March 3, 2025 • 40 mins
In this episode of the Changing State of Talent Acquisition, hosts Graham Thornton and Martin Predd are joined by Matthew J. Daniel, Senior Principal of Talent Strategy at Guild, for a deep dive into the evolving nature of skills and career development. Matthew shares insights from his diverse background in learning, talent development, and in-house strategy, challenging the notion of a rapid "half-life" for skills and advocating for a more nuanced approach to skill-building in today’s fast-changing market.
Topics include:
- The Durable Skillset vs. the Half-Life Myth: Rethinking the idea that all skills quickly become obsolete and emphasizing the enduring value of fundamental abilities like communication and problem-solving.
- Building a Skill Portfolio: How to strategically invest in skills as long-term career assets rather than viewing them as fleeting data points.
- AI’s Role in Upskilling: Exploring where organizations are on the Gartner hype cycle for AI and practical approaches to integrating AI into talent development without over-reliance on outdated models.
- Practical Strategies for Talent Development: From auditing current AI usage among employees to designing learning strategies that address both immediate needs and future capabilities.
Join us for a candid conversation that bridges the gap between HR strategy and real-world application in the era of AI, and discover actionable insights to help your organization and employees stay ahead of the curve.
Matthew J. Daniel, Senior Principal of Talent Strategy, Guild
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Welcome to the Changing State of Talent
Acquisition, where your hosts,graham Thornton and Martin Cred,
share their unfiltered takes onwhat's happening in the world
of talent acquisition today.
Each week brings new guests whoshare their stories on the
tools, trends and technologiescurrently impacting the changing
state of talent acquisition.
Have feedback or want to jointhe show?
(00:21):
Head on over to changestateio.
And now on to this week'sepisode.
Speaker 2 (00:27):
All right and we're back with another episode of the
Changing State of TalentAcquisition podcast.
Super excited for our nextguest.
I think a logical next step inour conversation flow to start
the year.
Happy to welcome Matthew Daniel, senior Principal of Talent
Strategy at Guild.
Matthew, welcome to the podcast.
Speaker 3 (00:45):
Hey, thanks for having me.
Glad to be here.
Speaker 2 (00:48):
Awesome.
Well, I'd love to set the stagehere by having you tell us a
little bit more about yourself.
Why don't you tell us a littlebit more about your career
journey, Matthew, and what ledyou to your current role at
Guild, and maybe whatprofessional topics and
interests really occupy most ofyour time currently?
Speaker 3 (01:03):
Yeah, so I come from the world of learning and talent
development.
It's literally the first jobright out of college that I had
was in that space, and I workedfor a fantastic company, gp
Strategies, that did a ton oflearning, outsourcing and
programs like that, and it gaveme a chance the first six or
seven years of my career to justfloat around to public sector
(01:26):
and private sector, oil and gasand healthcare, tech and lots of
different organizations, whatthey were doing, how they were
doing it.
It felt like a six or sevenyear rotation program,
internship of like getting tosee and do it in so many places.
And then I think that you know,hot take here is that
consultants who've actuallynever lived inside the business
(01:49):
sometimes the advice they givedoesn't always connect with
reality, and so I had a coupleof those moments I remember in
particular.
Nike was a customer of mine andI said something one day and
across the table they looked atme like I had five eyes and I
thought, oh, okay, they're nevergoing to go do this, like I
just stumbled into something Ishouldn't have said and I
(02:13):
decided I wanted to go in-houseand learn what it was like to
actually be the person who hasto get initiatives over that
hill and get people to buy intoit.
And so I went in-house atCapital One, had just crossed
into the Fortune 100 and spentsix years there, which is where
I really learned.
If the audience that you haveis mostly talent acquisition,
(02:34):
then those are the people Ireally started to work with.
When I was there, I started tothink cross-functional.
I got outside of the bubble oflearning and did that for six
years.
It was great, did some of myown consulting, where I was
learning like go to market inaddition to building up those
proficiencies and understandingof HR, and then finally, five
years ago, landed at Guild,which has been the journey of a
(02:58):
lifetime.
I've been here from the reallyearly days.
Just a handful of customersback then, and now a really
large number of partners waswhat we call them employee
partners or customers that wework with and getting to
experience a real focus.
I built out our career,mobility, coe, and so this is
(03:20):
where I feel like I reallyintersected with your world,
which is, essentially, if we'rebuilding talent, if that's the
goal of what we're trying to do,but we haven't built the
connection into our folks intalent acquisition, then it all
falls apart, then we don't getto recognize the impact, we
don't get to change lives, wedon't get to take those skills
(03:40):
and apply them into the business, and so it really starts
spending a lot of time on howdoes this look?
How do we do it in an equitableway?
How do we have real impact?
How do we think about frontlineemployees as a talent pool for
more advanced roles inside theorganization that we're
struggling to recruit, thosekinds of things?
And so really started.
I found myself a talentacquisition mentor who I just
(04:01):
asked, barraged with questionsday after day, and started
working with TA teams inside thecustomers.
And anyway, what I spend my timeon right now, my role at Guild
is essentially to almost doprofessional advisory work like
professional services andadvisory work to Guild's
perspective and existingemployer partners and really do
(04:23):
research Right now guild'sperspective and existing
employer partners and really doresearch.
Right now we're in the middleof a body of research around roi
.
Uh feels like there's so muchpressure on finances.
Folks want to know thisinvestment that I'm making is it
worth it?
How am I going to account forit?
And so we're doing a bunch ofresearch on that that will start
to formulate into some papersand uh articles and podcasts and
that kind of stuff.
(04:43):
So so that's my job isessentially to research what's
happening in the market forGuild, make sure Guild
understands that, learn deeplyabout it.
I'm at a conference for CLOsright now whether they care
about what's working and thentake that back to Guild and
formulate frameworks andresearch that really meets the
needs of the market.
That's my job.
(05:04):
That's why I spend so much ofmy time on here.
Speaker 4 (05:07):
Wow.
Well, I'm also thrilled to haveyou.
I know Graham mentioned that.
Quite a backstory.
We have a lot of folks on thepodcast, matthew, but not all of
them come to us through theroute that you took.
I was kind of laughing when youwere talking about consultants,
because that's sort of the hatI've worn most of my career and
I can definitely relate to thefeeling of, as is so often the
(05:28):
case, a strength can also havesort of the opposite polarity or
an Achilles heel.
So consultants can be valuablebecause they're, for the same
reason that they can be,limiting, because they have an
outside perspective.
But yes, I've definitely sat inboard meetings and said
something that sounded reallystupid, just because I'm not in
the organization living andbreathing it.
So I definitely could relate tothat.
(05:50):
Well, there's a lot we want totalk about and you know AI is, I
think, everyone's topicfavorite topic these days.
But before we get into that, Ithought we could kind of ease
into it by way of a conversationabout this idea of skills
having a half-life.
I'm not really sure where thatoriginated.
You could probably tell us whofirst sort of coined that term
(06:11):
or this idea, but the idea isthat we live in a new economy, a
new labor market.
In our parents' generation oreven 20 years ago, you might get
a college degree and it wouldlast you most of your career, if
not all of your career, withthose same skills.
And now we're in a new normalwhere you might learn something
and I think the stat isirrelevant or outdated in two to
(06:34):
five years, which is reallyjust terrifying, I think.
If you're an employee, so maybeyou can help us unpack that.
Where did that come from?
I know you don't quite agreewith it.
I think you notoriously calledthis a half lie and I wonder if
you could just tell us moreabout your perspective on that.
Speaker 3 (06:49):
Yeah, I'm happy to.
Let me start with where I findcomplete alignment, which is
that the pace of change is high.
We all feel that If you've beenin the workforce I've been in
the workforce for 20 years andcertainly it feels in the
perspective of today like thingsare changing very quickly.
That data point actually comesfrom a misquote of someone who
(07:14):
gave congressional testimony inlike 1982, right before I was
even born.
That's actually where it comesfrom, but it makes for really
good marketing.
That's actually where it comesfrom, but it makes for really
good marketing.
And so there are lots of folks,especially on the learning
content side, who've taken that,grabbed hold of it and
reprinted it over and over andover again, but you just have
Lightcast on.
(07:35):
Those folks did a really goodreport not too long ago.
That's a lot more concreteabout how many of the skills in
job postings have changed basedon what they were a couple of
years ago.
Here's why it matters to me.
I don't much care about talkingabout the fact of the origins.
I find it amusing.
I think the real challenge thatI have is that you end up in a
(07:58):
world if you believe that thehalf-life of skills is two and a
half years if it's technical,or five if it's longer then you
start to believe you have tolive in this perpetual state,
especially if you're in the HRspace of like generating content
and getting it in front ofpeople and micro-learning.
And the fact is, one of themost critical skills you ever
(08:18):
built was communication and ifyou learned how to do that
really good, learned how to doit really well when you're 20,
21, 22, that thing sticks withyou.
Now you may learn newmodalities for that to go into.
Those do change.
Right, it's Slack and before itwas Slack you were using DMs at
work and whatever that was.
(08:38):
But ultimately it mattersbecause also the way that I
invest skills, the way I thinkabout skills and hopefully my
talent acquisition friends willget this too is that there are
skills that are more valuablethan others.
