August 27, 2025 • 33 mins
Tim and Tom are joined by Ben Eubanks, Chief Research Officer at Lighthouse Research & Advisory, bestselling author of Artificial Intelligence for HR, and a leading thinker on the intersection of people, technology, and the future of work. Together they explore how AI is reshaping HR — not only in how the function operates day-to-day, but also in how it redefines HR’s outward-facing strategic role in organizations.
Learning more about Ben’s research and insights here: lhra.io
Read Nexthink's study on AI, HR, and IT here: https://nexthink.com/resource/its-new-mandate-the-science-of-productivity-part-2
Read about AI's impact on creativity here: https://techxplore.com/news/2024-10-explores-impact-llms-human-creativity.html
Book your ticket for Nexthink Experience Boston or London here: https://experience.nexthink.com/london
Learning more about Ben’s research and insights here: lhra.io
Read Nexthink's study on AI, HR, and IT here: https://nexthink.com/resource/its-new-mandate-the-science-of-productivity-part-2
Read about AI's impact on creativity here: https://techxplore.com/news/2024-10-explores-impact-llms-human-creativity.html
Book your ticket for Nexthink Experience Boston or London here: https://experience.nexthink.com/london
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:01):
Welcome it. Change Makers to the Deck Show with Tim
Flower and Tom McGraw. Let's get into it.
Speaker 2 (00:09):
And then change Makers. Tim and I are back together
on the show once again.
Speaker 3 (00:14):
How you doing, Tim, I'm good time. Yeah, we're just
catching up a little bit on some some PTO time
we each had. And uh, it's a we're recording this
on a Monday, so back in the saddle, so it's
good to good to reconnect with.
Speaker 2 (00:25):
The I'm recording this from from Ireland. I keep I
kept calling it. I learned for ages. If everyone is like,
which island do you go into?
Speaker 4 (00:33):
Okay, Ireland, You've got to add the extra hottle syllable
in the middle, And I got it. I got into
a shout at Tim to friend of the show Sarah, Yeah,
I saw who you know who has facilitated many wonderful
guests that we've had on the show.
Speaker 2 (00:49):
And and I know he's a listener because every now
and then she says, I like the episode you just did,
and so hopefully she's listening to this song becase we've
got to congratulate her on her on her wonderful wedding
in West Cork. Beautiful occasion, a beautiful hotel, beautiful, beautiful
landscape and beautiful weather, which is anyone who's been to
Westcourt knows is not is not a so bing shout
(01:12):
out to uh and and Mark her her husband. So
today onto our guest, him, onto our guest. We're joined
by someone who's been the forefront of exploring how AI
is reshaping the world of work, which is something we
do here quite often, of course, but this gentleman, Ben Ubanks.
Speaker 4 (01:30):
He does it from a perspective of HR. So very
very excited to talk to him. Ben is the chief
research officer at Lighthouse Research and Advisory and a decorated
and celebrated author and podcaster and public speaker.
Speaker 2 (01:46):
And we're just excited to talk to you. Ben. How
are you doing today?
Speaker 5 (01:48):
I'm doing really well, Tom, glad to be here. And
if you ask me how we sit here in the
Southern US, it's Ireland, so that would have been really
easy bout dellan nun.
Speaker 2 (01:58):
But what if it's an island is what are you corral?
Speaker 3 (02:01):
Maybe?
Speaker 2 (02:02):
Oh, it doesn't matter.
Speaker 4 (02:03):
Let's move on, listener, Shalli already well, look Ben, so
excited to talk to you, big big fan of your work.
You bring a very very fresh perspective to something we
spend a lot of time thinking about and talking about
here here on the deck show.
Speaker 2 (02:17):
Hey, look, it's it's obvious to say he like in it.
Speaker 4 (02:20):
Like anything, AI is going to have a like in it. Specifically, rather,
AI is going to have a dual impact on HR
because onmber one hand, it's going to change how HR
carries out its own work. On the other hand, it
has to reshape HR's outward facing role.
Speaker 2 (02:36):
In the business. Right, it's going to influence HR's own
strategy at the very highest level. Could you maybe update
our audience, who isn't your typical HR audience on what's
most significant in these different dimensions of change.
