November 19, 2025 • 31 mins
Yvette Hansen has spent nearly two decades leading talent acquisition at major health systems: UnitedHealth Group, Optum, Amedisys, and most recently as Director of TA & Belonging at Baylor Scott & White Health. In that time, she's learned that healthcare doesn't let you chase shiny tools. High stakes, compliance requirements, and tight labor markets force a process-first mindset.
But Yvette's also honest about what disappoints: vendors who oversell integration capabilities, tools that look great in demos but disrupt recruiter workflows, and the gap between "we can do that" and actually doing it. One vendor demo promised seamless integration. When implementation started? "Not so much."
One surprising insight: healthcare is no longer lagging in tech adoption. Health systems have moved to the front of the pack on responsible AI implementation, proving that constraints can drive better outcomes.
For TA leaders drowning in vendor pitches and paralyzed by options, this episode delivers a practical roadmap.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
SPEAKER_00 (00:00):
Welcome to the Changing State of Talent
Acquisition podcast with yourhost, Graham Thornton.
Each episode brings youunfiltered conversations about
the tools, trends, andtechnologies impacting the
future of talent acquisition.
Our guests share their storieson what's working, what's hype,
and what's actually helpingcompanies hire better and grow
(00:21):
faster.
Have feedback or want to jointhe show?
Head on over to Tollibity.com tolearn more.
But now we're on to this week'sepisode.
SPEAKER_03 (01:29):
And that really started as a foundation that
shaped everything because itreally taught me how deeply the
hiring process affects bothcandidates and hiring teams.
I would get letters and cardsthat's back before email was
very popular from candidatesabout how this was affecting
their family, not just a job.
So I realized quickly that itwasn't really about filling a
(01:50):
job or filling a role.
It was really about how I wasmaking people feel.
And that really was a turningpoint for me because it really
made me look at the entireprocess end to end and made me
realize that there wasbottlenecks in the process about
where people, it wasn't aboutpeople working harder.
It was really about workflowsand technology.
(02:12):
If we really wanted to affectchange and how we were helping
candidates, it was really goingto be about what workflow made
the most sense to reach thecandidate where they are in that
moment and what when when didthat moment really matter?
So it really led me intosourcing, uh, recruitment
marketing, and ultimatelybuilding TA infrastructures.
So I've done everything fromstanding up sourcing and
(02:33):
branding teams, depleming CRMs,automation and AI.
And that's really allowed me toblend innovation with empathy,
like I said, reallyunderstanding the candidate,
launching automation and AIprograms that made hiring both
faster and more human.
And today my focus is on theintersection of AI, ethics, and
belonging.
So building systems that areefficient, fair, but also
(02:55):
reflective of the people thatthey serve.
So I'm essentially interested inhow TA can evolve from that
transactional functional thatwe've seen it be to a true
intelligence engine that'spredicting needs, that engages
the passive talent, and shapesorganizational readiness.
SPEAKER_02 (03:19):
And I think that your you know your background
really kind of leans into thehuman and uh in human resources
too.
You know, before we get started,you know, more deeply on the
humanity aspect and you knowconnecting humanity and
technology, you know, youmentioned in our pre-call that
you know you've worked withrecruitics for about 15 years,
and you know, I would say from apartnership standpoint, you
(03:42):
know, that's a pretty longvendor relationship in this
industry.
You know, many partnershipsoften you know kind of flame out
after a handful of years, youknow, an implementation and the
honeymoon period ends.
You know, I'm just curious, froma partnership lens, you know,
what's made your partnershipswith Recruitics last?
SPEAKER_03 (03:58):
You're right.
I will say, Graham, a 15-yearvendor relationship is rare and
TA.
Um I think it works because therelationship with Recruittics
was never transactional.
No matter what organization Iwas with, because I've worked
with Recruits in multipleorganizations, it really became
an extension of whatever team Iwas on.
So we shared goals, data,challenges, and they gave us
(04:19):
full transparency into theirroadmap so we could co-create
solutions.
I think back to when Ioriginally started working with
them, and the focus was reallyabout programmatic distribution
and basic campaign tracking.
But that partnership evolvedinto full funnel analytics, UTM
and attribution modeling,competitive insights.
They even advised on emergingtech and AI use cases, which was
(04:40):
really beneficial as we startedto dip our toe in that world.
And then my work started toexpand into talent intelligence,
market disruption analysis, andof course, AI strategy.
And what I loved aboutrecruitics is they were willing
to evolve right alongside thatwork.
Ultimately, the longevity camefrom aligning on outcomes and
not deliverables.
And as we both know, or anybodywho's in this industry knows,
(05:02):
recruitment marketing isn'tstatic.
It shifts with the labor market,technology, of course, our
brands, and they grow with youat every step of the way.
Ultimately, our work was builton trust and shared learning and
continuous innovation, and itwasn't just about the contract
at the end of the day.
SPEAKER_02 (05:18):
Yeah, no, I think that's great.
And I think you know, therecruitment marketing and
recruitment landscape in a genin general continues to evolve.
You know, we've done a call,well, probably a half dozen
calls just this week talkingabout boy, like what's the
future of SEO?
And, you know, are we going tocoin this new phrase geo,
generative search optimization,and you know, and pushing back
and like, hey, the reality is,you know, it's recruitment
(05:41):
marketing is just evolved fromnewspapers to job boards to you
know programmatic advertisingand you know, social media and
you know, Google ads, but at theend of the way, end of the day,
it's still recruitmentmarketing.
And I think you know, we'reseeing a similar path with you
know search engine optimization.
You know, generative search isjust a new search engine.
So we're still optimizing searchfor you know AI search for chat
(06:04):
GPT for Gemini and you know,whatever, I'll get off my
soapbox.
So, you know, that I think thatis a pretty good segue into you
know what I want to talk about.
And you know, you know, let'stalk a little bit more about
healthcare, maybe morespecifically.
So, you know, you spent yourentire career in health systems,
whether it's United Health, youknow, Optum, you know, Baylor,
(06:24):
Scott, and white, you know, Ithink that it's probably easy to
say healthcare is notoriouslychallenging, you know, high
volume, tight labor markets, youknow, clinical roles from some
very, very specific credentials,you know, maybe compliance
complexity, we can go on and on.
You know, I'm curious, you know,from you know, from a healthcare
lens, you know, how did some ofyou know maybe your healthcare
(06:45):
constraints shape how you thinkabout technology adoption?
You know, I can imagine that,you know, you know, when you're
in healthcare, you can't justimplement any new flashy tool
that comes your way.
So, you know, are you seeinghealthcare lag, lead when it
comes to technologyimplementation, maybe AI
adoption and recruiting?
SPEAKER_03 (07:02):
You know, that's a really great question.
And I do believe healthcare usedto lag in tech adoption.
I don't believe that's true anylonger.
I would dare to say that in thelast few years, health systems
have moved to the front of thepack, leading the industry in
responsible, human-centered AIacross town engagement,
forecasting, and workflowautomation.
But you are absolutely alsoright in the fact that
(07:24):
healthcare is a very uniqueanimal.
You've got high volume, highstakes, deeply regulated.
So, of course, we can't chaseevery shiny new tool that comes
in front of us.
Every tech decision has to betied back to compliance,
scalability, and ultimatelypatient care.
So when I think about that, itreally forced me into a process
(07:46):
first, a problem first mindset.
And when I what I mean when Isay that is I map out the
workflow.
I find the friction points, thegaps, um, the pain points,
whatever you want to call it.
And then you choose thetechnology that actually
improves the experience in thatspace, whether it's recruiters,
hiring managers, candidatesthemselves, and you really look
(08:10):
for a goal that introduces AI inpurposeful ways.
