:18:12.720 No, I completely agree. 00:18:12.880 --> 00:18:16.480 Well, I want to talk a little bit more about you know the realities of AI implementations. 00:18:16.559 --> 00:18:17.920 You know, I think it's a great segue. 00:18:18.079 --> 00:18:24.000 So, you know, I think you recently presented, uh, it might have been two, three weeks ago at this point at LinkedIn Talent Connect. 00:18:24.079 --> 00:18:28.640 I think you're presenting with David Barr about you know using AI to personalize talent engagement. 00:18:28.720 --> 00:18:31.440 And I know that's kind of an area that's near and

dear to your heart. 00:18:31.599 --> 00:18:36.559 You know, I'm curious, you know, let's talk about what's actually working from a talent engagement standpoint. 00:18:36.720 --> 00:18:41.759 Where is where do you see kind of AI delivering value in your recruitment process? 00:18:41.920 --> 00:18:49.119 Not just, you know, where vendors promise it you know is gonna work, but where where are you personally seeing measurable improvement with you know with AI? 00:18:49.440 --> 00:18:55.359 Yeah, I I think AI has been most valuable in specific repeatable parts of recruiting. 00:18:55.519 --> 00:19:00.400 Um the biggest wins I've seen are in the areas of things like personalized engagement. 00:19:00.559 --> 00:19:10.160 So AI allows us to nurture passive talent at scale with textual messaging, often doubling engagement versus that generic outreach. 00:19:10.480 --> 00:19:13.920 Screening and scheduling, also another area where we've seen AI. 00:19:14.000 --> 00:19:19.039 I know talked about voice agents and chatbots, but that dramatically reduces admin work. 00:19:19.359 --> 00:19:26.000 I mean, one team can cut time to screen by over 60% by implementing a voice agent or a chat bot. 00:19:26.240 --> 00:19:31.279 And then the other area where I've seen some big wins is in the predictive insights side. 00:19:31.359 --> 00:19:36.720 Uh, talent insights helps forecast hiring needs as well as spot the market disruptions. 00:19:36.960 --> 00:19:42.640 So teams can source proactively versus reactively, which is what you want your teams to do. 00:19:42.799 --> 00:19:51.519 I mean, that's what we're going towards that model of is being more proactive, reaching the paths of talent, but we have to give them some triggers, like where should we go first? 00:19:51.680 --> 00:19:54.079 Like, um kind of like a bullseye approach. 00:19:54.160 --> 00:19:56.400 Let's start here and then fan ourselves out. 00:19:56.640 --> 00:20:01.599 And then I do think that there are some areas where there's still opportunity for AI. 00:20:01.839 --> 00:20:04.960 I think that there's been some disappointment around the integration. 00:20:05.119 --> 00:20:13.119 I think it's still a major challenge because even great tools lose value when they don't play well with legacy systems or they disrupt the recruiter workflow. 00:20:13.279 --> 00:20:24.079 That's why I think it's so important to do the front-end work, which is that recruiter workflow analysis, and then identify what tool what tool makes the most sense before you just go buy the tool and try to implement it. 00:20:24.400 --> 00:20:30.000 Yeah, well, I I've always said, you know, integration is the most poorly used word in in HR tech. 00:20:30.240 --> 00:20:32.160 And you know, I stand by that today. 00:20:32.400 --> 00:20:44.319 I do think that I think it's gotten better, it's gotten easier, and you know, integration doesn't uh scare as many people, you know, but you know, integration doesn't mean you know, provides a link to a job posting. 00:20:44.400 --> 00:20:47.759 That's you know, it's a very different integration, I think, what people would truly mean. 00:20:48.000 --> 00:20:54.400 So I I guess I'd say a harder question than, you know, where would you say AI has kind of disappointed you the most? 00:20:54.640 --> 00:20:56.480 Is it in that integration area? 00:20:56.880 --> 00:20:57.839 Yeah, I think so. 00:20:58.000 --> 00:21:03.359 In the integration, that and I think the other area would probably be um the overselling from vendors. 00:21:03.680 --> 00:21:09.680 You know, it's it's comical to think about it, but like when you do a vendor demo, they show you every bell and whistle. 00:21:09.759 --> 00:21:15.839 And I think, Graham, one of the things that I have noticed is that integration, it's it's more used today. 00:21:15.920 --> 00:21:18.640 You're right, it was an underused word, but it's more used today. 00:21:18.799 --> 00:21:21.519 But I think vendors are so quick to say, yeah, we can integrate, no problem. 00:21:21.759 --> 00:21:23.200 Open API, no problem. 