And this is where I think itgets scary is if you imagine
that all skills are justdissipating in value perpetually
(08:59):
all the time, then you willtreat every skill development as
if it's the same.
But whether you're acquiring askill or building a skill, if
you're making an investment insomething that's a really
durable skill, it's not fallingoff a resume in three years.
It's not falling off a jobposting in five, like the
ability to communicate matters,being a really good problem
(09:20):
solver when you're 25 years oldand investing the time and
energy into building that skill.
It's worth it.
And the way I think about thatis like there are programs that
you are or skills that you builtin college.
They actually matter.
There's a reason we can allargue about the cost of college
right now because it's crazy,but also we know that there are
(09:42):
fundamental skills of writing,presenting an idea, defending an
idea that we developed inschool that are critical for the
future, and so some of thatmoney was definitely worth it.
Did we learn how to use Slack?
No Like.
Did we learn how to use thelatest AI in a TA platform, an
ATS?
No Like.
That's not what we learned, butalso we learned these like
(10:04):
super fundamental, durableskills that do matter.
And then the other side of thatis, yes, there are skills that
are constantly changing yourprocesses and systems around you
, and so in that way, yes, youdo have to keep the right flow
of constantly learning,refreshing, making sure that
you're ready, but we have tothink about those skills, the
(10:25):
precision of how we know who haswhat skill and how we build
skill.
It has to have more nuance thanjust oh, all the skills are
falling apart.
Right, we have to think aboutit as in building a portfolio,
building a 401k, building aninvestment.
You have financial advisors whotell you build long-term in
this mutual fund and keep thismuch money in checking and
(10:48):
savings, and here's what you canhave in different formats.
And, you know, do theseinvestments in international and
it's riskier.
Right, you need that same thingfrom a skill portfolio.
You need things that are reallysolid, worth the investment,
sit on the shelf and accruevalue.
And then you got to also keepsome skills that are constantly
in the bank, changing all thetime, and just think in a little
(11:08):
more complicated way about whatskills mean to us.
Speaker 4 (11:12):
Thanks for unpacking that a bit.
I think that I had no ideaabout the backstory and I know
that's probably not the mostinteresting part here, but I
would never have guessed thatthat originated based on a
misquote from 1982.
So it's a good reminder to readheadlines and click-baity kind
of titles with caution.
I think there's a lot you saidthat I found interesting.
(11:33):
But I love this idea of a skillportfolio because I do think
when you see these stats whetherwe're talking about skills,
half-life or some othersensationalist take it can kind
of seem like fear-mongering orpanic-inducing.
If you're just a regularemployee, you know, and you're
like boy I just I might have$100,000 in student loan debt to
(11:55):
acquire these skills.
You're telling me, in five yearsit's gonna be worthless, and so
I just think that it'srefreshing to see some nuance to
the conversation.
And you know, anecdote is notdata, of course, but you know,
as a counterpoint to this ideathat skills dissipate in value
so quickly were relevant, and Itook a job when I was in my
(12:25):
early 20s and this is the storythat's common for a lot of
people they take an initial jobbecause they have a certain set
of skills and then somehow theybuild a career on it, because
it's just much easier to iterateon those skills than it is to
try to acquire completelydifferent or new skills.
And I think that just speaks toyou know and again it's just an
anecdote, but I think it speaksto this idea that what you were
(12:48):
saying, that skills some skillsdo are durable.
And, yes, maybe some of thelittle bells and whistles that
ornament the skills, if you willchange over time, but a lot of
people have skills that aredurable that will serve them for
their entire careers in someformat.
Is that a fair way ofdescribing?
Speaker 3 (13:02):
it.
It is, and actually you said aword a couple of times that I
want to key in on.
You said the word career andone of the things that's really
interesting.
Again, I work in a company thatis focused on how do we talk to
employers.
Guild's business model isessentially B2B2C right, we are
connecting and buildingrelationships with employers,
(13:24):
and that unlocks a relationshipdirectly with consumers or
learners, and in that we knowthat there are messages that are
different that we need to giveto the business.
The business is hyper-focused onskills, but look, normal human
beings, the people who work atyour company, aren't going home
sitting around the table andtalking about skills.
(13:44):
Right, in the world ofmarketing, sometimes what we do
is latch onto language that'salready there.
Sometimes we try to incept anew term into the market.
I think this is one of thoseareas where HR, frankly, has
been trying to convince theworld that skills mean a thing.
But that's not the way normalhumans talk.
(14:05):
When they go home and sit at thedinner table, they talk about
careers, they talk about howmuch they make, they talk about
where they want to go and,marnie, what you were saying
like, we think in terms of ourcareers, we don't think in terms
of skills and sometimes we justover-index on this level of
precision that, frankly, doesn'tresonate with our employees and
(14:26):
their employee experience.
They feel absolutely lost andoverwhelmed, and so do we need
to build skills, 100% Everythingthat we're doing.
We should do that way, weshould acquire the right skills,
but the way that we talk aboutthat is in terms of the career
that you're getting if you comework here, the career that
you're getting if you enroll inthese programs and develop
(14:46):
yourself, and so we have tolearn the difference between
talking to each other as HRprofessionals and the science
behind what we do and,ultimately, how we talk to our
employees and the language thatresonates with them.
Speaker 2 (15:00):
Yeah, I think that's interesting.
It makes me a little bitworried about how I want to
phrase this next questionMatthew, right?
Speaker 3 (15:09):
Never a good thing to do to a host on a podcast.
My bad my bad, I take it allback.
Speaker 2 (15:17):
Great, all right.
So we've talked a lot about thehalf-life and skills.
We're talking a lot more aboutemployee development, career
development.
I wanted to get us to you knowa conversation about, you know,
ai and its impact on skills andupskilling the workforce.
You know, but, however, however, like I wonder how I want to
phrase this now.
Speaker 3 (15:35):
So you know, let me let me yeah, you're going to
take a stab at it, but I'm goingto say it.
For us in HR, skills is a greatway to talk about it, right?
Skills in this format, skillsare data points.
They're ones and zeros.
They actually don't mean muchand we should talk about it.
We should just quit freakingtalking to employees about it as
if it's normal to them, becausethey're just what the hell?
(15:57):
But I'm sorry, go with yourquestion.
It's a great topic for us.
Speaker 2 (16:03):
I think that's great.
Well, fair enough, so I'm goingto use it anyway.
So, all right, we're talking alot about AI.
There are past guests in heretoo, and I think you've written
a lot about upskillingworkforces for an AI future,
right, and so I think there'sprobably a case to be made that
we are in what Gartner you knowwhat Gartner, or you know any
(16:24):
any of these folks would callyou know a trough of.
You know the hype cycle, right.
So when you know new technologykind of loses its, you know
initial, you know excitement,and so you know, I guess, a
couple things.
You know we've seen the cyclerepeat a lot, like, maybe more
recently with, you know, digitaltransformation in our space.
Maybe a good place to start is,like you know.
Can you kind of give a littlebit of an overview of you know
(16:45):
what is?
You know what do we mean by ahype cycle, gartner's hype cycle
, and you know.
Then I'd love to just, you know, dive in a little bit more
about, like, if AI is enteringthis trough period, what can we
learn or how should we bethinking about like AI and
upscaling, you know, throughthat lens of a Gartner hype
cycle, for example?
Speaker 3 (17:03):
Yeah, yeah, all right .
So the Gartner hype cycle it'sbeen around a number of years.
It essentially it's a graphleft to right and a new
technology or new idea comes onthe scene.
Josh Burson has a great one onskills-based organization that
he shares.
The hype cycle and where we areand what provides value, I
think in this AI, we are, Ithink, starting to come down
(17:27):
into what they call the troughof disillusionment, which I
think is, you know, soundsreally sad, and I think it is a
little sad because you justthink, oh, this is going to
change everything.
And I think what's interestingis AI, more than other things,
like the trough isn't quite asdeep, honestly, it does.
If you're an AI adopter, ifyou're using Gemini or GPT or
(17:52):
your internal, you know whateverthat looks like that's behind
the firewall, like you'veprobably started on a daily
basis.
You've got that tab open allthe time and you're like using
it to help you write, tosynthesize, to summarize, right.
So it has changed things, butalso you got some things to
learn about how to use it.
(18:12):
It has pretty significantlimitations and it doesn't get
as smart as you want it.
My own experience is like oh,you're telling me it learns as
it goes, but it sure doesn'tfeel like it's getting that much
smarter in the responses thatit's giving me.
I have to continually promptand push and prompt and push to
get the answer that I need, andso that's what we call that
(18:34):
trough of disillusionment, wherefolks start to feel like, yeah,
this is not changing everythingquite the way that I expected,
and then from there it kind ofgoes back up into they call it
the slope of enlightenment andthat's kind of where solutions
are found and ecosystems startto expand things, start to
really talk to each other, worktogether, and then it levels off
(18:55):
into the plateau ofproductivity where that
technology or innovation becomesmainstream.
If you haven't looked at it,you should.
The question that you asked,which is essentially what do we
do in this moment?