So is it going to automate thescreening and scheduling?
Are you using it for predictiveinsights to engage passive
talent?
Are you freeing recruiters to dohigher value work?
You basically want to automatefor efficiency, but that
shouldn't be the only goal.
The goal should really be aboutimproving the candidate and the
(08:31):
patient in experience.
And I think that's whathealthcare is focusing on right
now.
The industry as a whole islooking at that today.
SPEAKER_02 (08:37):
Yeah.
So, you know, maybe a good quitegood place to start then is like
in your world, where did youfirst start experimenting then
with AI and recruiting?
Was it, you know, was it more inthe, hey, we're trying to
automate X, Y, and Z, or wasthere a particular moment in
time when you said, boy, youknow, this is going to change
how we work, you know, we needto, you know, we need to set up
X now?
SPEAKER_03 (08:59):
Yeah, that's a that's a really great question.
And I'm thinking back to whatwas my real, my first real
exposure to AI?
And I, and if I think back, itprobably was right around 2018
when everybody started exploringconversational bots and
automation within their CRMtechnology.
And I think back then most of ussaw AI as a way to speed up
administrative work, right?
(09:19):
Like scheduling and screeningand follow-ups and like
reminders on our like theseautomatic reminders and things
like that.
Nobody really saw them as gamechangers.
I think the moment that changedfor me was during a it was
recent actually.
It was during a pilot that I wasleading using an AI voice agent
to conduct the first roundcandidate screens.
(09:40):
And it was, it was a really, itwas really eye-opening because
within a few weeks the systemhad processed hundreds of
applicants, not just processedand interviewed them, but it
assessed them and scored them.
And one of the surprises that umI found in reviewing the data
was the quality didn't drop, itactually improved.
We saw that candidates felt moreinformed, recruiters were
(10:01):
gaining hours back in their day,hiring managers were getting
better shortlists of candidatesfaster, and it was making them
more happy.
So it was the real it was thatmoment that I realized this
isn't incremental, thisfundamentally changes how we
work.
And so what I what I realizedthen is that AI is not a
plug-in.
It has to be treated as part ofthe core recruiting
(10:22):
infrastructure, something thatwe could connect the entire
talent journey on.
So from attraction to alumni.
So even in the employee journeyitself, when you think about the
employee journey, it reallyshould start from the attraction
perspective all the way toalumni.
And I do believe AI is going tobe core in making sure that we
can tie it all together.
SPEAKER_02 (10:42):
Yeah, so Yvette, I think that's a really
interesting piece.
And you know, I wonder if wecould unpack that a little bit
more.
So, you know, I think we hear alot that, you know, for the last
however many months and years,that you know, people are afraid
that AI is going to get itwrong, AI is gonna take our jobs
and and whatnot.
But you know, I think in yourexample you said, you know, hey,
like you found that you know AIrunning, I'll say, you know,
(11:05):
almost first-round interviews orscreenings with candidates did a
on par or better job inservicing and you know, and
screening out and identifyingthe right candidates.
And you know, I think a fewyears ago, or you know, maybe a
year ago, we heard you know,that hey, candidates are fine
with AI getting them furtheraround in the process, you know,
(11:27):
as long as it's a you know apersonalized experience, right?
And they don't feel like youknow, they're just being passed
on to a you know to a bot and toan agent.
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 popup.
But if it can get me my answerto my question faster, I'm okay
with that.
You know, are you kind of seeinga similar balance play out with
(11:48):
our you know AI sort ofscreening and interviewing
tools?
You know, given maybe it's ahey, a high volume of candidates
are coming through.
Hey, if I'm you know a qualifiedcandidate, you know, I'm more
than happy to engage with an AIgenerated interview if it's
going to help me advance throughthe process faster.
Is that kind of what you're umseeing from a balance, or am I
(12:09):
you know making a bit of a leap?
SPEAKER_03 (12:11):
Oh no, no, no, Graham.
That's exactly what we'reseeing.
I I think today I look at AI asthat bridge between efficiency
and empathy.
It it frees up the ability tofocus on the human moments that
really matter and think aboutwhat a human moment that really
matters is.
When a candidate applies for ajob, and if there if it's a high
volume role where you'regetting, let's say, a hundred
candidates a day, maybe, maybemore even, um, a recruiter does
(12:36):
not have the time to lookthrough that many applicants.
So historically, the recruiterwill go through the most
current, the applicants thatappear to be the best fit, who
applied the soonest, or maybethe first ones who applied, but
they don't get them all.
Now, an agent can come in andscreen every single applicant.
So, what does that do for therecruiter?
It obviously gives them, servesthem up the best of all the
(12:56):
applicants who applied, not justthe ones they were able to get
connected with within thetimeframe that they had.
And what does that do for thecandidate?
But it takes away that blackhole.
Because how many times have youheard, and you've seen this on
Glassdoor, you've seen it onComparably, and all these other
places where candidates canleave reviews, is that they feel
like they're not important.
There's a black hole, they applyand never hear anything.
(13:19):
So now you're getting rid ofthat feedback.
You're saying, we're gonna takethat away because now we've
given you an opportunity toactually be screened by somebody
and get assessed.
And I think the technology isgoing to advance and give
candidates an opportunity toeven maybe forego recruit
resumes, and maybe we can startum giving agents an opportunity
to give feedback, right?
(13:40):
So like they can say, I canapply for a job, or I go to
apply for a job, and this issomebody, this isn't my idea.
Somebody told me this, that thisis their idea.
They want to be able to applyfor a job and instead of a
resume, talk to an agent andsay, and the agent asks dynamic
questions, right?
And then I can ask the agentquestions, and at the end of my
conversation, the agent canhonestly tell me, hey, that you
(14:02):
applied for this job, and basedon what you've shared today,
you're about a 75% fit.
We have 30 other candidates whoare a hundred percent fit.
We don't think this job is rightfor you, but why don't you keep
looking and we'll serve you upother jobs that might be a
better fit for you based on whatyou shared today?
Like I think that's where theirtechnology is going, and I think
candidates are going to be moreand more appreciative that we're
(14:24):
giving them an opportunity tonot just share about their
experience, but get feedback onwhy they are fit for this role
or why they may not be the bestfit for this role.
SPEAKER_02 (14:33):
Yeah, well, you know, I would say I think that's
a great parallel to you knowwhat we're seeing in the
evolution of you know SEO.
And so, you know, the way I'vebeen explaining it lately is you
know, you think about you knowhow people use Google, it's you
know you're essentially yellinginto a search engine.
It's you know, jobs near me,it's pizza restaurants.
And you know, great, that's youknow, and and websites have been
(14:56):
built to optimize for shortkeywords that they want to
capture.
And you know, because of that,you have all these content farms
where you know everyone'swriting you know, 500 blog posts
about pizza restaurants or jobs.
And you know, the whole goal iswe want to make sure that we're
showing up higher on Google andyou know getting on the first
page or second page with links.
(15:16):
And I think you know, what youknow AI is kind of injecting in
here, you know, with generativesearch becoming more important,
people you know, using Chat GPTand Gemini, you know, is you
know, you're havingconversations with a chat, you
know, with a uh generativesearch agent, an LLM, and it is
much more like the scenario thatyou just described, Yvette.
And it's you know, hey, I, youknow, I'm looking for, I'm a you
(15:41):
know, I'm a nurse with fiveyears of experience.
I move into the Dallas FortWorth area.
Here's where my credentials are.
I'm looking for a company thathas, you know, has leadership
opportunities, you know, and orcontinuing education benefits
and you know, great work-lifebalance where I won't have to
work weekends.