Speaker 5 (02:49):
The very first three words you said there in that question,
I think, will you tell it? It's like in it?
Speaker 3 (02:53):
Right?
Speaker 5 (02:54):
It work is divided to between these very compliance focused,
very pros like checklist sorts of things and other things
where that are high level strategy and impact and what
does this mean and unlock for us in terms of
opportunity and so for me, the perspective is HR is
divided the same way. We have this compliance piece, this
checklist piece, checking it off, just moving along the list.
(03:16):
We also have the strategy side of it. I was
talking to a leader of people analytics for a large
bank recently and he was telling me he's getting pressured
to adopt AI. And he said, they're telling me to
do it around our employee service delivery and how people
answer questions like, yeah, there's there's some good stuff there.
There's also opt curuity here on the strategy side, where
you can answer questions about how we can grow our talent,
(03:37):
how we can meet that business objective, how we can
meet this need. And so there's this sort of fibrication
there between the two different lenses of how that goes,
and I think it's not too similar from how I
teas thees that but doing the compliance things well may
get you little applause, But unlocking the strategy and opportunity
is where the real competitive advantage comes from for employers.
Speaker 2 (04:01):
When when you think about previous ways of digital transformation
that you've witnessed and thought about and analyzed and how
they affected HR strategically, what lessons, first of all, do
you feel do apply to this coming way AI driven
digital transformation And where exactly do you think the lessons
of the past will short in which ways do you see,
(04:22):
a AI transformation is something that's truly uncharted and if
you will, unprecedented, if at all, if.
Speaker 5 (04:29):
At all, oh my goodness, at all, it might they not.
So there's this a I think you might have heard of. No,
so I'll start with this. So when I was writing
the book Artificial Intelligence for HR and the second edition
and the third edition, I kept going back to the research.
I could find anything old or new that highlighted what
happens to work when this evolution comes through and automation
(04:51):
strips away things. And again, hundreds of years ago, mechanical
automation suddenly farming is easier. Great, okay, But today it's
digital automation. It's changing the work that we do, taking
pieces out that we had to do manually before. It
makes it easier for us. That automation compartment there is great.
That's been a thing for a long time. AI changes
that because it's not just about automation that we've done,
(05:12):
but it's about accelerating things, augmenting things, adapting work itself.
We are having to redefine how work it's done because
some things no longer have to be done by human
and in some cases we're all just thank goodness my
feet of urest for a moment. But in other cases
we're saying, now, what does this make possible? What can
I do now that I couldn't do before because I
was too busy just churn it away at these other
(05:33):
tasks and things. And I think that's the real opportunity
that we have now in front of us, is to
rethink that and what's possible. I think that's the big thing.
It's not just about doing other stuff faster, but giving
us new things we can do that in the past
we're just beyond our reach.
Speaker 3 (05:48):
And so Ben, I'll add my excitement to having on
the show. We've talked about this linkage between HR and
IT for a while, and having you here to share
some of your research and the lessons out of your books,
I think is going to be real big for the audience.
So welcome. You know, we've known for years now that
AI holds this tremendous promise for all sorts of enterprises.
(06:11):
But what do you see are the biggest risks with
AI in the workplace, both in terms of culture. So
I'll lay out a couple here and get my thoughts out.
There's this tremendous promise, but there are also angles where
it can be demonized. How dare you use AI to
create your content? And there's actually AI to detect whether
or not you used AI, And now there's AI to
(06:33):
make my AI production more human, so you can't detect it. Right,
this this back and forth swing on whether it's good
or whether it's bad. And we're also starting I'm starting
to sense some of this internal HR kind of responsibility
to manage the human competition in an enterprise. So what
role does HR play in anticipating and managing and hopefully
(06:59):
mitigating some of these back and forth plays in their
own enterprise.