00:21:23.359 --> 00:21:30.319 And then when the rubber hits the road, it's like, oh no, not so much, not so not as seamless as we thought it was going to be. 00:21:30.559 --> 00:21:33.680 So I think that that's where I there's still some challenges. 00:21:34.000 --> 00:21:42.319 Yeah, well, I I think the bigger challenge, and we see this just in the news everywhere, is like everyone is being tasked to, you know, use the AI somehow. 00:21:42.559 --> 00:21:46.720 And I think that there are a lot of vendors that are taken advantage of that fact, right? 00:21:46.880 --> 00:22:00.319 And you know, when we go through our practices, it's you know, sure, like you can use AI, and like, you know, everyone can go by a Gartner report and you know figure out that, yep, they aren't using AI enough, or they should use it in employer brand or in their process. 00:22:00.400 --> 00:22:10.400 But you know, the bigger problem is doing the work to map out you know where and why, and you know, more importantly, probably what problems you're gonna solve, you know, how much time it's taking to do X, Y, and Z. 00:22:10.480 --> 00:22:16.640 And like if we're gonna prioritize AI to you know something as simple as automate scheduling, right? 00:22:16.799 --> 00:22:20.880 Or you know, screen out candidates that you know simply don't live in the US. 00:22:20.960 --> 00:22:37.839 You know, I think that there are a lot of you know low-hanging fruit areas, and and I think way too often you know, companies jump to the you know, the holy grail, we're gonna buy acts system if it's going to find candidates and deliver the top three that are already pre-screened and and ready to start tomorrow. 00:22:37.920 --> 00:22:40.640 And I think the reality is you know somewhere in between, right? 00:22:40.720 --> 00:22:47.119 And I think we need to sometimes maybe admit that there's some limitations to where we wanna um where we want to start.

00:22:47.279 --> 00:22:48.720 But hey, we're not a vendor anymore. 00:22:48.799 --> 00:22:55.680 So this is a great and sometimes admit this isn't this product doesn't do everything you need it to do, right? 00:22:55.759 --> 00:23:02.000 Like it does 80% of what you want it to do, and we can work on that last 20% if you help us. 00:23:02.079 --> 00:23:03.279 Like, let's be a partner in this. 00:23:03.440 --> 00:23:08.799 I think vendors shouldn't be afraid to say that, but they are so afraid to say that because they're afraid they're gonna lose the deal. 00:23:09.039 --> 00:23:16.559 But ultimately, if you end up with a product that doesn't get adopted because it doesn't do everything we thought it was going to do, then everybody loses. 00:23:16.720 --> 00:23:21.359 So I think that's one of the areas a vendor should probably be a little bit more open to. 00:23:21.680 --> 00:23:28.720 Well, I'm I'm reminded of uh an old boss of mine who said, you know, he was sitting in vendor demos and you know it was who knows? 00:23:28.799 --> 00:23:39.359 We'll say it was with bullhorn, you know, and and then bullhorn sales rep was promising them could do X, it could do Y, it could do Z, you know, and and then one guy, you know, at Bullhorn said, Well, no, no, no, no. 00:23:39.440 --> 00:23:40.799 It actually it can't do Z. 00:23:40.880 --> 00:23:43.599 And you know, sales rep kind of cut him off, said, No, it could do it. 00:23:43.680 --> 00:23:47.440 And you know, remember our old boss said, No, that's the guy I want in the room every time. 00:23:47.599 --> 00:23:49.680 The guy that tells me what it can't do. 00:23:50.000 --> 00:24:03.119 And we can, you know, we can do, you know, if we could do seven out of ten things, that's still better than you know, than than where we're at today, you know, but we'd rather do seven things well, you know, than than overpromise at uh at this point. 00:24:03.279 --> 00:24:11.599 And so I think there's a lot of value in boy, transparency and a vendor agnostic sort of lens to, you know, hey, if it doesn't do everything, that's okay. 00:24:11.759 --> 00:24:13.920 Let's just make sure they can do all the things that we're seeing. 00:24:14.160 --> 00:24:14.640 Absolutely. 00:24:14.880 --> 00:24:24.640 Well, one thing you shared on LinkedIn, and I'm gonna paraphrase it and get it close to right, is you know, in your world, you think AI can enhance creativity and not, you know, not replace it. 00:24:24.880 --> 00:24:34.240 And you know, I think that you know, your point was it's uh it's a reminder that technology, if if it's used kind of thoughtfully, can amplify our humanity rather than diminish it, right? 00:24:34.400 --> 00:24:41.359 And and I think that you know that's probably a different framing than you know most of us are seeing and hearing at conferences. 00:24:41.519 --> 00:24:48.559 You know, many vendors are selling efficiency and automation, but you are kind of talking about you know humanity and belonging. 