And I'm of the persuasion thatorganizations who actually are
doing the right amount of skillbuilding and infrastructure
(19:16):
building and laying thegroundwork, I think those are
the folks that, as thetechnology actually does get
better, as AI is built into moreof our platforms, or as we have
the ability, you know, theengineers that we have behind
the scenes are building AI evendeeper into homegrown products,
etc.
I think the organizations whohide from it.
(19:37):
And literally there wassomebody on a stage yesterday
who had just come from oneorganization to another and she
said you know, we ran away inthe organization I just came
from, you weren't allowed totouch it.
Now everybody was touching iton their personal devices, but
we weren't allowed to touch itfrom the company perspective.
And then she goes to the nextcompany and that company says no
(19:58):
, you know, explore it, see whathappens.
I think the difference betweenthose two companies is that
they're both going to find thatit has its limitations for
day-to-day use, but one group isgoing to be in the process of
finding ways to use it that makethe world better and get talent
that actually builds thoseskills, and the other is going
(20:19):
to get absolutely caughtflat-footed by competitors in
the market whenever it reallycomes out.
And I think that is thedifference between one and the
other.
Our CEO at Capital One used totalk about this concept of a
loaded spring and he would saylook, I know what we're doing
building this infrastructure anddigital and all of these things
(20:41):
.
It doesn't feel like it'shaving that much of an impact
yet, but I promise what we'redoing is we are storing energy
in a loaded spring and at somepoint, the trigger is going to
come along and this energy isgoing to be released into the
market, and you're going to seeit in our stock price.
You're going to see it in theproducts that we build, you're
going to see it in the customerexperience, and I really think,
(21:03):
in this AI moment, what we'redoing should be building skills.
Even if we're disappointed,even if it doesn't work the way
we thought, even if thoseproduct companies that told us
all those HR platforms weregoing to revolutionize our world
and they don't it's still goodto build the skills right now,
because when it does get better,you're going to have talent
(21:25):
that's ready to build for thefuture.
That's truly what I believe.
Speaker 2 (21:27):
Yeah, I, I, uh, you know, I feel like, you know
terms like trough, of uh,disillusionment, you know, you
remind me of, uh, something thatyou'd hear on a severance
episode.
Uh, you know, one of thebasement of a piece, but, um, no
, I mean, I, I think that'sgreat and, like you know, I'm
kind of reminded.
I think there's an interviewwith, you know, jeff Bezos.
You know, and you know, talkingabout how, like hey, like, when
(21:48):
we invented you know,electricity it was, you know,
the initial goal was, like hey,we just wanted to put a light
bulb, you know, on in the house.
And so, like hey, electricitywas, like you know, quite
literally invented.
So, you know, we could, youknow, turn on a light bulb.
And you know, you think aboutthe impact of electricity today,
you know it's gone far beyondturning on a light.
And, you know, I think, when wethink about AI, you know, yeah,
(22:10):
sure, you know we might be in alittle bit of a lull.
You know you get frustratedthat you pop something into an
algorithm, but I think you knowhe's comparing AI to, you know,
the advent of electricity, right, and like hey, like we're, you
know, so, you know, so early onthat you know the companies that
are, you know, embracing AIwith more of a, you know
future-focused.
You know mindset recognize thatthere's a pretty big shift
(22:32):
coming.
You know that we're all bracingfor right.
Speaker 3 (22:35):
Yeah, I mean, this is where my brain goes to.
You know, I'm not advocatingfor anybody to create risk in
their organization by layeringAI on you know, social security
numbers or customer data thatshouldn't be exposed.
There have to be rules, therehas to be a sandbox, there has
to be governance Like let's notbe stupid.
You know, certainly we havethose kind of things at Guild.
(22:57):
We're making sure we protectdata, but ultimately I think you
do have to create a sandbox,otherwise that data is going
outside of enterprise, right,and folks are going to play with
that data, no matter how manytimes you tell them not to.
They're going to go pull upGemini or chat GPT and they're
(23:17):
going to try and figure out justhow far they can go playing
with that tool and how it canhelp them, but ultimately, you
know, create risk to yourorganization.
I think I have a stat here thatfolks say see, this was a JFF
study last year 88% of employeesaren't confident their employer
will support them inunderstanding AI.
You've got the trust surveythat comes out every year from
(23:40):
Edelman and what it says is likeI am nervous in this world
about whether or not I getsupport, and what it says is
like I am nervous in this worldabout whether or not I get
support.
So I think this is whereemployers have an opportunity to
say no, we're committed to youlearning, even if we're not
fully committed to baking itinto every part of the way our
business functions.
Yet.
Speaker 4 (23:56):
Yeah, well said.
I think you've made aninteresting point in a few
different ways here, which isthat so often we're thinking
from the lens of employers.
I mean, we are talentacquisition folks after all, so
that's not surprising.
But I think one of the knockouteffects of that is that we can
be speaking to our employees andto prospective talent in
language that just does notapply to what their experience
(24:16):
is at all.
You made the point earlier aboutthis idea of skills versus
career and here, specific to AI,I think there's something
similar going on.
If you're an employer thattakes this posture of well, we
got to find the people theemployees have already figured
out AI and hire those people,rather than taking an approach
of it's.
Actually the onus is on us asthe employer or even bigger than
(24:38):
employer, as an industry, tocultivate the skills and lead
the way for all these greatpeople and all the great talent
that currently exists that maynot have all of the skills that
they need.
So I think that's a breath offresh air in an industry where
sometimes it can feel like we'reputting too much of the weight
on the employee.
And then the other thing that Ithink is interesting, that I'd
love to get your perspective onis.
(24:58):
I mean, I don't remember wherethis came from either, but
there's a lot of folks employeesthat are already using
generative AI in some fashion.
I think we've kind of hinted atthat in passing here, but I
think that raises interestingquestions.
It's sort of you know, as TAleaders, we can be so future
focused, like we're all waiting,we're in this trough or loaded
(25:19):
spring or however you want totalk about it, waiting for some
big moment to happen, and thenyou see stats that say it's kind
of already here in some way.
A lot of employees are using achat, gpt or another generative
AI engine to assist them intheir jobs, and often without
employer knowledge, oversight,guidance structure or any of
that.
I just wonder if you couldexpand on that a bit and help us
(25:43):
understand.
If you are an organizationwhere that may be the case,
where do you begin?
I mean, do you have to start byjust auditing how the tools are
already being used, despiteyour knowledge, or where would
you start?
Speaker 3 (25:53):
Yeah, the stats are really fascinating in how AI is
getting used.
You have greater than 40, 50,60 percent, depending on who's
asking what's happening.
And I think, if I am anemployer right now and Guild
actually did this with our ownemployees, which I appreciated
(26:15):
they went out to the population,they gave us an anonymous
survey you didn't have to likethere was none of our data on
the back end and they said howare you using it today?
Like, in what ways?
What are the platforms thatyou're using?
How often are you using it?
What are the ways that you'reusing it?
Because I think, as humans, weall have a little bit of agency
(26:36):
and we all all know our jobs andwe all know what we're
interested in, and so, for thoseof us who are kind of going to
lead in this, we're going tofind a way to do it, no matter
what, and so actually askingyour employees where they're
using it, what they findinteresting in it, and giving
that anonymity to them so thatyou can get honest answers, is a
(26:57):
great way to start.
Ask your talent, what'shappening right now.
I think the second piece isyou've got to work on a learning
strategy for your existingtalent.
This is where I think all of usover-index.
Your job in talent acquisitionis to buy talent.
My job in talent development isto build it, and I think the
truth is it's a little bit ofboth.
(27:18):
Right, we need those, we needthat bot talent from the market
that can serve as some leaders.
But, honestly, if what you'retrying to do is acquire AI
talent on the market, that'ssome freaking expensive talent
right now Hard to find.
That posting is going to beopen for a while.
You're going to be disappointedwhen they get behind the
firewall anyway, because it'sfairly limited how far they
(27:40):
could have gone right now, andso I think this is a lot of a
building, and so we worked on abit of a framework to say, ok,
how do I subdivide the employeesthat I have and the kinds of
programs that I'm building?
You know one category we talkabout AI fundamentals, and this
is really, you know, focusing onAI literacy, ethics, the
(28:00):
implications of AI, and this isessentially something you know
everybody should have frontlineemployees or lead career leaders
and executives.
And then you have AI practice,and this is really about how do
I apply AI to my job, no matterwhere it is, and that's really
everybody, up and down thespectrum of the organization.
And then you have this nextcategory, which is like AI
(28:22):
expertise, builders of AI, thosewho are figuring out how to
apply it within the technologiesin the business environment.
And then you have this fourthcategory we talked about is like
AI for leaders, and this iswhere you're thinking of I've
got to make decisions about ourbusiness strategy and how AI
bakes into that, and so if youstart to think about the
(28:44):
learning that you're creating,the skills that you're building
in your organization, and youthoughtfully engage those
audiences, you can build out awhole range of you know.
Is it just an AI literacyprogram you put in front of
folks, or are you doing you knowMIT has implications for
business strategy certificate inAI, and so you can start to map
(29:07):
some of the programs that youneed to make available for your
own employees and then thoseplaces where you can let them
explore.
But whatever you do, ask thequestion of what they're
thinking about already.
Don't try and build a fire.