Speaker 5 (07:05):
Well, if I could snap my fingers and every organization
had access to the same AI tools, the only differentiator
would be in your talent, your people, what they can do,
what they know, and how they do it. I think
that's the real thing. And so there are some very
real risks that are there. Everybody wanted to start out
with with bias and all the pieces of that, And
(07:25):
to me, like, what's interesting is, yes, AI could be
biased if it's programmed the way if it's the data
is trained on or or biased. Yes, but also I
can actually audit that I can't audit that manager in
my business who was always saying, you know what, I
really i'd like to you, I just can't hire a
woman for my team. I just can't you. They can't
cut it, And I can't audit that manager has something
(07:45):
going on in his head that's, you know, shutting that down.
I don't know AI. I can audit and say, hey, look,
it's looking at these indicators. It's turning them down because
they're women. We can fix that and change that. So
I think that's the bias piece. Yes, it's a risk,
but it's also auditible and changeable in a way that
it's not possible with humans. So for me, that's a risk,
but not the full stop, nothing goes forward. We all
(08:07):
have to be pulling our hairt and screaming and running
in circles kind of risk. The other one that gets
me though, the one that's come out more recently. There
was a study by the University of Toronto while back,
and they looked at humans who were using large language
models to do their work and to do some creative tasks,
and they gave them an actual assessment, not just some
questions how do you feel your opinion, but an actual
assessment of creativity, and the people who used large language
(08:31):
models CHAGUPT and others to do their work, their creativity
was lower than people who did not. And the part
that's most scary isn't that, it's that when they brought
them back a little bit later to test them again,
nobody got to use it this time. And that second
group who would use tativity, they were still less creative.
Their ideas were very narrow, very streamlined, very homogeneous, as
(08:52):
the term they use where they all start to sound
the same. But the brainstorming and the creativity from the
other group that had not done that, it was it
was broader, more novel ideas. More creativity was actually show
im proven in the research. So to me, that's the
part that gets me is humans picked the path of
least resistance. Our brains are wired to be lazy and
at the same time going that shortcut route for all
(09:13):
of our brainstorming, all of our creative thinking, not just
automating the simple tasks. When we start doing the higher
order tasks and using it to outsource our thinking, that's
going to start hurting us long term. And that's the
risk that I'm most concerned with because human behavior is
hard to change guys. It's really hard to change people,
and we're wired to take that easy path. So the
(09:34):
thing we're gonna have to do is very carefully, very
very intelligently put some limits around when and where those
are used, and determine which types of work can be
done that way in which we need to stay away
from because the short term win is not worth a
long term loss.
Speaker 3 (09:49):
It's really interesting research. I'm gonna I'll chat with you.
Maybe we can put in the speaker notes where folks
can get that research. Because as a semi creative person myself,
I feel like my creative ideas are actually augmented by
some AI collaboration. Right, it's and maybe this is maybe
this is collaboration with people versus creative collaboration with AI,
(10:12):
but it's it's a curious take. I do a lot
of my creative ideas I feel have have really taken
off with some of that, with some of that AI
back and forth. But I'll ruminate on that a little
bit more. But there's strong opinions on both sides even
to take this and step further that some of this
AI capability is actually going to take jobs, and if
(10:35):
those jobs become more siloed, less creative. It's an interesting
it's an interesting implication. But we're also at this kind
of we're the middle of also some talent scarcity right
in many areas that the there's there's an inability to
(10:58):
find the right people with the right talents. I'm curious
how you reconcile those two conundrums, right the it's going
to take my job, but we're gonna, uh, we don't
have the right talent to actually run AI models. How
do you reconcile and see those two things converging in
the future.
Speaker 5 (11:16):
The first thing I think of is there was a
study to my key research. I mean, maybe it's probably
not ten years ago, but it's it's been a while
now since the early days of AI being a conversation
and just in public. And they surveyed American workers said, hey,
how do you think that AI is going to change
work and change jobs? And it was something like, you know,
(11:36):
three quarters them said yes. I said, how many of
you think it's going to change your job? And you're
like no, no. Generally, you know, people are like, no,
it won't change my job, it's going to change everybody else's.
And so our brains have this like hardwired defense mechanism
and says, well, this is risky and scary, and look
at our horizon. I'll probably be okay because my I know,
my work is too creative for that. So that's that's
(11:57):
the first place my mind goes. So in in the
book I wrote Talent scarcity, it really looks at the
reasons that it's hard to find good quality of people.