00:24:48.640 --> 00:24:51.599 And you know, I know it's literally in many of your titles, right? 00:24:51.759 --> 00:24:58.240 And so maybe walk me through how that philosophy you know shows up in your shows up in your work. 00:24:58.640 --> 00:25:04.960 Yeah, I think um I've always believed that technology should expand our capacity for connection, not replace it. 00:25:05.039 --> 00:25:12.960 So AI is most powerful when we can remove friction, not feeling, and create a space for the work only humans can do. 00:25:13.039 --> 00:25:18.400 And that is practice empathy, tell our story and our brand, and express belonging. 00:25:18.559 --> 00:25:20.160 So I think that that's really important. 00:25:20.400 --> 00:25:27.039 The philosophy can guide you through implementation with AI is looking at the design of everything. 00:25:27.200 --> 00:25:50.319 So start starting with the moments that matter, like improving candidate feedback, looking at the recruiter workload, or even a new hire's first day, and then making sure that you have open communication with your team, framing AI as giving recruiters time back for real conversations, maybe elevating their role to a talent advisor, or there's a new term, talent agent, or talent business partner, whatever term you want to use. 00:25:50.480 --> 00:25:53.920 But it's not really to replace them, it's really to elevate their role. 00:25:54.160 --> 00:25:59.839 And then, of course, culture, because I think about AI technology and I think about the prompts that we're using. 00:25:59.920 --> 00:26:06.880 So prompts and chat flows should still really reflect empathy and inclusion because those small details scale culture. 00:26:07.039 --> 00:26:14.240 So when I think about that, it's like we have to really think about how it's making the experience more human at scale. 00:26:14.480 --> 00:26:23.599 And AI should amplify our culture and not replace it, and it shouldn't just be about the speed, if that makes sense. 00:26:24.000 --> 00:26:24.799 Yeah, yeah. 00:26:24.960 --> 00:26:26.160 No, I think it totally does. 00:26:26.240 --> 00:26:53.519 And I think like, you know, even some of the examples of you know, where we're going with generative search, I think, you know, for the right organizations that you know implemented or action correctly, like, you know, AI and and LLM and generative search is going to give us a chance to share our stories and share our culture a lot more broadly and a lot more deeply than you know, you typically would get in, you know, Arg at least, you know, SEO that would you know maybe penalize or reward the wrong players in that space too. 00:26:53.599 --> 00:27:07.680 So I think I'm I think we're in a in a very interesting spot in kind of bridging that gap between you know humanity and and technology and you know, and using that to really shine the light on you know more deeper stories within organizations and cultures as a whole. 00:27:08.160 --> 00:27:13.279 Well, talk to me about you

know a TA leader, you know, sitting in their office then right now, Yvette. 00:27:13.359 --> 00:27:14.720 We've talked a lot about AI. 00:27:14.880 --> 00:27:29.759 I think a lot of executives are getting pressure from the C-suite to do something with AI, you know, the drowning vendor pitches, as we've kind of said, you know, most vendor pitches end with we can do everything, you know, and so I think there's oftentimes a lot of you know paralysis around not knowing where to start. 00:27:29.920 --> 00:27:42.880 And so, you know, if you had some advice for you know the overwhelmed TA leader, you know, that's sitting there getting pressure from the C-suite to do something with AI, you know, what's what's one piece of advice you'd give to you know a town acquisition leader today? 00:27:42.960 --> 00:27:43.680 What would that be? 00:27:43.920 --> 00:27:52.400 Yeah, my one piece of advice would be to start small, measure fast, and design for adoption, not perfection. 00:27:52.559 --> 00:27:56.160 So don't go in trying to overhaul your whole tech stack at once. 00:27:56.400 --> 00:28:01.680 Pick one pain point that's measurable, like screening or candidate engagement. 00:28:01.920 --> 00:28:03.839 And prove the value there first. 00:28:04.000 --> 00:28:13.759 Build trust with your recruiters early, because that's key to adoption, by being transparent about what the tool does and doesn't do to our point earlier. 00:28:14.000 --> 00:28:15.759 Make adoption a KPI. 00:28:16.000 --> 00:28:19.680 Because at the end of the day, you can buy the best AI on the market. 00:28:19.759 --> 00:28:24.480 But if your team doesn't trust it or it doesn't fit the workflow, you'll never see the ROI. 00:28:24.640 --> 00:28:28.960 So the most successful pilots I've led, I didn't consider tech projects. 