And like people can have aliteral conversation like that
with ChatGPT, with Gemini, andit will pop out, you know,
(16:05):
employers that you know fit thatmatch are looking for those
types of candidates or providethose types of you know
benefits.
And I think the challenge is youknow, companies are having to
evolve their search strategy tomake sure that they have the
content or the context that youknow match those deep
conversations that you knowcandidates want to have.
(16:25):
And so I think the scenario thatyou just described is you know
what we're kind of seeing playout in real time in generative
search.
And now instead of racing foryou know keywords in the first
page on Google, you know, wehave companies that are racing
to make sure that all the goodthings that they are known for,
or all the good reasons whypeople should go work for an
(16:46):
organization, you know, we haveto go fight for real estate in
LLMs and generative searchmodels, right?
And so I think we're not faroff, uh maybe not far off as a
stretch, but I think we're Ithink we're progressing towards
you know the state that you kindof described, Yvette.
And like I hope we get there.
Because again, like I think youknow it's it's a similar
(17:07):
challenge where you know Googlesearch has gotten a bit gummed
up with, you know, it's too manypeople trying to fight for links
on page one.
And I think it's probably asimilar standpoint when it looks
at you know how easy it's gottento apply to jobs and you know,
integrate applies everywhere,and I can open up a requisition
and I get a hundred applicationsin a day, sure, but how many of
(17:28):
them are the right people?
So I, you know, I can see thependulum swinging back towards
the candidate, you know, in afew different ways with the you
know, call it a the assist of umof AI.
SPEAKER_03 (17:40):
I completely agree with you.
And I and I think we are headedin that direction, Graham.
And I would agree with you thatit is in the best interest of
the candidate.
And I think that's whyrecruitment marketing is so
important.
I think that making sure thatemployers are marketing why,
what's that employee valueproposition?
What are you promising to yourpotential employers and making
it authentic and genuine?
And because that's ultimatelywhat candidates are doing,
(18:02):
especially today in the duringthe era of the great stay,
right?
Like they're not gonna make amove unless they really feel
like you're gonna give them whatthey have, what they're looking
for.
SPEAKER_02 (18:11):
Yeah, yeah.
No, I completely agree.
Well, I want to talk a littlebit more about you know the
realities of AI implementations.
You know, I think it's a greatsegue.
So, you know, I think yourecently presented, uh, it might
have been two, three weeks agoat this point at LinkedIn Talent
Connect.
I think you're presenting withDavid Barr about you know using
AI to personalize talentengagement.
And I know that's kind of anarea that's near and dear to
your heart.
(18:31):
You know, I'm curious, you know,let's talk about what's actually
working from a talent engagementstandpoint.
Where is where do you see kindof AI delivering value in your
recruitment process?
Not just, you know, wherevendors promise it you know is
gonna work, but where where areyou personally seeing measurable
improvement with you know withAI?
SPEAKER_03 (18:49):
Yeah, I I think AI has been most valuable in
specific repeatable parts ofrecruiting.
Um the biggest wins I've seenare in the areas of things like
personalized engagement.
So AI allows us to nurturepassive talent at scale with
textual messaging, oftendoubling engagement versus that
generic outreach.
(19:10):
Screening and scheduling, alsoanother area where we've seen
AI.
I know talked about voice agentsand chatbots, but that
dramatically reduces admin work.
I mean, one team can cut time toscreen by over 60% by
implementing a voice agent or achat bot.
And then the other area whereI've seen some big wins is in
the predictive insights side.
(19:31):
Uh, talent insights helpsforecast hiring needs as well as
spot the market disruptions.
So teams can source proactivelyversus reactively, which is what
you want your teams to do.
I mean, that's what we're goingtowards that model of is being
more proactive, reaching thepaths of talent, but we have to
give them some triggers, likewhere should we go first?
(19:51):
Like, um kind of like a bullseyeapproach.
Let's start here and then fanourselves out.
And then I do think that thereare some areas where there's
still opportunity for AI.
I think that there's been somedisappointment around the
integration.
I think it's still a majorchallenge because even great
tools lose value when they don'tplay well with legacy systems or
they disrupt the recruiterworkflow.
(20:13):
That's why I think it's soimportant to do the front-end
work, which is that recruiterworkflow analysis, and then
identify what tool what toolmakes the most sense before you
just go buy the tool and try toimplement it.
SPEAKER_02 (20:24):
Yeah, well, I I've always said, you know,
integration is the most poorlyused word in in HR tech.
And you know, I stand by thattoday.
I do think that I think it'sgotten better, it's gotten
easier, and you know,integration doesn't uh scare as
many people, you know, but youknow, integration doesn't mean
you know, provides a link to ajob posting.
That's you know, it's a verydifferent integration, I think,
(20:46):
what people would truly mean.
So I I guess I'd say a harderquestion than, you know, where
would you say AI has kind ofdisappointed you the most?
Is it in that integration area?
SPEAKER_03 (20:56):
Yeah, I think so.
In the integration, that and Ithink the other area would
probably be um the oversellingfrom vendors.
You know, it's it's comical tothink about it, but like when
you do a vendor demo, they showyou every bell and whistle.
And I think, Graham, one of thethings that I have noticed is
that integration, it's it's moreused today.
You're right, it was anunderused word, but it's more
(21:18):
used today.
But I think vendors are so quickto say, yeah, we can integrate,
no problem.
Open API, no problem.
And then when the rubber hitsthe road, it's like, oh no, not
so much, not so not as seamlessas we thought it was going to
be.
So I think that that's where Ithere's still some challenges.
SPEAKER_02 (21:34):
Yeah, well, I I think the bigger challenge, and
we see this just in the newseverywhere, is like everyone is
being tasked to, you know, usethe AI somehow.
And I think that there are a lotof vendors that are taken
advantage of that fact, right?
And you know, when we go throughour practices, it's you know,
sure, like you can use AI, andlike, you know, everyone can go
by a Gartner report and you knowfigure out that, yep, they
(21:55):
aren't using AI enough, or theyshould use it in employer brand
or in their process.
But you know, the bigger problemis doing the work to map out you
know where and why, and youknow, more importantly, probably
what problems you're gonnasolve, you know, how much time
it's taking to do X, Y, and Z.
And like if we're gonnaprioritize AI to you know
something as simple as automatescheduling, right?
(22:16):
Or you know, screen outcandidates that you know simply
don't live in the US.
You know, I think that there area lot of you know low-hanging
fruit areas, and and I think waytoo often you know, companies
jump to the you know, the holygrail, we're gonna buy acts
system if it's going to findcandidates and deliver the top
three that are alreadypre-screened and and ready to
(22:37):
start tomorrow.
And I think the reality is youknow somewhere in between,
right?
And I think we need to sometimesmaybe admit that there's some
limitations to where we wanna umwhere we want to start.
But hey, we're not a vendoranymore.
SPEAKER_03 (22:48):
So this is a great and sometimes admit this isn't
this product doesn't doeverything you need it to do,
right?
Like it does 80% of what youwant it to do, and we can work
on that last 20% if you help us.
Like, let's be a partner inthis.
I think vendors shouldn't beafraid to say that, but they are
so afraid to say that becausethey're afraid they're gonna
lose the deal.
(23:09):
But ultimately, if you end upwith a product that doesn't get
adopted because it doesn't doeverything we thought it was
going to do, then everybodyloses.
So I think that's one of theareas a vendor should probably
be a little bit more open to.
SPEAKER_02 (23:21):
Well, I'm I'm reminded of uh an old boss of
mine who said, you know, he wassitting in vendor demos and you
know it was who knows?