You mentioned in some field, some professions. The lack of
skills there is very real. So a couple of different
thing we're trying to unpack this big question. Number one,
AI is taking tasks, not jobs right now, that's what's happening.
(12:19):
So someone if you have a marketing team and you
had a content person that was doing that as part
of their tasks. Some of the content things they were doing,
we can now do like that staff of a finger
with AI, and that person's tasks they were doing all
around that writing, creating, editing, researching, Those pieces of their
job go away. Now does a company get rid of
(12:39):
that person entirely and offload the rest of their work
to other people maybe, or do they somehow streamline that
job and change it. It depends on the company. Depends
on the culture of the budget, all the things. But
that's what's really happening. The task's not the job now,
that piece of it. Let's set that aside for a second.
One of the things that concerns me again, I'm the
HR nerd. I'm a data nerd. In most rooms, I
was almost an e commomy and decided to go to
(13:01):
HR instead. Still a study of human behavior every day.
And one of the things that I wrote about in
the book is there's this demographic cliff that's out there,
and if anyone has heard some of the stories around this,
they're pretty much all true. Every developed nation in the
world has a birth rate that's below replacement rates, so
they are steadily going to be shrinking. And we see
(13:21):
this in some countries that are very far down this path,
like Japan, where they don't have enough working people to
pay for the social security to take care of the
people who are already at retirement age, and that sort
of social structure breakdown is again lots of fun reading
on the weekends, but it gives you this idea of like,
there's a lot of fear there. There was a one
(13:43):
of the Russian Ministers of Work of labor a few
years ago was on the news saying, hey, when you
get a break from work, go pro create. That was
there on the news are saying this because they're trying
to make sure their citizens are creating enough people, because
they're worried about that. We're losing people to retirement every day,
so it's stretching the workforce, and so that's a real problem.
In the book, I talked about how AI, automation, robotics,
(14:05):
those sorts of things give us a way to potentially
close that gap in some way. But there's a problem
with that. When we look at the job growth in
the last few quarters. The jobs that are actually out
there are standing jobs, not sitting jobs, and AI is
really well suited to sitting jobs, standing jobs, home health,
I need a person there checking on someone in person,
making sure they're okay. We're building something in a plant.
(14:28):
We have things like retail. AI is not doing those
type of jobs that it can't right now. So there
could be an opportunity for that down the line, but
right now it's really affecting for those sitting jobs and
white collar work and not as much of those standing
jobs where we're still trying to hire people still trying
to bring them in and we still have the shortage.
It's a weird sort of labor market issue.
Speaker 2 (14:50):
It's bad news for us sit as Tim.
Speaker 5 (14:52):
Yeah, all of us are sitting as well. That's you know,
we have a standard or the rest of this.
Speaker 3 (14:57):
Yeah, can I is it job security if I push
my standing best at the top and start standing up
for the calls. Yeah. And so a lot of the
functions that we talk about here right, therapy, finance, feedback,
any consultative work We've talked about in other shows, where
(15:18):
knowledge and education are becoming free, so you can find
your answers a lot easier. I'm curious, as HR in
itself becomes more technical through AI adoption, how do they,
as an HR function avoid losing their core purpose keeping
people at the center of the strategy. What practices or
principles help maintain that balance.
Speaker 5 (15:40):
So we actually did a piece of research earlier this
year and we surveyed almost a thousand different organizations across
the globe asking them about their people practices. And I
know this is not an HR show, but there's a
very good tie into that question where they we asked
them what's more important? Is it more important? To be
data oriented, really thinking about the numbers, the evidence, the metrics,
those things, or is it more important to be people focused.
(16:04):
And we found is a company that picked one of
those two things versus the catch all you know, the
cheat answer, like both are important. If they picked one
or the other of those, their results were horror. Their
perspective is were more limited, their impact was less. And
so those teams that say it's about all the AI
(16:24):
is great, let's go do all the things, and we're
using that to sacrifice the connection with people. You just
to sacrifice the opportunity we have to serve people. Those
companies may get again that short term gain and look
like they're winning in a long term loss. It reminds
me of the Clarna story where they replaced hundreds of
their customer service agents with an algorithm with an AI tool.