Follow the smoke is the waythat I would think about it and
support your employees inapplying that creativity and
(29:27):
ideas exactly where they areright now.
Speaker 2 (29:29):
Yeah, matthew.
So I think this is a greatpiece and I'm going to ask you
to unpack a little bit more.
So personas is something that'snear and dear to Marty's heart.
We talk about an employer brandside too, and I think there's
probably some public facingaspects of you know what you
just described.
I think you know you'd probablyagree that you know, adopting
AI and building out thesepersonas, as you kind of just
(29:51):
described them, is probably nota one size fits all.
You know proposition.
You know, proposition, you know.
But I'm curious, like in thepersonas that you kind of just
described, you know, do youthink those same buckets exist
at most organizations?
Or, you know, does it tend tobe more?
You know highly specific, youknow, at each organization.
You know, just in general, likehelp, you know, help us kind of
unpack this persona constructand like you know how you'd say,
(30:13):
you know, you know yourecommend HR leaders get started
with identifying.
You know you recommend HRleaders get started with
identifying.
You know, and sort of you knowoperationalizing.
You know these personas.
Speaker 3 (30:22):
Yeah, I mean, I think you do have to start if I'm
saying where do I focus myenergy?
Let me start with the firstquestion you asked.
Yes, I think we intentionallybuilt that framework so that it
could apply across as manyorganizations as possible, and
so those are broad enough.
You could, within yourorganization, really start to
(30:44):
segment up in more detail whothose folks are and what
programs apply to them.
I think this is also where Iwould encourage people to be
really thoughtful about whereyou try and build content versus
where you get good stuff offthe market, because building for
all of those audiences, frankly, you're probably not going to
have that expertise and that newtalent you just hired in off
(31:04):
the market.
You don't want them buildinglearning assets for others.
You really want them doing thejob so that they're bringing AI
into your products and solutions.
But yeah, so hopefully thosebuckets make sense to a lot of
people.
The second part of yourquestion is within these, maybe.
Where do I focus?
Where do I start?
I think that this is you heardme say it, but I believe in.
(31:29):
There are times that I like tobuild a fire and get everybody
excited.
There are also times where I'mjust smart enough to follow the
smoke, and I think this is aplace where you follow the smoke
.
And I think this is a placewhere you follow the smoke.
You figure out where thebusiness need is most likely to
drive adoption of AI tools andyou go to that place.
You don't focus on skilling upthe entire tech org on AI.
(31:50):
You figure out who's orientatedaround products.
You figure out who your leaderand executive is, who's going to
be on that bleeding edge, whoyour leader and executive is,
who's going to be on thatbleeding edge.
You start with them as youraudience.
You look at, you know, one ofthe ones that I just feel pretty
strongly about is we're goingto tend because this is what
employers do in general is notalways build the skills that we
(32:13):
need in our frontline employees.
To imagine you know what does aretail associate mean with like
understanding how to use a chat, gpt, and yet, at the same time
, what I'd say is God, wouldn'tit be amazing if you went to
your local hardware store andthey could, for the questions
(32:33):
that they don't know how toanswer, they could turn around
and pull up this tool with anemployee and show the value that
they add to say hey look, mylocal big box hardware store is
a place that I can trust to helpme solve this problem, even if
they don't know the answer.
So, and here's another stat foryou Only 14% of frontline
(32:53):
employees say they've receivedany type of training on AI
skills.
That comes from BCG last year,and so I think there is
intentionality we need to putbehind it.
Here's the danger Don't stopwhere you start, right, so start
somewhere.
Get some wins, start to buildthose skills, but also figure
out how you're going totransition beyond that first set
(33:16):
of personas, that firstaudience that you're going to
build with, so that you'reexpanding access as much as
possible.
So you have a talent pool topull from in lots of different
ways.
Speaker 4 (33:26):
Yeah, that makes a lot of sense, and I think that's
just what we're short on in theindustry often is practical
knowledge about where to begin,and I think you've given people
some really great pointers.
So thanks for that, matthew.
I mean I feel like we couldchat with you all day.
I know we're a little bit shorton time.
Maybe to sort of close here, wecould zoom out a bit.
One of the questions that I havefor a lot of folks at this
(33:50):
moment, as we think about AI, isit's very natural to want to
look back and use old models,old constructs, old frameworks
for understanding this moment.
We talked about Gartner's hypecycle.
It's not a new concept.
We've seen it in differentplaces, but there is a sense and
I'm no expert that AI isfundamentally different than
(34:12):
some of the other technologicaladvancements that have occurred,
and I think the only thing thatwe know for certain is that no
one knows for certain how thisis going to play out.
So if someone tells you thatall the knowledge workers are
going to be obsolete in fiveyears, it's a pretty good sign
that you're talking to a liar.
No one has a crystal ball right.
(34:32):
Nonetheless, it's an importantquestion.
I think it's a question that'son employers' minds.
It's a question that's onemployees' minds, and I guess
I'll ask you to look into yourcrystal ball.
I mean, what probability maybeis the way of getting at it,
rather than yes or no?
But what probability do youthink you would assign to the
possibility that we're going tosee some kind of exponential sea
(34:54):
change curve in terms of somekind of super intelligence that
really could obliterateknowledge work in a big way that
would not be overcomable.
Is that a thing?
Speaker 2 (35:06):
that could happen.
Speaker 3 (35:10):
Yeah, I don't love the term obliterate knowledge
work.
Speaker 2 (35:14):
I think that's the scariest thing.
Speaker 3 (35:16):
I feel like this makes me want to do severance
right, like let's cut the infrom the out.
Speaker 4 (35:22):
No.
Speaker 3 (35:23):
I think what do I put the odds at?
Here's my bottom line.
I'm hopeful.
I do think that the staffingmodels that we have right now
are going to fundamentallychange.
I just think the companies whoare further along in this
journey with AI what they'retelling us is this is not a
(35:46):
technology that you essentiallylayer on to your existing
processes.
This is something that youactually have to go back to the
whiteboard and redesign the waythat you work, when you do it,
y'all.
If we don't think that's goingto fundamentally shift jobs,
responsibilities, tasks, thatit's not going to impact like
shaving off work, I think you'refoolish, right?
(36:08):
I think you're not payingattention if that's what you're
saying.
So what is the chance that ithas a pretty significant impact
on roles in the knowledgeeconomy?
I'm putting it at like 40, 45%,I guess, if I were going to put
a number to it.
So it feels real enough to methat we need to prepare for it.
I think this is a moment wherewe need to be as clear with the
(36:31):
employees who work for us andwho are coming to work for us as
we can right now, and we needto say look, things are changing
, they're going to change, andif you are not willing to learn
right.
The quote that's going aroundeverywhere is you know you're
not going to be replaced with AI, but you are going to be
(36:51):
replaced by somebody who uses AI, and I think that is the
sentiment that we need tocommunicate clearly, which is
don't live in fear that your jobis going to change or the AI is
going to take things away.
Be the designer of your destiny.
Where it's possible, takeagency and figure out some of
the ways that AI comes into yourwork and or how your work can
(37:12):
be designed, so that you're notsitting there surprised when
somebody shows up and says youknow, it turns out this was a
series of tasks.
60% of your job is actuallyreally easy to do with agentic
AI and so we're going to turnloose on that and we don't need
you anymore.
I think there are some folkswho are definitely going to get
that message.
The folks who aren't going tobe surprised are the ones who
(37:35):
are actually figuring out ways,trying to influence AI, using it
in their personal life and,frankly, more than anything else
, just willing to learn as itcomes, willing to sit down and
wrestle with it.
That's what we get paid for andI do think work is going to be.
This makes things morechallenging.
I mean, I'll bring up like oneother interesting fact.
(37:57):
I don't know if you all saw thepress release Maybe it was last
week, week before where Workdayis adding the capability of
tracking agents in the same waythat you would like track
employees.
They are, and I was wonderingwho was going to be out first on
this right.
Were we going to do that fromHR?
Were we going to do that fromIT?
You know we should think aboutour jobs as maybe hiring and
(38:21):
training agents, tracking agents, making sure the agents play
well in the HR space.
So look, it's coming, it'sgoing to have a real impact and
the question is not, you know,should I prepare it's?
What are you doing today to getready for it?
Are you learning, investing inyourself, building your own
talent, helping the people thatyou lead?
(38:42):
Build those skills, creating asandbox so they can play, so you
can lead on the future, insteadof getting run over by?
Speaker 4 (38:49):
it, love it, love it.
Thanks for bringing us backtowards the light.
I was laughing with Graham inour backroom conversation
because on our previous episodeI closed it with a question
about whether the American dreamis dead, which really took us
into a dark place, and thentoday I tried to close it with
whether AI is going toobliterate all knowledge work.
(39:09):
So I appreciate you ending uswith a message of hope, and I
guess I got to do some workpersonally here to figure out
why I'm in such a dark place.
Grant, do you have anything tosay?
Speaker 2 (39:23):
to close yeah, be the change you want to see in the
world, marty.
You know, I think I think youknow.
The easiest question, I think,is this one Matthew, so loved
our conversation.
Where can people find youonline?
Yeah, loved our conversation.
Speaker 3 (39:38):
Where can people find you online?