We'll say it was with bullhorn,you know, and and then bullhorn
sales rep was promising themcould do X, it could do Y, it
could do Z, you know, and andthen one guy, you know, at
Bullhorn said, Well, no, no, no,no.
It actually it can't do Z.
And you know, sales rep kind ofcut him off, said, No, it could
(23:43):
do it.
And you know, remember our oldboss said, No, that's the guy I
want in the room every time.
The guy that tells me what itcan't do.
And we can, you know, we can do,you know, if we could do seven
out of ten things, that's stillbetter than you know, than than
where we're at today, you know,but we'd rather do seven things
well, you know, than thanoverpromise at uh at this point.
And so I think there's a lot ofvalue in boy, transparency and a
(24:07):
vendor agnostic sort of lens to,you know, hey, if it doesn't do
everything, that's okay.
Let's just make sure they can doall the things that we're
seeing.
SPEAKER_03 (24:14):
Absolutely.
SPEAKER_02 (24:14):
Well, one thing you shared on LinkedIn, and I'm
gonna paraphrase it and get itclose to right, is you know, in
your world, you think AI canenhance creativity and not, you
know, not replace it.
And you know, I think that youknow, your point was it's uh
it's a reminder that technology,if if it's used kind of
thoughtfully, can amplify ourhumanity rather than diminish
it, right?
And and I think that you knowthat's probably a different
(24:37):
framing than you know most of usare seeing and hearing at
conferences.
You know, many vendors areselling efficiency and
automation, but you are kind oftalking about you know humanity
and belonging.
And you know, I know it'sliterally in many of your
titles, right?
And so maybe walk me through howthat philosophy you know shows
up in your shows up in yourwork.
SPEAKER_03 (24:58):
Yeah, I think um I've always believed that
technology should expand ourcapacity for connection, not
replace it.
So AI is most powerful when wecan remove friction, not
feeling, and create a space forthe work only humans can do.
And that is practice empathy,tell our story and our brand,
and express belonging.
So I think that that's reallyimportant.
(25:20):
The philosophy can guide youthrough implementation with AI
is looking at the design ofeverything.
So start starting with themoments that matter, like
improving candidate feedback,looking at the recruiter
workload, or even a new hire'sfirst day, and then making sure
that you have open communicationwith your team, framing AI as
giving recruiters time back forreal conversations, maybe
(25:43):
elevating their role to a talentadvisor, or there's a new term,
talent agent, or talent businesspartner, whatever term you want
to use.
But it's not really to replacethem, it's really to elevate
their role.
And then, of course, culture,because I think about AI
technology and I think about theprompts that we're using.
So prompts and chat flows shouldstill really reflect empathy and
(26:03):
inclusion because those smalldetails scale culture.
So when I think about that, it'slike we have to really think
about how it's making theexperience more human at scale.
And AI should amplify ourculture and not replace it, and
it shouldn't just be about thespeed, if that makes sense.
SPEAKER_02 (26:24):
Yeah, yeah.
No, I think it totally does.
And I think like, you know, evensome of the examples of you
know, where we're going withgenerative search, I think, you
know, for the rightorganizations that you know
implemented or action correctly,like, you know, AI and and LLM
and generative search is goingto give us a chance to share our
stories and share our culture alot more broadly and a lot more
deeply than you know, youtypically would get in, you
(26:46):
know, Arg at least, you know,SEO that would you know maybe
penalize or reward the wrongplayers in that space too.
So I think I'm I think we're ina in a very interesting spot in
kind of bridging that gapbetween you know humanity and
and technology and you know, andusing that to really shine the
light on you know more deeperstories within organizations and
cultures as a whole.
(27:08):
Well, talk to me about you knowa TA leader, you know, sitting
in their office then right now,Yvette.
We've talked a lot about AI.
I think a lot of executives aregetting 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 knowparalysis around not knowing
(27:29):
where to start.
And so, you know, if you hadsome advice for you know the
overwhelmed TA leader, you know,that's sitting there getting
pressure from the C-suite to dosomething with AI, you know,
what's what's one piece ofadvice you'd give to you know a
town acquisition leader today?
What would that be?
SPEAKER_03 (27:43):
Yeah, my one piece of advice would be to start
small, measure fast, and designfor adoption, not perfection.
So don't go in trying tooverhaul your whole tech stack
at once.
Pick one pain point that'smeasurable, like screening or
candidate engagement.
And prove the value there first.
(28:04):
Build trust with your recruitersearly, because that's key to
adoption, by being transparentabout what the tool does and
doesn't do to our point earlier.
Make adoption a KPI.
Because at the end of the day,you can buy the best AI on the
market.
But if your team doesn't trustit or it doesn't fit the
workflow, you'll never see theROI.
(28:24):
So the most successful pilotsI've led, I didn't consider tech
projects.
I considered them changemanagement initiatives that were
focused on helping people thatwork smarter, not differently.
SPEAKER_02 (28:35):
Yeah, I think that's great.
Well, I think that's a goodplace for us to close.
I got a couple quick hit, quickhits for you, If that.
So, you know, first one, it'scontrarian take time.
So, you know, what's your mostcontrarian prediction about
talent acquisition technology?
You know, what's what'ssomething that ever thinks is
gonna happen that you mightdisagree with?
SPEAKER_03 (28:52):
I think that the future of TA isn't about more
automation.
It's gonna be about morecuration and connection.
I think everyone assumes AI isgonna replace recruiters, but I
think the real advantage isgonna come from teams who use it
to deepen human connection.
I think automation is at thisday and age, it's table stakes.
Trust and personalization willbe the true different
(29:13):
differentiators.
I think the next phase won't beabout who has the most tools.
It's gonna be about who usesthem most intentionally to make
the experience feel more human,transparent, and authentic.
SPEAKER_02 (29:25):
All right, I like that.
Okay, well, the last questionthat I ask everyone is so what
are you reading or listening todo these days?
And you know, how are youlearning and staying ahead of
this curve?
SPEAKER_03 (29:34):
Yeah, so I listen to a lot of podcasts.
Um, one of my favorites isAstra, which is the American
Society for Healthcare HumanResources Administration.
So it hits close to home andit's a if they're quick listens.
I think they're like 25, 30minute listens.
I I'll listen to them while I'mlifting or running or something.
It's a podcast that's hosted byLuke Kerrigan and Bo Brabo, and
(29:56):
they have such a diverse mix ofhealthcare leaders that share
their experiences, theirSuccesses and my favorite
they're lessons learned becausewhy make the mistake if you
don't have to if you can learnfrom someone else?
SPEAKER_02 (30:07):
I know Luke Kerrigan.
He used to work at CareerBuilder.
Is he a Phenom?
I think he was at Phenom for awhile.
SPEAKER_03 (30:13):
He's at Phenom now, yes.
SPEAKER_02 (30:15):
You know what?
I don't know if Luke'slistening, but like I hired, I
tried to hire Luke for a salesengineering job probably 15
years ago at this point, and hehad a better job offer.
But he's very uh always a bigfan of Luke.
So yeah, I I know him very well.
SPEAKER_03 (30:32):
Yeah, he's fantastic.
He's so personable, and like Isaid, his podcast is awesome.
SPEAKER_02 (30:37):
Oh, that's great.
Well, Luke, or tag you in thisone for sure.
Um, big fan.
So oh that's great.
Okay, well, last question.
We'll list everything.
Um, we'll link out to yourLinkedIn profile for sure,
Yvette.
But you know, for folks thatwant to connect with you or
follow your work, you know,where should they find you?
SPEAKER_03 (30:54):
So obviously LinkedIn, but you can always
reach out to me at evet atevethanson.com.