(16:44):
They're like, look at us, We're great, and then a
year later like, oh yeah, we need people again. And
so they learned the hard way, and we're going to
see that pendulum swing too far. I think on the
talent side too, and you see that in some cases
where hey, this company automated their whole hiring process. There's
not a human to be heard or with or connected
to during that process, and when you go and you
look on Reddit and these other places, people like I
(17:05):
will never ever work in this company because that's terrible.
That's horrible. I need to connect with the human to
know if it's the right job for me. So for me,
the philosophical breakdown is do we use the technology to
keep people at arm's lengths or do we use the
technology to understand more about them so we can serve
them more deeply? And for hr people out there who
have that heart of service, they care about their teams,
I think that's where their strategy is going to lie.
(17:27):
Their best opportunity lies is they can now know more
about their people, not in the creepy stalker way, but
no more about their people, like what do they need
from us? How do we serve them better? What unique
benefits can we offer to Ben's family because they need
this thing right now from us versus Tim's family. They
need something different. And that level of understanding and awareness
that AI gives us is what's going to set those
(17:48):
companies apart that take this in the best positive direction.
Speaker 3 (17:53):
Just some free thought based on a reaction based on
some of the commentary it's not a far stress, which
if AI is taking accountability for hiring people, that AI
eventually takes accountability for firing people too. Right, we're in this.
If we don't get a manage on this soon, we're
going to be in a We're going to be in
a tough place. And I think there's enough smart people
(18:15):
that are seeing it. It's a matter now what do
we do? And in that regard, who takes accountability for it? Right?
Uh uh? Corporate functions are very easily siloed off. HR
only does HR, it does it, procurement does procurement, but
the rework the redesign of work that's AI driven. If
(18:37):
a business wants to take on those functions like you're
talking about of how does it? How do we redesign
the hiring function without just turning it all over to AI?
How do we use AI to redesign that function? It
sits squarely in the middle of it, and HR one
silo can't do it alone or without the other. So
how do those two functions converge to meet this moment?
Speaker 5 (19:01):
I think we armed both sides in a deathmatch and
let seek standing after we're all done that. This seems
likely easiest for that. I think a lot of sharpening
my battle acts over here, So I'm ready to I'm
ready for it. On said it, it's finally someone knows.
So I've always been an advocate that HR and ID
stronger ties. So we did a piece of research a
(19:22):
couple of years ago now where we surveyed an audience
of HR leaders and IT leaders around some technology implementations
relevant to HR tech. But to me, the the interesting
takeaway overall across the board every respondent when we said
is your organization ready for what's next? Are you adaptable?
Are you ready for the future. The ones that said yes,
we asked them about the technologies and tools are using
(19:43):
to manage their people. How big of a role does
that play? Ninety seven percent of people said it plays
a key role. And then being agile and responsive as
an organization. And to me, that blows me away because
statistically that never happens. That's like getting one hundred people
in a room and saying what shweet for a lot
much and ninetie Ever for some people said the same things.
That's ridiculous to even saying a load, But that happened
(20:06):
in the research, So to me, they gives me strong
hope that that's possible. The thing that got me though
in the research we started looking at the two different audiences.
When we asked about implementations, it generally said, hey, listen,
we're here, we're ready, put me in coach. I'm ready
to help out whatever you need. We've got this extensive experience,
we know what we're doing. Just let us let us help.
(20:26):
And HR's general response and that was, we'll call you
if we need you. Strangely enough, later on in the survey,
HR is much more likely than it to say, we
see these problems pop up in implantations, we're not sure
how to deal with them, and they were unexpected, and
so you're like, you've got a great advisor and expert
right here saying let me know we need help, and
you ignore them, and then later on you say, man,
(20:46):
I wish I would have gotten some help. So I'm
hoping those sorts of messages, those are the stories help
our friends across the aisle come together, because the opportunity
there when we do see this together, you see organizations
that are trying to combine those roles, and whether that's
a good decision or not, we can we could probably
debate that, but I do think the opportunity is there.