Yeah, linkedincom, slash inslash.
Matthew J Daniel, that's whereto find me, and you will find me
at Guild, at events, atpodcasts.
You'll see all that posted upthere and I would love to
connect with you directly thereand teach me something about
talent acquisition.
Speaker 2 (39:57):
I love it, love it.
Well, thank you, matthew.
We'll link everything in theshow notes, of course, and I
know you write a lot of contenttoo, so you know some great
articles.
If you just Google, matthew,you'll see them all over the
internet.
So thanks again for joining us,matthew.
It's been a great conversation,all right.
Thanks for tuning in.
As always, head on over tochangestateio or shoot us a note
(40:18):
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, where your hosts,graham Thornton and Martin Cred,
share their unfiltered takes onwhat's happening in the world
of talent acquisition today.
Each week brings new guests whoshare their stories on the
tools, trends and technologiescurrently impacting the changing
state of talent acquisition.
Have feedback or want to jointhe show?
(00:21):
Head on over to changestateio.
And now on to this week'sepisode.
Speaker 2 (00:27):
All right and we're back with another episode of the
Changing State of TalentAcquisition podcast.
Super excited for our nextguest.
I think a logical next step inour conversation flow to start
the year.
Happy to welcome Matthew Daniel, senior Principal of Talent
Strategy at Guild.
Matthew, welcome to the podcast.
Speaker 3 (00:45):
Hey, thanks for having me.
Glad to be here.
Speaker 2 (00:48):
Awesome.
Well, I'd love to set the stagehere by having you tell us a
little bit more about yourself.
Why don't you tell us a littlebit more about your career
journey, Matthew, and what ledyou to your current role at
Guild, and maybe whatprofessional topics and
interests really occupy most ofyour time currently?
Speaker 3 (01:03):
Yeah, so I come from the world of learning and talent
development.
It's literally the first jobright out of college that I had
was in that space, and I workedfor a fantastic company, gp
Strategies, that did a ton oflearning, outsourcing and
programs like that, and it gaveme a chance the first six or
seven years of my career to justfloat around to public sector
(01:26):
and private sector, oil and gasand healthcare, tech and lots of
different organizations, whatthey were doing, how they were
doing it.
It felt like a six or sevenyear rotation program,
internship of like getting tosee and do it in so many places.
And then I think that you know,hot take here is that
consultants who've actuallynever lived inside the business
(01:49):
sometimes the advice they givedoesn't always connect with
reality, and so I had a coupleof those moments I remember in
particular.
Nike was a customer of mine andI said something one day and
across the table they looked atme like I had five eyes and I
thought, oh, okay, they're nevergoing to go do this, like I
just stumbled into something Ishouldn't have said and I
(02:13):
decided I wanted to go in-houseand learn what it was like to
actually be the person who hasto get initiatives over that
hill and get people to buy intoit.
And so I went in-house atCapital One, had just crossed
into the Fortune 100 and spentsix years there, which is where
I really learned.
If the audience that you haveis mostly talent acquisition,
(02:34):
then those are the people Ireally started to work with.
When I was there, I started tothink cross-functional.
I got outside of the bubble oflearning and did that for six
years.
It was great, did some of myown consulting, where I was
learning like go to market inaddition to building up those
proficiencies and understandingof HR, and then finally, five
years ago, landed at Guild,which has been the journey of a
(02:58):
lifetime.
I've been here from the reallyearly days.
Just a handful of customersback then, and now a really
large number of partners waswhat we call them employee
partners or customers that wework with and getting to
experience a real focus.
I built out our career,mobility, coe, and so this is
(03:20):
where I feel like I reallyintersected with your world,
which is, essentially, if we'rebuilding talent, if that's the
goal of what we're trying to do,but we haven't built the
connection into our folks intalent acquisition, then it all
falls apart, then we don't getto recognize the impact, we
don't get to change lives, wedon't get to take those skills
(03:40):
and apply them into the business, and so it really starts
spending a lot of time on howdoes this look?
How do we do it in an equitableway?
How do we have real impact?
How do we think about frontlineemployees as a talent pool for
more advanced roles inside theorganization that we're
struggling to recruit, thosekinds of things?
And so really started.
I found myself a talentacquisition mentor who I just
(04:01):
asked, barraged with questionsday after day, and started
working with TA teams inside thecustomers.
And anyway, what I spend my timeon right now, my role at Guild
is essentially to almost doprofessional advisory work like
professional services andadvisory work to Guild's
perspective and existingemployer partners and really do
(04:23):
research Right now guild'sperspective and existing
employer partners and really doresearch.
Right now we're in the middleof a body of research around roi
.
Uh feels like there's so muchpressure on finances.
Folks want to know thisinvestment that I'm making is it
worth it?
How am I going to account forit?
And so we're doing a bunch ofresearch on that that will start
to formulate into some papersand uh articles and podcasts and
that kind of stuff.
(04:43):
So so that's my job isessentially to research what's
happening in the market forGuild, make sure Guild
understands that, learn deeplyabout it.
I'm at a conference for CLOsright now whether they care
about what's working and thentake that back to Guild and
formulate frameworks andresearch that really meets the
needs of the market.
That's my job.
(05:04):
That's why I spend so much ofmy time on here.
Speaker 4 (05:07):
Wow.
Well, I'm also thrilled to haveyou.
I know Graham mentioned that.
Quite a backstory.
We have a lot of folks on thepodcast, matthew, but not all of
them come to us through theroute that you took.
I was kind of laughing when youwere talking about consultants,
because that's sort of the hatI've worn most of my career and
I can definitely relate to thefeeling of, as is so often the
(05:28):
case, a strength can also havesort of the opposite polarity or
an Achilles heel.
So consultants can be valuablebecause they're, for the same
reason that they can be,limiting, because they have an
outside perspective.
But yes, I've definitely sat inboard meetings and said
something that sounded reallystupid, just because I'm not in
the organization living andbreathing it.
So I definitely could relate tothat.
(05:50):
Well, there's a lot we want totalk about and you know AI is, I
think, everyone's topicfavorite topic these days.
But before we get into that, Ithought we could kind of ease
into it by way of a conversationabout this idea of skills
having a half-life.
I'm not really sure where thatoriginated.
You could probably tell us whofirst sort of coined that term
(06:11):
or this idea, but the idea isthat we live in a new economy, a
new labor market.
In our parents' generation oreven 20 years ago, you might get
a college degree and it wouldlast you most of your career, if
not all of your career, withthose same skills.
And now we're in a new normalwhere you might learn something
and I think the stat isirrelevant or outdated in two to
(06:34):
five years, which is reallyjust terrifying, I think.
If you're an employee, so maybeyou can help us unpack that.
Where did that come from?
I know you don't quite agreewith it.
I think you notoriously calledthis a half lie and I wonder if
you could just tell us moreabout your perspective on that.
Speaker 3 (06:49):
Yeah, I'm happy to.
Let me start with where I findcomplete alignment, which is
that the pace of change is high.
We all feel that If you've beenin the workforce I've been in
the workforce for 20 years andcertainly it feels in the
perspective of today like thingsare changing very quickly.
That data point actually comesfrom a misquote of someone who
(07:14):
gave congressional testimony inlike 1982, right before I was
even born.
That's actually where it comesfrom, but it makes for really
good marketing.
That's actually where it comesfrom, but it makes for really
good marketing.
And so there are lots of folks,especially on the learning
content side, who've taken that,grabbed hold of it and
reprinted it over and over andover again, but you just have
Lightcast on.
(07:35):
Those folks did a really goodreport not too long ago.
That's a lot more concreteabout how many of the skills in
job postings have changed basedon what they were a couple of
years ago.
Here's why it matters to me.
I don't much care about talkingabout the fact of the origins.
I find it amusing.
I think the real challenge thatI have is that you end up in a
(07:58):
world if you believe that thehalf-life of skills is two and a
half years if it's technical,or five if it's longer then you
start to believe you have tolive in this perpetual state,
especially if you're in the HRspace of like generating content
and getting it in front ofpeople and micro-learning.
And the fact is, one of themost critical skills you ever
(08:18):
built was communication and ifyou learned how to do that
really good, learned how to doit really well when you're 20,
21, 22, that thing sticks withyou.
Now you may learn newmodalities for that to go into.
Those do change.
Right, it's Slack and before itwas Slack you were using DMs at
work and whatever that was.
(08:38):
But ultimately it mattersbecause also the way that I
invest skills, the way I thinkabout skills and hopefully my
talent acquisition friends willget this too is that there are
skills that are more valuablethan others.
And this is where I think itgets scary is if you imagine
that all skills are justdissipating in value perpetually
(08:59):
all the time, then you willtreat every skill development as
if it's the same.
But whether you're acquiring askill or building a skill, if
you're making an investment insomething that's a really
durable skill, it's not fallingoff a resume in three years.
It's not falling off a jobposting in five, like the
ability to communicate matters,being a really good problem
(09:20):
solver when you're 25 years oldand investing the time and
energy into building that skill.
It's worth it.
And the way I think about thatis like there are programs that
you are or skills that you builtin college.
They actually matter.