00:28:29.119 --> 00:28:35.359 I considered them change management initiatives that were focused on helping people that work smarter, not differently. 00:28:35.599 --> 00:28:36.720 Yeah, I think that's great. 00:28:36.960 --> 00:28:38.960 Well, I think that's a good place for us to close. 00:28:39.039 --> 00:28:41.279 I got a couple quick hit, quick hits for you, If that. 00:28:41.440 --> 00:28:43.839 So, you know, first one, it's contrarian take time. 00:28:44.000 --> 00:28:48.559 So, you know, what's your most contrarian prediction about talent acquisition technology? 00:28:48.640 --> 00:28:52.480 You know, what's what's something that ever thinks is gonna happen that you might disagree with? 00:28:52.799 --> 00:28:56.000 I think that the future of TA isn't about more automation. 00:28:56.079 --> 00:28:58.559 It's gonna be about more curation and connection. 00:28:58.720 --> 00:29:06.240 I think everyone assumes AI is gonna replace recruiters, but I think the real advantage is gonna come from teams who use it to deepen human connection. 00:29:06.480 --> 00:29:10.640 I think automation is at this day and age, it's table stakes. 00:29:10.799 --> 00:29:14.400 Trust and personalization will be the true different differentiators. 00:29:14.559 --> 00:29:17.920 I think the next phase won't be about who has the most tools. 00:29:18.000 --> 00:29:24.880 It's gonna be about who uses them most intentionally to make the experience feel more human, transparent, and authentic. 00:29:25.119 --> 00:29:26.000 All right, I like that. 00:29:26.160 --> 00:29:31.519 Okay, well, the last question that I ask everyone is so what are you reading or listening to do these days? 00:29:31.599 --> 00:29:34.240 And you know, how are you learning and staying ahead of this curve? 00:29:34.559 --> 00:29:36.559 Yeah, so I listen to a lot of podcasts. 00:29:36.799 --> 00:29:42.720 Um, one of my favorites is Astra, which is the American Society for Healthcare Human Resources Administration. 00:29:42.799 --> 00:29:46.160 So it hits close to home and it's a if they're quick listens. 00:29:46.240 --> 00:29:48.319 I think they're like 25, 30 minute listens. 00:29:48.480 --> 00:29:52.160 I I'll listen to them while I'm lifting or running or something. 00:29:52.400 --> 00:30:06.960 It's a podcast that's hosted by Luke Kerrigan and Bo Brabo, and they have such a diverse mix of healthcare leaders that share their experiences, their Successes and my favorite they're lessons learned because why make the mistake if you don't have to if you can learn from someone else? 00:30:07.200 --> 00:30:08.559 I know Luke Kerrigan. 00:30:08.720 --> 00:30:10.160 He used to work at Career Builder. 00:30:10.240 --> 00:30:11.119 Is he a Phenom? 00:30:11.279 --> 00:30:13.039 I think he was at Phenom for a while. 00:30:13.279 --> 00:30:14.640 He's at Phenom now, yes. 00:30:15.359 --> 00:30:16.000 You know what? 00:30:16.400 --> 00:30:27.039 I don't know if Luke's listening, but like I hired, I tried to hire Luke for a sales engineering job probably 15 years ago at this point, and he had a better job offer. 00:30:27.119 --> 00:30:29.759 But he's very uh always a big fan of Luke. 00:30:29.839 --> 00:30:31.599 So yeah, I I know him very well. 00:30:32.079 --> 00:30:33.119 Yeah, he's fantastic. 00:30:33.440 --> 00:30:36.960 He's so personable, and like I said, his podcast is awesome. 00:30:37.279 --> 00:30:38.079 Oh, that's great. 00:30:38.160 --> 00:30:40.720 Well, Luke, or tag you in this one for sure. 00:30:40.799 --> 00:30:42.000 Um, big fan. 00:30:42.079 --> 00:30:43.440 So oh that's great. 00:30:43.680 --> 00:30:45.039 Okay, well, last question. 00:30:45.119 --> 00:30:46.079 We'll list everything. 00:30:46.160 --> 00:30:49.680 Um, we'll link out to your LinkedIn profile for sure, Yvette. 00:30:49.759 --> 00:30:54.559 But you know, for folks that want to connect with you or follow your work, you know, where should they find you? 00:30:54.799 --> 00:30:59.839 So obviously LinkedIn, but you can always reach out to me at evet at evethanson.com. 00:31:00.160 --> 00:31:00.640 Awesome. 00:31:00.799 --> 00:31:01.200 Love it. 00:31:01.279 --> 00:31:04.319 Well, we'll link that in the show notes, uh, your email, your LinkedIn. 00:31:04.480 --> 00:31:06.559 Um, and again, it's been a great conversation. 00:31:06.640 --> 00:31:08.319 So really appreciate you joining us. 00:31:08.559 --> 00:31:10.000 Thank you so much for having me. 00:31:10.240 --> 00:31:12.079 All right, thanks for tuning in. 00:31:12.240 --> 00:31:18.480 As always, head on over to changestate.io or shoot us a note on all the social media. 00:31:18.559 --> 00:31:22.400 We'd love to hear from you, and we'll check you guys next week.