SPEAKER_02 (31:00):
Awesome.
Love it.
Well, we'll link that in theshow notes, uh, your email, your
LinkedIn.
Um, and again, it's been a greatconversation.
So really appreciate you joiningus.
SPEAKER_01 (31:08):
Thank you so much for having me.
All right, thanks for tuning in.
As always, head on over tochangestate.io or shoot us a
note on all the social media.
We'd love to hear from you, andwe'll check you guys next week.
Welcome to the Changing State of Talent
Acquisition podcast with yourhost, Graham Thornton.
Each episode brings youunfiltered conversations about
the tools, trends, andtechnologies impacting the
future of talent acquisition.
Our guests share their storieson what's working, what's hype,
and what's actually helpingcompanies hire better and grow
(00:21):
faster.
Have feedback or want to jointhe show?
Head on over to Tollibity.com tolearn more.
But now we're on to this week'sepisode.
SPEAKER_03 (01:29):
And that really started as a foundation that
shaped everything because itreally taught me how deeply the
hiring process affects bothcandidates and hiring teams.
I would get letters and cardsthat's back before email was
very popular from candidatesabout how this was affecting
their family, not just a job.
So I realized quickly that itwasn't really about filling a
(01:50):
job or filling a role.
It was really about how I wasmaking people feel.
And that really was a turningpoint for me because it really
made me look at the entireprocess end to end and made me
realize that there wasbottlenecks in the process about
where people, it wasn't aboutpeople working harder.
It was really about workflowsand technology.
(02:12):
If we really wanted to affectchange and how we were helping
candidates, it was really goingto be about what workflow made
the most sense to reach thecandidate where they are in that
moment and what when when didthat moment really matter?
So it really led me intosourcing, uh, recruitment
marketing, and ultimatelybuilding TA infrastructures.
So I've done everything fromstanding up sourcing and
(02:33):
branding teams, depleming CRMs,automation and AI.
And that's really allowed me toblend innovation with empathy,
like I said, reallyunderstanding the candidate,
launching automation and AIprograms that made hiring both
faster and more human.
And today my focus is on theintersection of AI, ethics, and
belonging.
So building systems that areefficient, fair, but also
(02:55):
reflective of the people thatthey serve.
So I'm essentially interested inhow TA can evolve from that
transactional functional thatwe've seen it be to a true
intelligence engine that'spredicting needs, that engages
the passive talent, and shapesorganizational readiness.
SPEAKER_02 (03:19):
And I think that your you know your background
really kind of leans into thehuman and uh in human resources
too.
You know, before we get started,you know, more deeply on the
humanity aspect and you knowconnecting humanity and
technology, you know, youmentioned in our pre-call that
you know you've worked withrecruitics for about 15 years,
and you know, I would say from apartnership standpoint, you
(03:42):
know, that's a pretty longvendor relationship in this
industry.
You know, many partnershipsoften you know kind of flame out
after a handful of years, youknow, an implementation and the
honeymoon period ends.
You know, I'm just curious, froma partnership lens, you know,
what's made your partnershipswith Recruitics last?
SPEAKER_03 (03:58):
You're right.
I will say, Graham, a 15-yearvendor relationship is rare and
TA.
Um I think it works because therelationship with Recruittics
was never transactional.
No matter what organization Iwas with, because I've worked
with Recruits in multipleorganizations, it really became
an extension of whatever team Iwas on.
So we shared goals, data,challenges, and they gave us
(04:19):
full transparency into theirroadmap so we could co-create
solutions.
I think back to when Ioriginally started working with
them, and the focus was reallyabout programmatic distribution
and basic campaign tracking.
But that partnership evolvedinto full funnel analytics, UTM
and attribution modeling,competitive insights.
They even advised on emergingtech and AI use cases, which was
(04:40):
really beneficial as we startedto dip our toe in that world.
And then my work started toexpand into talent intelligence,
market disruption analysis, andof course, AI strategy.
And what I loved aboutrecruitics is they were willing
to evolve right alongside thatwork.
Ultimately, the longevity camefrom aligning on outcomes and
not deliverables.
And as we both know, or anybodywho's in this industry knows,
(05:02):
recruitment marketing isn'tstatic.
It shifts with the labor market,technology, of course, our
brands, and they grow with youat every step of the way.
Ultimately, our work was builton trust and shared learning and
continuous innovation, and itwasn't just about the contract
at the end of the day.
SPEAKER_02 (05:18):
Yeah, no, I think that's great.
And I think you know, therecruitment marketing and
recruitment landscape in a genin general continues to evolve.
You know, we've done a call,well, probably a half dozen
calls just this week talkingabout boy, like what's the
future of SEO?
And, you know, are we going tocoin this new phrase geo,
generative search optimization,and you know, and pushing back
and like, hey, the reality is,you know, it's recruitment
(05:41):
marketing is just evolved fromnewspapers to job boards to you
know programmatic advertisingand you know, social media and
you know, Google ads, but at theend of the way, end of the day,
it's still recruitmentmarketing.
And I think you know, we'reseeing a similar path with you
know search engine optimization.
You know, generative search isjust a new search engine.
So we're still optimizing searchfor you know AI search for chat
(06:04):
GPT for Gemini and you know,whatever, I'll get off my
soapbox.
So, you know, that I think thatis a pretty good segue into you
know what I want to talk about.
And you know, you know, let'stalk a little bit more about
healthcare, maybe morespecifically.
So, you know, you spent yourentire career in health systems,
whether it's United Health, youknow, Optum, you know, Baylor,
(06:24):
Scott, and white, you know, Ithink that it's probably easy to
say healthcare is notoriouslychallenging, you know, high
volume, tight labor markets, youknow, clinical roles from some
very, very specific credentials,you know, maybe compliance
complexity, we can go on and on.
You know, I'm curious, you know,from you know, from a healthcare
lens, you know, how did some ofyou know maybe your healthcare
(06:45):
constraints shape how you thinkabout technology adoption?
You know, I can imagine that,you know, you know, when you're
in healthcare, you can't justimplement any new flashy tool
that comes your way.
So, you know, are you seeinghealthcare lag, lead when it
comes to technologyimplementation, maybe AI
adoption and recruiting?
SPEAKER_03 (07:02):
You know, that's a really great question.
And I do believe healthcare usedto lag in tech adoption.
I don't believe that's true anylonger.
I would dare to say that in thelast few years, health systems
have moved to the front of thepack, leading the industry in
responsible, human-centered AIacross town engagement,
forecasting, and workflowautomation.
But you are absolutely alsoright in the fact that
(07:24):
healthcare is a very uniqueanimal.
You've got high volume, highstakes, deeply regulated.
So, of course, we can't chaseevery shiny new tool that comes
in front of us.
Every tech decision has to betied back to compliance,
scalability, and ultimatelypatient care.
So when I think about that, itreally forced me into a process
(07:46):
first, a problem first mindset.
And when I what I mean when Isay that is I map out the
workflow.
I find the friction points, thegaps, um, the pain points,
whatever you want to call it.
And then you choose thetechnology that actually
improves the experience in thatspace, whether it's recruiters,
hiring managers, candidatesthemselves, and you really look
(08:10):
for a goal that introduces AI inpurposeful ways.
So is it going to automate thescreening and scheduling?
Are you using it for predictiveinsights to engage passive
talent?
Are you freeing recruiters to dohigher value work?
You basically want to automatefor efficiency, but that
shouldn't be the only goal.
The goal should really be aboutimproving the candidate and the
(08:31):
patient in experience.
And I think that's whathealthcare is focusing on right
now.
The industry as a whole islooking at that today.