There's a reason we can allargue about the cost of college
right now because it's crazy,but also we know that there are
(09:42):
fundamental skills of writing,presenting an idea, defending an
idea that we developed inschool that are critical for the
future, and so some of thatmoney was definitely worth it.
Did we learn how to use Slack?
No Like.
Did we learn how to use thelatest AI in a TA platform, an
ATS?
No Like.
That's not what we learned, butalso we learned these like
(10:04):
super fundamental, durableskills that do matter.
And then the other side of thatis, yes, there are skills that
are constantly changing yourprocesses and systems around you
, and so in that way, yes, youdo have to keep the right flow
of constantly learning,refreshing, making sure that
you're ready, but we have tothink about those skills, the
(10:25):
precision of how we know who haswhat skill and how we build
skill.
It has to have more nuance thanjust oh, all the skills are
falling apart.
Right, we have to think aboutit as in building a portfolio,
building a 401k, building aninvestment.
You have financial advisors whotell you build long-term in
this mutual fund and keep thismuch money in checking and
(10:48):
savings, and here's what you canhave in different formats.
And, you know, do theseinvestments in international and
it's riskier.
Right, you need that same thingfrom a skill portfolio.
You need things that are reallysolid, worth the investment,
sit on the shelf and accruevalue.
And then you got to also keepsome skills that are constantly
in the bank, changing all thetime, and just think in a little
(11:08):
more complicated way about whatskills mean to us.
Speaker 4 (11:12):
Thanks for unpacking that a bit.
I think that I had no ideaabout the backstory and I know
that's probably not the mostinteresting part here, but I
would never have guessed thatthat originated based on a
misquote from 1982.
So it's a good reminder to readheadlines and click-baity kind
of titles with caution.
I think there's a lot you saidthat I found interesting.
(11:33):
But I love this idea of a skillportfolio because I do think
when you see these stats whetherwe're talking about skills,
half-life or some othersensationalist take it can kind
of seem like fear-mongering orpanic-inducing.
If you're just a regularemployee, you know, and you're
like boy I just I might have$100,000 in student loan debt to
(11:55):
acquire these skills.
You're telling me, in five yearsit's gonna be worthless, and so
I just think that it'srefreshing to see some nuance to
the conversation.
And you know, anecdote is notdata, of course, but you know,
as a counterpoint to this ideathat skills dissipate in value
so quickly were relevant, and Itook a job when I was in my
(12:25):
early 20s and this is the storythat's common for a lot of
people they take an initial jobbecause they have a certain set
of skills and then somehow theybuild a career on it, because
it's just much easier to iterateon those skills than it is to
try to acquire completelydifferent or new skills.
And I think that just speaks toyou know and again it's just an
anecdote, but I think it speaksto this idea that what you were
(12:48):
saying, that skills some skillsdo are durable.
And, yes, maybe some of thelittle bells and whistles that
ornament the skills, if you willchange over time, but a lot of
people have skills that aredurable that will serve them for
their entire careers in someformat.
Is that a fair way ofdescribing?
Speaker 3 (13:02):
it.
It is, and actually you said aword a couple of times that I
want to key in on.
You said the word career andone of the things that's really
interesting.
Again, I work in a company thatis focused on how do we talk to
employers.
Guild's business model isessentially B2B2C right, we are
connecting and buildingrelationships with employers,
(13:24):
and that unlocks a relationshipdirectly with consumers or
learners, and in that we knowthat there are messages that are
different that we need to giveto the business.
The business is hyper-focused onskills, but look, normal human
beings, the people who work atyour company, aren't going home
sitting around the table andtalking about skills.
(13:44):
Right, in the world ofmarketing, sometimes what we do
is latch onto language that'salready there.
Sometimes we try to incept anew term into the market.
I think this is one of thoseareas where HR, frankly, has
been trying to convince theworld that skills mean a thing.
But that's not the way normalhumans talk.
(14:05):
When they go home and sit at thedinner table, they talk about
careers, they talk about howmuch they make, they talk about
where they want to go and,marnie, what you were saying
like, we think in terms of ourcareers, we don't think in terms
of skills and sometimes we justover-index on this level of
precision that, frankly, doesn'tresonate with our employees and
(14:26):
their employee experience.
They feel absolutely lost andoverwhelmed, and so do we need
to build skills, 100% Everythingthat we're doing.
We should do that way, weshould acquire the right skills,
but the way that we talk aboutthat is in terms of the career
that you're getting if you comework here, the career that
you're getting if you enroll inthese programs and develop
(14:46):
yourself, and so we have tolearn the difference between
talking to each other as HRprofessionals and the science
behind what we do and,ultimately, how we talk to our
employees and the language thatresonates with them.
Speaker 2 (15:00):
Yeah, I think that's interesting.
It makes me a little bitworried about how I want to
phrase this next questionMatthew, right?
Speaker 3 (15:09):
Never a good thing to do to a host on a podcast.
My bad my bad, I take it allback.
Speaker 2 (15:17):
Great, all right.
So we've talked a lot about thehalf-life and skills.
We're talking a lot more aboutemployee development, career
development.
I wanted to get us to you knowa conversation about, you know,
ai and its impact on skills andupskilling the workforce.
You know, but, however, however, like I wonder how I want to
phrase this now.
Speaker 3 (15:35):
So you know, let me let me yeah, you're going to
take a stab at it, but I'm goingto say it.
For us in HR, skills is a greatway to talk about it, right?
Skills in this format, skillsare data points.
They're ones and zeros.
They actually don't mean muchand we should talk about it.
We should just quit freakingtalking to employees about it as
if it's normal to them, becausethey're just what the hell?
(15:57):
But I'm sorry, go with yourquestion.
It's a great topic for us.
Speaker 2 (16:03):
I think that's great.
Well, fair enough, so I'm goingto use it anyway.
So, all right, we're talking alot about AI.
There are past guests in heretoo, and I think you've written
a lot about upskillingworkforces for an AI future,
right, and so I think there'sprobably a case to be made that
we are in what Gartner you knowwhat Gartner, or you know any
(16:24):
any of these folks would callyou know a trough of.
You know the hype cycle, right.
So when you know new technologykind of loses its, you know
initial, you know excitement,and so you know, I guess, a
couple things.
You know we've seen the cyclerepeat a lot, like, maybe more
recently with, you know, digitaltransformation in our space.
Maybe a good place to start is,like you know.
Can you kind of give a littlebit of an overview of you know
(16:45):
what is?
You know what do we mean by ahype cycle, gartner's hype cycle
, and you know.
Then I'd love to just, you know, dive in a little bit more
about, like, if AI is enteringthis trough period, what can we
learn or how should we bethinking about like AI and
upscaling, you know, throughthat lens of a Gartner hype
cycle, for example?
Speaker 3 (17:03):
Yeah, yeah, all right .
So the Gartner hype cycle it'sbeen around a number of years.
It essentially it's a graphleft to right and a new
technology or new idea comes onthe scene.
Josh Burson has a great one onskills-based organization that
he shares.
The hype cycle and where we areand what provides value, I
think in this AI, we are, Ithink, starting to come down
(17:27):
into what they call the troughof disillusionment, which I
think is, you know, soundsreally sad, and I think it is a
little sad because you justthink, oh, this is going to
change everything.
And I think what's interestingis AI, more than other things,
like the trough isn't quite asdeep, honestly, it does.
If you're an AI adopter, ifyou're using Gemini or GPT or
(17:52):
your internal, you know whateverthat looks like that's behind
the firewall, like you'veprobably started on a daily
basis.
You've got that tab open allthe time and you're like using
it to help you write, tosynthesize, to summarize, right.
So it has changed things, butalso you got some things to
learn about how to use it.
(18:12):
It has pretty significantlimitations and it doesn't get
as smart as you want it.
My own experience is like oh,you're telling me it learns as
it goes, but it sure doesn'tfeel like it's getting that much
smarter in the responses thatit's giving me.
I have to continually promptand push and prompt and push to
get the answer that I need, andso that's what we call that
(18:34):
trough of disillusionment, wherefolks start to feel like, yeah,
this is not changing everythingquite the way that I expected,
and then from there it kind ofgoes back up into they call it
the slope of enlightenment andthat's kind of where solutions
are found and ecosystems startto expand things, start to
really talk to each other, worktogether, and then it levels off
(18:55):
into the plateau ofproductivity where that
technology or innovation becomesmainstream.
If you haven't looked at it,you should.
The question that you asked,which is essentially what do we
do in this moment?
And I'm of the persuasion thatorganizations who actually are
doing the right amount of skillbuilding and infrastructure
(19:16):
building and laying thegroundwork, I think those are
the folks that, as thetechnology actually does get
better, as AI is built into moreof our platforms, or as we have
the ability, you know, theengineers that we have behind
the scenes are building AI evendeeper into homegrown products,
etc.
I think the organizations whohide from it.
(19:37):
And literally there wassomebody on a stage yesterday
who had just come from oneorganization to another and she
said you know, we ran away inthe organization I just came
from, you weren't allowed totouch it.
Now everybody was touching iton their personal devices, but
we weren't allowed to touch itfrom the company perspective.
And then she goes to the nextcompany and that company says no
(19:58):
, you know, explore it, see whathappens.