All Right, one more thing I'll tell you on that,
(21:08):
just to give you a picture of how this could be.
So a couple of years ago, when everyone was hiring
in a frenzy, you couldn't pay people enough money to
get them to come to your organization. It was wild.
I put together this panel with a compensation leader and
a recruiting leader, because in every conversation I was here
with recruiting, they're like, comp want adjust the pay rates,
and they're they're they're out of their minds. So what
(21:30):
do they think they're doing. We're losing good people? And
I thought the comp leaders are saying, what is wrong
with the people in recruiting. They don't understand we have budgets,
we have we have controls, we have to you know,
may be fair. They don't know what's going on. And
so each of them was sort of saying the same thing.
We want to be competitive, we want to be fair,
we want to treat people right. But they were both
accountble for different things. They both had different objectives in
(21:51):
the moment that we're trying to accomplish. But at the
end of the day, if I pressed them, they would say,
we both want to make sure we're doing the right
thing to set us up for success long term and
hiring the best peace people, and so the same sort
of thing there. If we could adapt that to this,
IT leaders and HR leaders saying get together with your
own counterpart and your own organization, anyone listen to me
right now and talk to them about what they're accountable to,
(22:14):
what things they're prioritizing, what they're worried about. Because you
would be surprised how often something comes across and there's
an overlap where you can step in and support and
serve and build a bridge versus building a barrier. That's
what I think is the real opportunity for us.
Speaker 3 (22:28):
So who takes the lead right not just on governance
for AI, but all the other operational aspects of this.
Does HR report to it or vice versa? Is it
cross functional body, is it one leader or organization that
owns both. What's the operational the organizational model look like
in terms of ownership and leadership. You see some organizations
(22:49):
that are actually hiring someone to lead AI in the business,
and I don't think that's a bad thing to do,
to have someone with that perspective across all the different
disciplines and functions and roles and use cases and opportunity
there within its own realm. Though, HR generally is trying
to think about again, our problems are hiring, retention, benefits, composition.
Those sorts of things are our priorities for us. It's
(23:11):
problems are not those same problems, and so we need
to have some ownership within our our space as an
HR function.
Speaker 5 (23:18):
Yes, it's like global governance and local flexibility as sort
of how I see companies implement policies like here's what
it means across the globe, but within your local region,
we know that you can't work on this day of
the week because of religious holidays, so we'll give you
flexibility to accommodate that. And the same thing is true here.
We need this big picture vision. We need to get
together and say this is who we want to be.
Do we want to be a company that automates all
(23:42):
the people, roles, gets everybody out of the business, tries
to just go straight technology. What do we want of
those companies that relies on our competitive advantage, which is
our people, And we're going to use those as our
differentiator and You've said it earlier. We're going to use
people to actually create content what no, really, Yes, that
will be our that will be our advantage over someone
else because they're creating things that again very nearro very homogeneous,
(24:05):
they're all going to start to sound the same. We're
going to use our people for the unique stories they
can tell, the differentiators, the connections they can make with
our audience. And so I think that's the opportunity really is. Yes,
has overarching sort of perspective, whether it is having a
person dedicated to it or having a counsel around that.
But within your own disciplines, you're going to have to
have the flexibility because the problems you're trying to solve
(24:26):
day to day are different than the problems trying to
be solved from marketing or sales or HR in this case.
Speaker 2 (24:32):
And do you think that might be a part of
a role for HR as a management in its management
of employer brand? You know, like this is the kind
of organization where you know, AI is kept at this level.
Do you know what I mean like weight, weight based,
a human centric policy towards hiring, et cetera. I mean
and and and and how does how does hr play
(24:53):
that role in communicating externally about that brand.
Speaker 5 (24:57):
I have actually not thought about that, and I think
that's a to question. Honestly, you see companies talking about
their fair treatment of people you think their company. You
see companies talking about what it's like to work here.
They share all these kind of details transparently in their brand,
trying to attract the right people, trying to discourage the
people who are like, oh, they work hard, that's a
fast paced I want some the solar pace. I'm gonna
(25:19):
find another company to work for. They're using their brands
for those things. I don't think it's a far cry
to say we should be talking about how we see
AI as a part of the evolving model of work
and the evolving nature of work, and say we expect
you to come here and be able to use those things.