SPEAKER_02 (08:37):
Yeah.
So, you know, maybe a good quitegood place to start then is like
in your world, where did youfirst start experimenting then
with AI and recruiting?
Was it, you know, was it more inthe, hey, we're trying to
automate X, Y, and Z, or wasthere a particular moment in
time when you said, boy, youknow, this is going to change
how we work, you know, we needto, you know, we need to set up
X now?
SPEAKER_03 (08:59):
Yeah, that's a that's a really great question.
And I'm thinking back to whatwas my real, my first real
exposure to AI?
And I, and if I think back, itprobably was right around 2018
when everybody started exploringconversational bots and
automation within their CRMtechnology.
And I think back then most of ussaw AI as a way to speed up
administrative work, right?
(09:19):
Like scheduling and screeningand follow-ups and like
reminders on our like theseautomatic reminders and things
like that.
Nobody really saw them as gamechangers.
I think the moment that changedfor me was during a it was
recent actually.
It was during a pilot that I wasleading using an AI voice agent
to conduct the first roundcandidate screens.
(09:40):
And it was, it was a really, itwas really eye-opening because
within a few weeks the systemhad processed hundreds of
applicants, not just processedand interviewed them, but it
assessed them and scored them.
And one of the surprises that umI found in reviewing the data
was the quality didn't drop, itactually improved.
We saw that candidates felt moreinformed, recruiters were
(10:01):
gaining hours back in their day,hiring managers were getting
better shortlists of candidatesfaster, and it was making them
more happy.
So it was the real it was thatmoment that I realized this
isn't incremental, thisfundamentally changes how we
work.
And so what I what I realizedthen is that AI is not a
plug-in.
It has to be treated as part ofthe core recruiting
(10:22):
infrastructure, something thatwe could connect the entire
talent journey on.
So from attraction to alumni.
So even in the employee journeyitself, when you think about the
employee journey, it reallyshould start from the attraction
perspective all the way toalumni.
And I do believe AI is going tobe core in making sure that we
can tie it all together.
SPEAKER_02 (10:42):
Yeah, so Yvette, I think that's a really
interesting piece.
And you know, I wonder if wecould unpack that a little bit
more.
So, you know, I think we hear alot that, you know, for the last
however many months and years,that you know, people are afraid
that AI is going to get itwrong, AI is gonna take our jobs
and and whatnot.
But you know, I think in yourexample you said, you know, hey,
like you found that you know AIrunning, I'll say, you know,
(11:05):
almost first-round interviews orscreenings with candidates did a
on par or better job inservicing and you know, and
screening out and identifyingthe right candidates.
And you know, I think a fewyears ago, or you know, maybe a
year ago, we heard you know,that hey, candidates are fine
with AI getting them furtheraround in the process, you know,
(11:27):
as long as it's a you know apersonalized experience, right?
And they don't feel like youknow, they're just being passed
on to a you know to a bot and toan agent.
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 popup.
But if it can get me my answerto my question faster, I'm okay
with that.
You know, are you kind of seeinga similar balance play out with
(11:48):
our you know AI sort ofscreening and interviewing
tools?
You know, given maybe it's ahey, a high volume of candidates
are coming through.
Hey, if I'm you know a qualifiedcandidate, you know, I'm more
than happy to engage with an AIgenerated interview if it's
going to help me advance throughthe process faster.
Is that kind of what you're umseeing from a balance, or am I
(12:09):
you know making a bit of a leap?
SPEAKER_03 (12:11):
Oh no, no, no, Graham.
That's exactly what we'reseeing.
I I think today I look at AI asthat bridge between efficiency
and empathy.
It it frees up the ability tofocus on the human moments that
really matter and think aboutwhat a human moment that really
matters is.
When a candidate applies for ajob, and if there if it's a high
volume role where you'regetting, let's say, a hundred
candidates a day, maybe, maybemore even, um, a recruiter does
(12:36):
not have the time to lookthrough that many applicants.
So historically, the recruiterwill go through the most
current, the applicants thatappear to be the best fit, who
applied the soonest, or maybethe first ones who applied, but
they don't get them all.
Now, an agent can come in andscreen every single applicant.
So, what does that do for therecruiter?
It obviously gives them, servesthem up the best of all the
(12:56):
applicants who applied, not justthe ones they were able to get
connected with within thetimeframe that they had.
And what does that do for thecandidate?
But it takes away that blackhole.
Because how many times have youheard, and you've seen this on
Glassdoor, you've seen it onComparably, and all these other
places where candidates canleave reviews, is that they feel
like they're not important.
There's a black hole, they applyand never hear anything.
(13:19):
So now you're getting rid ofthat feedback.
You're saying, we're gonna takethat away because now we've
given you an opportunity toactually be screened by somebody
and get assessed.
And I think the technology isgoing to advance and give
candidates an opportunity toeven maybe forego recruit
resumes, and maybe we can startum giving agents an opportunity
to give feedback, right?
(13:40):
So like they can say, I canapply for a job, or I go to
apply for a job, and this issomebody, this isn't my idea.
Somebody told me this, that thisis their idea.
They want to be able to applyfor a job and instead of a
resume, talk to an agent andsay, and the agent asks dynamic
questions, right?
And then I can ask the agentquestions, and at the end of my
conversation, the agent canhonestly tell me, hey, that you
(14:02):
applied for this job, and basedon what you've shared today,
you're about a 75% fit.
We have 30 other candidates whoare a hundred percent fit.
We don't think this job is rightfor you, but why don't you keep
looking and we'll serve you upother jobs that might be a
better fit for you based on whatyou shared today?
Like I think that's where theirtechnology is going, and I think
candidates are going to be moreand more appreciative that we're
(14:24):
giving them an opportunity tonot just share about their
experience, but get feedback onwhy they are fit for this role
or why they may not be the bestfit for this role.
SPEAKER_02 (14:33):
Yeah, well, you know, I would say I think that's
a great parallel to you knowwhat we're seeing in the
evolution of you know SEO.
And so, you know, the way I'vebeen explaining it lately is you
know, you think about you knowhow people use Google, it's you
know you're essentially yellinginto a search engine.
It's you know, jobs near me,it's pizza restaurants.
And you know, great, that's youknow, and and websites have been
(14:56):
built to optimize for shortkeywords that they want to
capture.
And you know, because of that,you have all these content farms
where you know everyone'swriting you know, 500 blog posts
about pizza restaurants or jobs.
And you know, the whole goal iswe want to make sure that we're
showing up higher on Google andyou know getting on the first
page or second page with links.
(15:16):
And I think you know, what youknow AI is kind of injecting in
here, you know, with generativesearch becoming more important,
people you know, using Chat GPTand Gemini, you know, is you
know, you're havingconversations with a chat, you
know, with a uh generativesearch agent, an LLM, and it is
much more like the scenario thatyou just described, Yvette.
And it's you know, hey, I, youknow, I'm looking for, I'm a you
(15:41):
know, I'm a nurse with fiveyears of experience.
I move into the Dallas FortWorth area.
Here's where my credentials are.
I'm looking for a company thathas, you know, has leadership
opportunities, you know, and orcontinuing education benefits
and you know, great work-lifebalance where I won't have to
work weekends.
And like people can have aliteral conversation like that
with ChatGPT, with Gemini, andit will pop out, you know,
(16:05):
employers that you know fit thatmatch are looking for those
types of candidates or providethose types of you know
benefits.
And I think the challenge is youknow, companies are having to
evolve their search strategy tomake sure that they have the
content or the context that youknow match those deep
conversations that you knowcandidates want to have.
(16:25):
And so I think the scenario thatyou just described is you know
what we're kind of seeing playout in real time in generative
search.