I think the difference betweenthose two companies is that
they're both going to find thatit has its limitations for
day-to-day use, but one group isgoing to be in the process of
finding ways to use it that makethe world better and get talent
that actually builds thoseskills, and the other is going
(20:19):
to get absolutely caughtflat-footed by competitors in
the market whenever it reallycomes out.
And I think that is thedifference between one and the
other.
Our CEO at Capital One used totalk about this concept of a
loaded spring and he would saylook, I know what we're doing
building this infrastructure anddigital and all of these things
(20:41):
.
It doesn't feel like it'shaving that much of an impact
yet, but I promise what we'redoing is we are storing energy
in a loaded spring and at somepoint, the trigger is going to
come along and this energy isgoing to be released into the
market, and you're going to seeit in our stock price.
You're going to see it in theproducts that we build, you're
going to see it in the customerexperience, and I really think,
(21:03):
in this AI moment, what we'redoing should be building skills.
Even if we're disappointed,even if it doesn't work the way
we thought, even if thoseproduct companies that told us
all those HR platforms weregoing to revolutionize our world
and they don't it's still goodto build the skills right now,
because when it does get better,you're going to have talent
(21:25):
that's ready to build for thefuture.
That's truly what I believe.
Speaker 2 (21:27):
Yeah, I, I, uh, you know, I feel like, you know
terms like trough, of uh,disillusionment, you know, you
remind me of, uh, something thatyou'd hear on a severance
episode.
Uh, you know, one of thebasement of a piece, but, um, no
, I mean, I, I think that'sgreat and, like you know, I'm
kind of reminded.
I think there's an interviewwith, you know, jeff Bezos.
You know, and you know, talkingabout how, like hey, like, when
(21:48):
we invented you know,electricity it was, you know,
the initial goal was, like hey,we just wanted to put a light
bulb, you know, on in the house.
And so, like hey, electricitywas, like you know, quite
literally invented.
So, you know, we could, youknow, turn on a light bulb.
And you know, you think aboutthe impact of electricity today,
you know it's gone far beyondturning on a light.
And, you know, I think, when wethink about AI, you know, yeah,
(22:10):
sure, you know we might be in alittle bit of a lull.
You know you get frustratedthat you pop something into an
algorithm, but I think you knowhe's comparing AI to, you know,
the advent of electricity, right, and like hey, like we're, you
know, so, you know, so early onthat you know the companies that
are, you know, embracing AIwith more of a, you know
future-focused.
You know mindset recognize thatthere's a pretty big shift
(22:32):
coming.
You know that we're all bracingfor right.
Speaker 3 (22:35):
Yeah, I mean, this is where my brain goes to.
You know, I'm not advocatingfor anybody to create risk in
their organization by layeringAI on you know, social security
numbers or customer data thatshouldn't be exposed.
There have to be rules, therehas to be a sandbox, there has
to be governance Like let's notbe stupid.
You know, certainly we havethose kind of things at Guild.
(22:57):
We're making sure we protectdata, but ultimately I think you
do have to create a sandbox,otherwise that data is going
outside of enterprise, right,and folks are going to play with
that data, no matter how manytimes you tell them not to.
They're going to go pull upGemini or chat GPT and they're
(23:17):
going to try and figure out justhow far they can go playing
with that tool and how it canhelp them, but ultimately, you
know, create risk to yourorganization.
I think I have a stat here thatfolks say see, this was a JFF
study last year 88% of employeesaren't confident their employer
will support them inunderstanding AI.
You've got the trust surveythat comes out every year from
(23:40):
Edelman and what it says is likeI am nervous in this world
about whether or not I getsupport, and what it says is
like I am nervous in this worldabout whether or not I get
support.
So I think this is whereemployers have an opportunity to
say no, we're committed to youlearning, even if we're not
fully committed to baking itinto every part of the way our
business functions.
Yet.
Speaker 4 (23:56):
Yeah, well said.
I think you've made aninteresting point in a few
different ways here, which isthat so often we're thinking
from the lens of employers.
I mean, we are talentacquisition folks after all, so
that's not surprising.
But I think one of the knockouteffects of that is that we can
be speaking to our employees andto prospective talent in
language that just does notapply to what their experience
(24:16):
is at all.
You made the point earlier aboutthis idea of skills versus
career and here, specific to AI,I think there's something
similar going on.
If you're an employer thattakes this posture of well, we
got to find the people theemployees have already figured
out AI and hire those people,rather than taking an approach
of it's.
Actually the onus is on us asthe employer or even bigger than
(24:38):
employer, as an industry, tocultivate the skills and lead
the way for all these greatpeople and all the great talent
that currently exists that maynot have all of the skills that
they need.
So I think that's a breath offresh air in an industry where
sometimes it can feel like we'reputting too much of the weight
on the employee.
And then the other thing that Ithink is interesting, that I'd
love to get your perspective onis.
(24:58):
I mean, I don't remember wherethis came from either, but
there's a lot of folks employeesthat are already using
generative AI in some fashion.
I think we've kind of hinted atthat in passing here, but I
think that raises interestingquestions.
It's sort of you know, as TAleaders, we can be so future
focused, like we're all waiting,we're in this trough or loaded
(25:19):
spring or however you want totalk about it, waiting for some
big moment to happen, and thenyou see stats that say it's kind
of already here in some way.
A lot of employees are using achat, gpt or another generative
AI engine to assist them intheir jobs, and often without
employer knowledge, oversight,guidance structure or any of
that.
I just wonder if you couldexpand on that a bit and help us
(25:43):
understand.
If you are an organizationwhere that may be the case,
where do you begin?
I mean, do you have to start byjust auditing how the tools are
already being used, despiteyour knowledge, or where would
you start?
Speaker 3 (25:53):
Yeah, the stats are really fascinating in how AI is
getting used.
You have greater than 40, 50,60 percent, depending on who's
asking what's happening.
And I think, if I am anemployer right now and Guild
actually did this with our ownemployees, which I appreciated
(26:15):
they went out to the population,they gave us an anonymous
survey you didn't have to likethere was none of our data on
the back end and they said howare you using it today?
Like, in what ways?
What are the platforms thatyou're using?
How often are you using it?
What are the ways that you'reusing it?
Because I think, as humans, weall have a little bit of agency
(26:36):
and we all all know our jobs andwe all know what we're
interested in, and so, for thoseof us who are kind of going to
lead in this, we're going tofind a way to do it, no matter
what, and so actually askingyour employees where they're
using it, what they findinteresting in it, and giving
that anonymity to them so thatyou can get honest answers, is a
(26:57):
great way to start.
Ask your talent, what'shappening right now.
I think the second piece isyou've got to work on a learning
strategy for your existingtalent.
This is where I think all of usover-index.
Your job in talent acquisitionis to buy talent.
My job in talent development isto build it, and I think the
truth is it's a little bit ofboth.
(27:18):
Right, we need those, we needthat bot talent from the market
that can serve as some leaders.
But, honestly, if what you'retrying to do is acquire AI
talent on the market, that'ssome freaking expensive talent
right now Hard to find.
That posting is going to beopen for a while.
You're going to be disappointedwhen they get behind the
firewall anyway, because it'sfairly limited how far they
(27:40):
could have gone right now, andso I think this is a lot of a
building, and so we worked on abit of a framework to say, ok,
how do I subdivide the employeesthat I have and the kinds of
programs that I'm building?
You know one category we talkabout AI fundamentals, and this
is really, you know, focusing onAI literacy, ethics, the
(28:00):
implications of AI, and this isessentially something you know
everybody should have frontlineemployees or lead career leaders
and executives.
And then you have AI practice,and this is really about how do
I apply AI to my job, no matterwhere it is, and that's really
everybody, up and down thespectrum of the organization.
And then you have this nextcategory, which is like AI
(28:22):
expertise, builders of AI, thosewho are figuring out how to
apply it within the technologiesin the business environment.
And then you have this fourthcategory we talked about is like
AI for leaders, and this iswhere you're thinking of I've
got to make decisions about ourbusiness strategy and how AI
bakes into that, and so if youstart to think about the
(28:44):
learning that you're creating,the skills that you're building
in your organization, and youthoughtfully engage those
audiences, you can build out awhole range of you know.
Is it just an AI literacyprogram you put in front of
folks, or are you doing you knowMIT has implications for
business strategy certificate inAI, and so you can start to map
(29:07):
some of the programs that youneed to make available for your
own employees and then thoseplaces where you can let them
explore.
But whatever you do, ask thequestion of what they're
thinking about already.
Don't try and build a fire.
Follow the smoke is the waythat I would think about it and
support your employees inapplying that creativity and
(29:27):
ideas exactly where they areright now.
Speaker 2 (29:29):
Yeah, matthew.
So I think this is a greatpiece and I'm going to ask you
to unpack a little bit more.
So personas is something that'snear and dear to Marty's heart.
We talk about an employer brandside too, and I think there's
probably some public facingaspects of you know what you
just described.
I think you know you'd probablyagree that you know, adopting
AI and building out thesepersonas, as you kind of just
(29:51):
described them, is probably nota one size fits all.
You know proposition.
You know, proposition, you know.
But I'm curious, like in thepersonas that you kind of just
described, you know, do youthink those same buckets exist
at most organizations?