And now instead of racing foryou know keywords in the first
page on Google, you know, wehave companies that are racing
to make sure that all the goodthings that they are known for,
or all the good reasons whypeople should go work for an
(16:46):
organization, you know, we haveto go fight for real estate in
LLMs and generative searchmodels, right?
And so I think we're not faroff, uh maybe not far off as a
stretch, but I think we're Ithink we're progressing towards
you know the state that you kindof described, Yvette.
And like I hope we get there.
Because again, like I think youknow it's it's a similar
(17:07):
challenge where you know Googlesearch has gotten a bit gummed
up with, you know, it's too manypeople trying to fight for links
on page one.
And I think it's probably asimilar standpoint when it looks
at you know how easy it's gottento apply to jobs and you know,
integrate applies everywhere,and I can open up a requisition
and I get a hundred applicationsin a day, sure, but how many of
(17:28):
them are the right people?
So I, you know, I can see thependulum swinging back towards
the candidate, you know, in afew different ways with the you
know, call it a the assist of umof AI.
SPEAKER_03 (17:40):
I completely agree with you.
And I and I think we are headedin that direction, Graham.
And I would agree with you thatit is in the best interest of
the candidate.
And I think that's whyrecruitment marketing is so
important.
I think that making sure thatemployers are marketing why,
what's that employee valueproposition?
What are you promising to yourpotential employers and making
it authentic and genuine?
And because that's ultimatelywhat candidates are doing,
(18:02):
especially today in the duringthe era of the great stay,
right?
Like they're not gonna make amove unless they really feel
like you're gonna give them whatthey have, what they're looking
for.
SPEAKER_02 (18:11):
Yeah, yeah.
No, I completely agree.
Well, I want to talk a littlebit more about you know the
realities of AI implementations.
You know, I think it's a greatsegue.
So, you know, I think yourecently presented, uh, it might
have been two, three weeks agoat this point at LinkedIn Talent
Connect.
I think you're presenting withDavid Barr about you know using
AI to personalize talentengagement.
And I know that's kind of anarea that's near and dear to
your heart.
(18:31):
You know, I'm curious, you know,let's talk about what's actually
working from a talent engagementstandpoint.
Where is where do you see kindof AI delivering value in your
recruitment process?
Not just, you know, wherevendors promise it you know is
gonna work, but where where areyou personally seeing measurable
improvement with you know withAI?
SPEAKER_03 (18:49):
Yeah, I I think AI has been most valuable in
specific repeatable parts ofrecruiting.
Um the biggest wins I've seenare in the areas of things like
personalized engagement.
So AI allows us to nurturepassive talent at scale with
textual messaging, oftendoubling engagement versus that
generic outreach.
(19:10):
Screening and scheduling, alsoanother area where we've seen
AI.
I know talked about voice agentsand chatbots, but that
dramatically reduces admin work.
I mean, one team can cut time toscreen by over 60% by
implementing a voice agent or achat bot.
And then the other area whereI've seen some big wins is in
the predictive insights side.
(19:31):
Uh, talent insights helpsforecast hiring needs as well as
spot the market disruptions.
So teams can source proactivelyversus reactively, which is what
you want your teams to do.
I mean, that's what we're goingtowards that model of is being
more proactive, reaching thepaths of talent, but we have to
give them some triggers, likewhere should we go first?
(19:51):
Like, um kind of like a bullseyeapproach.
Let's start here and then fanourselves out.
And then I do think that thereare some areas where there's
still opportunity for AI.
I think that there's been somedisappointment around the
integration.
I think it's still a majorchallenge because even great
tools lose value when they don'tplay well with legacy systems or
they disrupt the recruiterworkflow.
(20:13):
That's why I think it's soimportant to do the front-end
work, which is that recruiterworkflow analysis, and then
identify what tool what toolmakes the most sense before you
just go buy the tool and try toimplement it.
SPEAKER_02 (20:24):
Yeah, well, I I've always said, you know,
integration is the most poorlyused word in in HR tech.
And you know, I stand by thattoday.
I do think that I think it'sgotten better, it's gotten
easier, and you know,integration doesn't uh scare as
many people, you know, but youknow, integration doesn't mean
you know, provides a link to ajob posting.
That's you know, it's a verydifferent integration, I think,
(20:46):
what people would truly mean.
So I I guess I'd say a harderquestion than, you know, where
would you say AI has kind ofdisappointed you the most?
Is it in that integration area?
SPEAKER_03 (20:56):
Yeah, I think so.
In the integration, that and Ithink the other area would
probably be um the oversellingfrom vendors.
You know, it's it's comical tothink about it, but like when
you do a vendor demo, they showyou every bell and whistle.
And I think, Graham, one of thethings that I have noticed is
that integration, it's it's moreused today.
You're right, it was anunderused word, but it's more
(21:18):
used today.
But I think vendors are so quickto say, yeah, we can integrate,
no problem.
Open API, no problem.
And then when the rubber hitsthe road, it's like, oh no, not
so much, not so not as seamlessas we thought it was going to
be.
So I think that that's where Ithere's still some challenges.
SPEAKER_02 (21:34):
Yeah, well, I I think the bigger challenge, and
we see this just in the newseverywhere, is like everyone is
being tasked to, you know, usethe AI somehow.
And I think that there are a lotof vendors that are taken
advantage of that fact, right?
And you know, when we go throughour practices, it's you know,
sure, like you can use AI, andlike, you know, everyone can go
by a Gartner report and you knowfigure out that, yep, they
(21:55):
aren't using AI enough, or theyshould use it in employer brand
or in their process.
But you know, the bigger problemis doing the work to map out you
know where and why, and youknow, more importantly, probably
what problems you're gonnasolve, you know, how much time
it's taking to do X, Y, and Z.
And like if we're gonnaprioritize AI to you know
something as simple as automatescheduling, right?
(22:16):
Or you know, screen outcandidates that you know simply
don't live in the US.
You know, I think that there area lot of you know low-hanging
fruit areas, and and I think waytoo often you know, companies
jump to the you know, the holygrail, we're gonna buy acts
system if it's going to findcandidates and deliver the top
three that are alreadypre-screened and and ready to
(22:37):
start tomorrow.
And I think the reality is youknow somewhere in between,
right?
And I think we need to sometimesmaybe admit that there's some
limitations to where we wanna umwhere we want to start.
But hey, we're not a vendoranymore.
SPEAKER_03 (22:48):
So this is a great and sometimes admit this isn't
this product doesn't doeverything you need it to do,
right?
Like it does 80% of what youwant it to do, and we can work
on that last 20% if you help us.
Like, let's be a partner inthis.
I think vendors shouldn't beafraid to say that, but they are
so afraid to say that becausethey're afraid they're gonna
lose the deal.
(23:09):
But ultimately, if you end upwith a product that doesn't get
adopted because it doesn't doeverything we thought it was
going to do, then everybodyloses.
So I think that's one of theareas a vendor should probably
be a little bit more open to.
SPEAKER_02 (23:21):
Well, I'm I'm reminded of uh an old boss of
mine who said, you know, he wassitting in vendor demos and you
know it was who knows?
We'll say it was with bullhorn,you know, and and then bullhorn
sales rep was promising themcould do X, it could do Y, it
could do Z, you know, and andthen one guy, you know, at
Bullhorn said, Well, no, no, no,no.
It actually it can't do Z.
And you know, sales rep kind ofcut him off, said, No, it could
(23:43):
do it.
And you know, remember our oldboss said, No, that's the guy I
want in the room every time.
The guy that tells me what itcan't do.
And we can, you know, we can do,you know, if we could do seven
out of ten things, that's stillbetter than you know, than than
where we're at today, you know,but we'd rather do seven things
well, you know, than thanoverpromise at uh at this point.
And so I think there's a lot ofvalue in boy, transparency and a
(24:07):
vendor agnostic sort of lens to,you know, hey, if it doesn't do
everything, that's okay.
Let's just make sure they can doall the things that we're
seeing.
SPEAKER_03 (24:14):
Absolutely.
SPEAKER_02 (24:14):
Well, one thing you shared on LinkedIn, and I'm
gonna paraphrase it and get itclose to right, is you know, in
your world, you think AI canenhance creativity and not, you
know, not replace it.
And you know, I think that youknow, your point was it's uh
it's a reminder that technology,if if it's used kind of
thoughtfully, can amplify ourhumanity rather than diminish
it, right?
And and I think that you knowthat's probably a different
(24:37):
framing than you know most of usare seeing and hearing at
conferences.
You know, many vendors areselling efficiency and
automation, but you are kind oftalking about you know humanity
and belonging.
And you know, I know it'sliterally in many of your
titles, right?
And so maybe walk me through howthat philosophy you know shows
up in your shows up in yourwork.
SPEAKER_03 (24:58):
Yeah, I think um I've always believed that
technology should expand ourcapacity for connection, not
replace it.
So AI is most powerful when wecan remove friction, not
feeling, and create a space forthe work only humans can do.
And that is practice empathy,tell our story and our brand,
and express belonging.
So I think that that's reallyimportant.
(25:20):
The philosophy can guide youthrough implementation with AI
is looking at the design ofeverything.
So start starting with themoments that matter, like
improving candidate feedback,looking at the recruiter
workload, or even a new hire'sfirst day, and then making sure
that you have open communicationwith your team, framing AI as
giving recruiters time back forreal conversations, maybe
(25:43):
elevating their role to a talentadvisor, or there's a new term,
talent agent, or talent businesspartner, whatever term you want
to use.
But it's not really to replacethem, it's really to elevate
their role.
And then, of course, culture,because I think about AI
technology and I think about theprompts that we're using.
So prompts and chat flows shouldstill really reflect empathy and
(26:03):
inclusion because those smalldetails scale culture.
So when I think about that, it'slike we have to really think
about how it's making theexperience more human at scale.
And AI should amplify ourculture and not replace it, and
it shouldn't just be about thespeed, if that makes sense.
SPEAKER_02 (26:24):
Yeah, yeah.
No, I think it totally does.
And I think like, you know, evensome of the examples of you
know, where we're going withgenerative search, I think, you
know, for the rightorganizations that you know
implemented or action correctly,like, you know, AI and and LLM
and generative search is goingto give us a chance to share our
stories and share our culture alot more broadly and a lot more
deeply than you know, youtypically would get in, you
(26:46):
know, Arg at least, you know,SEO that would you know maybe
penalize or reward the wrongplayers in that space too.
So I think I'm I think we're ina in a very interesting spot in
kind of bridging that gapbetween you know humanity and
and technology and you know, andusing that to really shine the
light on you know more deeperstories within organizations and
cultures as a whole.
(27:08):
Well, talk to me about you knowa TA leader, you know, sitting
in their office then right now,Yvette.
We've talked a lot about AI.
I think a lot of executives aregetting 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 knowparalysis around not knowing
(27:29):
where to start.
And so, you know, if you hadsome advice for you know the
overwhelmed TA leader, you know,that's sitting there getting
pressure from the C-suite to dosomething with AI, you know,
what's what's one piece ofadvice you'd give to you know a
town acquisition leader today?
What would that be?
SPEAKER_03 (27:43):
Yeah, my one piece of advice would be to start
small, measure fast, and designfor adoption, not perfection.
So don't go in trying tooverhaul your whole tech stack
at once.
Pick one pain point that'smeasurable, like screening or
candidate engagement.
And prove the value there first.
(28:04):
Build trust with your recruitersearly, because that's key to
adoption, by being transparentabout what the tool does and
doesn't do to our point earlier.
Make adoption a KPI.
Because at the end of the day,you can buy the best AI on the
market.
But if your team doesn't trustit or it doesn't fit the
workflow, you'll never see theROI.
(28:24):
So the most successful pilotsI've led, I didn't consider tech
projects.
I considered them changemanagement initiatives that were
focused on helping people thatwork smarter, not differently.
SPEAKER_02 (28:35):
Yeah, I think that's great.
Well, I think that's a goodplace for us to close.
I got a couple quick hit, quickhits for you, If that.
So, you know, first one, it'scontrarian take time.
So, you know, what's your mostcontrarian prediction about
talent acquisition technology?
You know, what's what'ssomething that ever thinks is
gonna happen that you mightdisagree with?
SPEAKER_03 (28:52):
I think that the future of TA isn't about more
automation.
It's gonna be about morecuration and connection.
I think everyone assumes AI isgonna replace recruiters, but I
think the real advantage isgonna come from teams who use it
to deepen human connection.
I think automation is at thisday and age, it's table stakes.
Trust and personalization willbe the true different
(29:13):
differentiators.
I think the next phase won't beabout who has the most tools.
It's gonna be about who usesthem most intentionally to make
the experience feel more human,transparent, and authentic.
SPEAKER_02 (29:25):
All right, I like that.
Okay, well, the last questionthat I ask everyone is so what
are you reading or listening todo these days?
And you know, how are youlearning and staying ahead of
this curve?
SPEAKER_03 (29:34):
Yeah, so I listen to a lot of podcasts.
Um, one of my favorites isAstra, which is the American
Society for Healthcare HumanResources Administration.
So it hits close to home andit's a if they're quick listens.
I think they're like 25, 30minute listens.
I I'll listen to them while I'mlifting or running or something.
It's a podcast that's hosted byLuke Kerrigan and Bo Brabo, and
(29:56):
they have such a diverse mix ofhealthcare leaders that share
their experiences, theirSuccesses and my favorite
they're lessons learned becausewhy make the mistake if you
don't have to if you can learnfrom someone else?
SPEAKER_02 (30:07):
I know Luke Kerrigan.
He used to work at CareerBuilder.
Is he a Phenom?
I think he was at Phenom for awhile.
SPEAKER_03 (30:13):
He's at Phenom now, yes.
SPEAKER_02 (30:15):
You know what?
I don't know if Luke'slistening, but like I hired, I
tried to hire Luke for a salesengineering job probably 15
years ago at this point, and hehad a better job offer.
But he's very uh always a bigfan of Luke.
So yeah, I I know him very well.
SPEAKER_03 (30:32):
Yeah, he's fantastic.
He's so personable, and like Isaid, his podcast is awesome.
SPEAKER_02 (30:37):
Oh, that's great.
Well, Luke, or tag you in thisone for sure.
Um, big fan.
So oh that's great.
Okay, well, last question.
We'll list everything.
Um, we'll link out to yourLinkedIn profile for sure,
Yvette.
But you know, for folks thatwant to connect with you or
follow your work, you know,where should they find you?
SPEAKER_03 (30:54):
So obviously LinkedIn, but you can always
reach out to me at evet atevethanson.com.
SPEAKER_02 (31:00):
Awesome.
Love it.
Well, we'll link that in theshow notes, uh, your email, your
LinkedIn.
Um, and again, it's been a greatconversation.
So really appreciate you joiningus.
SPEAKER_01 (31:08):
Thank you so much for having me.
All right, thanks for tuning in.
As always, head on over tochangestate.io or shoot us a
note on all the social media.
We'd love to hear from you, andwe'll check you guys next week.
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