Or, you know, does it tend tobe more?
You know highly specific, youknow, at each organization.
You know, just in general, likehelp, you know, help us kind of
unpack this persona constructand like you know how you'd say,
(30:13):
you know, you know yourecommend HR leaders get started
with identifying.
You know you recommend HRleaders get started with
identifying.
You know, and sort of you knowoperationalizing.
You know these personas.
Speaker 3 (30:22):
Yeah, I mean, I think you do have to start if I'm
saying where do I focus myenergy?
Let me start with the firstquestion you asked.
Yes, I think we intentionallybuilt that framework so that it
could apply across as manyorganizations as possible, and
so those are broad enough.
You could, within yourorganization, really start to
(30:44):
segment up in more detail whothose folks are and what
programs apply to them.
I think this is also where Iwould encourage people to be
really thoughtful about whereyou try and build content versus
where you get good stuff offthe market, because building for
all of those audiences, frankly, you're probably not going to
have that expertise and that newtalent you just hired in off
(31:04):
the market.
You don't want them buildinglearning assets for others.
You really want them doing thejob so that they're bringing AI
into your products and solutions.
But yeah, so hopefully thosebuckets make sense to a lot of
people.
The second part of yourquestion is within these, maybe.
Where do I focus?
Where do I start?
I think that this is you heardme say it, but I believe in.
(31:29):
There are times that I like tobuild a fire and get everybody
excited.
There are also times where I'mjust smart enough to follow the
smoke, and I think this is aplace where you follow the smoke
.
And I think this is a placewhere you follow the smoke.
You figure out where thebusiness need is most likely to
drive adoption of AI tools andyou go to that place.
You don't focus on skilling upthe entire tech org on AI.
(31:50):
You figure out who's orientatedaround products.
You figure out who your leaderand executive is, who's going to
be on that bleeding edge, whoyour leader and executive is,
who's going to be on thatbleeding edge.
You start with them as youraudience.
You look at, you know, one ofthe ones that I just feel pretty
strongly about is we're goingto tend because this is what
employers do in general is notalways build the skills that we
(32:13):
need in our frontline employees.
To imagine you know what does aretail associate mean with like
understanding how to use a chat, gpt, and yet, at the same time
, what I'd say is God, wouldn'tit be amazing if you went to
your local hardware store andthey could, for the questions
(32:33):
that they don't know how toanswer, they could turn around
and pull up this tool with anemployee and show the value that
they add to say hey look, mylocal big box hardware store is
a place that I can trust to helpme solve this problem, even if
they don't know the answer.
So, and here's another stat foryou Only 14% of frontline
(32:53):
employees say they've receivedany type of training on AI
skills.
That comes from BCG last year,and so I think there is
intentionality we need to putbehind it.
Here's the danger Don't stopwhere you start, right, so start
somewhere.
Get some wins, start to buildthose skills, but also figure
out how you're going totransition beyond that first set
(33:16):
of personas, that firstaudience that you're going to
build with, so that you'reexpanding access as much as
possible.
So you have a talent pool topull from in lots of different
ways.
Speaker 4 (33:26):
Yeah, that makes a lot of sense, and I think that's
just what we're short on in theindustry often is practical
knowledge about where to begin,and I think you've given people
some really great pointers.
So thanks for that, matthew.
I mean I feel like we couldchat with you all day.
I know we're a little bit shorton time.
Maybe to sort of close here, wecould zoom out a bit.
One of the questions that I havefor a lot of folks at this
(33:50):
moment, as we think about AI, isit's very natural to want to
look back and use old models,old constructs, old frameworks
for understanding this moment.
We talked about Gartner's hypecycle.
It's not a new concept.
We've seen it in differentplaces, but there is a sense and
I'm no expert that AI isfundamentally different than
(34:12):
some of the other technologicaladvancements that have occurred,
and I think the only thing thatwe know for certain is that no
one knows for certain how thisis going to play out.
So if someone tells you thatall the knowledge workers are
going to be obsolete in fiveyears, it's a pretty good sign
that you're talking to a liar.
No one has a crystal ball right.
(34:32):
Nonetheless, it's an importantquestion.
I think it's a question that'son employers' minds.
It's a question that's onemployees' minds, and I guess
I'll ask you to look into yourcrystal ball.
I mean, what probability maybeis the way of getting at it,
rather than yes or no?
But what probability do youthink you would assign to the
possibility that we're going tosee some kind of exponential sea
(34:54):
change curve in terms of somekind of super intelligence that
really could obliterateknowledge work in a big way that
would not be overcomable.
Is that a thing?
Speaker 2 (35:06):
that could happen.
Speaker 3 (35:10):
Yeah, I don't love the term obliterate knowledge
work.
Speaker 2 (35:14):
I think that's the scariest thing.
Speaker 3 (35:16):
I feel like this makes me want to do severance
right, like let's cut the infrom the out.
Speaker 4 (35:22):
No.
Speaker 3 (35:23):
I think what do I put the odds at?
Here's my bottom line.
I'm hopeful.
I do think that the staffingmodels that we have right now
are going to fundamentallychange.
I just think the companies whoare further along in this
journey with AI what they'retelling us is this is not a
(35:46):
technology that you essentiallylayer on to your existing
processes.
This is something that youactually have to go back to the
whiteboard and redesign the waythat you work, when you do it,
y'all.
If we don't think that's goingto fundamentally shift jobs,
responsibilities, tasks, thatit's not going to impact like
shaving off work, I think you'refoolish, right?
(36:08):
I think you're not payingattention if that's what you're
saying.
So what is the chance that ithas a pretty significant impact
on roles in the knowledgeeconomy?
I'm putting it at like 40, 45%,I guess, if I were going to put
a number to it.
So it feels real enough to methat we need to prepare for it.
I think this is a moment wherewe need to be as clear with the
(36:31):
employees who work for us andwho are coming to work for us as
we can right now, and we needto say look, things are changing
, they're going to change, andif you are not willing to learn
right.
The quote that's going aroundeverywhere is you know you're
not going to be replaced with AI, but you are going to be
(36:51):
replaced by somebody who uses AI, and I think that is the
sentiment that we need tocommunicate clearly, which is
don't live in fear that your jobis going to change or the AI is
going to take things away.
Be the designer of your destiny.
Where it's possible, takeagency and figure out some of
the ways that AI comes into yourwork and or how your work can
(37:12):
be designed, so that you're notsitting there surprised when
somebody shows up and says youknow, it turns out this was a
series of tasks.
60% of your job is actuallyreally easy to do with agentic
AI and so we're going to turnloose on that and we don't need
you anymore.
I think there are some folkswho are definitely going to get
that message.
The folks who aren't going tobe surprised are the ones who
(37:35):
are actually figuring out ways,trying to influence AI, using it
in their personal life and,frankly, more than anything else
, just willing to learn as itcomes, willing to sit down and
wrestle with it.
That's what we get paid for andI do think work is going to be.
This makes things morechallenging.
I mean, I'll bring up like oneother interesting fact.
(37:57):
I don't know if you all saw thepress release Maybe it was last
week, week before where Workdayis adding the capability of
tracking agents in the same waythat you would like track
employees.
They are, and I was wonderingwho was going to be out first on
this right.
Were we going to do that fromHR?
Were we going to do that fromIT?
You know we should think aboutour jobs as maybe hiring and
(38:21):
training agents, tracking agents, making sure the agents play
well in the HR space.
So look, it's coming, it'sgoing to have a real impact and
the question is not, you know,should I prepare it's?
What are you doing today to getready for it?
Are you learning, investing inyourself, building your own
talent, helping the people thatyou lead?
(38:42):
Build those skills, creating asandbox so they can play, so you
can lead on the future, insteadof getting run over by?
Speaker 4 (38:49):
it, love it, love it.
Thanks for bringing us backtowards the light.
I was laughing with Graham inour backroom conversation
because on our previous episodeI closed it with a question
about whether the American dreamis dead, which really took us
into a dark place, and thentoday I tried to close it with
whether AI is going toobliterate all knowledge work.
(39:09):
So I appreciate you ending uswith a message of hope, and I
guess I got to do some workpersonally here to figure out
why I'm in such a dark place.
Grant, do you have anything tosay?
Speaker 2 (39:23):
to close yeah, be the change you want to see in the
world, marty.
You know, I think I think youknow.
The easiest question, I think,is this one Matthew, so loved
our conversation.
Where can people find youonline?
Yeah, loved our conversation.
Speaker 3 (39:38):
Where can people find you online?
Yeah, linkedincom, slash inslash.
Matthew J Daniel, that's whereto find me, and you will find me
at Guild, at events, atpodcasts.
You'll see all that posted upthere and I would love to
connect with you directly thereand teach me something about
talent acquisition.
Speaker 2 (39:57):
I love it, love it.
Well, thank you, matthew.
We'll link everything in theshow notes, of course, and I
know you write a lot of contenttoo, so you know some great
articles.
If you just Google, matthew,you'll see them all over the
internet.
So thanks again for joining us,matthew.
It's been a great conversation,all right.
Thanks for tuning in.
As always, head on over tochangestateio or shoot us a note
(40:18):
on all the social media.
We'd love to hear from you andwe'll check you guys next week.
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