Use it during your hiring process. You're gonna be using
it at work every day. We want you to push
the boundaries what's possible or Hey, we're gonna be using
(25:39):
this the tool just like we would any other tool, email,
whatever else. But also we are going to prioritize and
emphasize and lean on the human as the key part
of this because there are things that transparently AI can't do.
AI can't take responsibility for things. AI can't build relationships
with other people. A I can't mentor others, and those
(26:00):
other things that it can't do is where we should
be spending more of our time. I've had this weird
sort of love hate conversation in the last few years
with that discussion around AI being, Oh, we don't do
all the routine stuff, so we can be more strategic
after like we'll put my hands on my hips like
a superhero pose strategic. And people have said that so
many times, like Okay, what do you mean by that?
(26:21):
We actually have data. We actually collected data on talent
acquisition leaders, people who are responsible for hiring in their businesses,
asking them, are you more efficient? Are you using AI?
Speaker 3 (26:30):
Okay?
Speaker 5 (26:31):
If so, yes to both of those questions. What are
you doing with that freed up time? Are you sitting
around playing games on Facebook or watching TikTok videos or
are you doing something useful? And what we find is
they're spending more time building relationships with candidates. So we
talked about this, right that key connection with a candidate
out there, not automating that they're spending more time building
relations with stakeholders. I've heard it is a stakeholder of
(26:54):
HR and vice versa, right, And they're also spending more
time proving to the business the value what they're doing
every day. So they're leaning those other areas that right
now they're like, that's just out of my grasp. I
can't reach it. And once they have that time for it,
they lean in. So we have some data around that,
And to me, that's that's encouraging because I was a
little bit skeptical. It was like, we'll be more strategic,
what does they even mean? And now I've gotten to
(27:14):
the data of proving that, yes, that's happening in this role,
and if it's happening here, the opportunities there in other
roles as well.
Speaker 4 (27:22):
I quite like your contempt for the word strategic, ben
is it is? It is a great hollow word in business,
isn't it?
Speaker 3 (27:29):
Yes?
Speaker 5 (27:30):
Again, every throws it around.
Speaker 3 (27:32):
We gotta let's back it up. What's some proof?
Speaker 4 (27:34):
Yeah, So you know, use that word to modernization earlier
as a potential consequence of lazy or excessive ai US,
you know, And it strikes me that that danger isn't
isn't I don't know if business is fully realized the
dimensions of that danger and what it could mean for them,
right like, because what could be worse for a business
(27:57):
than being completely homogenized.
Speaker 2 (27:58):
And against this competitive you lose your entire competitive edge.
Rest of all, do you think that that's true? Second
of all, does a char's role become therefore more hands on?
Speaker 3 (28:09):
Hips?
Speaker 2 (28:09):
It's true?
Speaker 5 (28:10):
Tag, So let's see, I do believe that. If ever here,
I'll give you an experiment. So we were talking with
one of our clients. Basically did an experiments across the
fortune one hundred, looked at all of their career sites,
pulled them together, did an analysis of the keywords, how
they talked about their cultures, all those things, and what
(28:31):
they found was substantially the majority of them. You could
have swapped out the logo and it would have all
sounded pretty much the same. They all stand for the
same things, they all believe the same things. There's no
difference between them. And that's not employer branding, that's employer blanding.
It all sounds exactly the same. There's no excitement, there's
no novelty. There's no reason for me to go work
(28:51):
here or there, and We did an experiment. I was
speaking at an events in for a group in India recently,
and I pulled together the age old debates here in
the States Coke versus Pepsi, and so I grabbed the
job from Coke India and Coke PEPs and Pepsi India
and put them together and showed the different jobs and
was asking the audience like, which one of these companies
(29:11):
want would you want to apply for? And so I'm
going through showing the job, posting themselves and no other
details from the website. You can't even tell eight clicks
in scrolling endlessly on the Pepsi one, who the company is.
It doesn't mention the company, it doesn't tell what they do.
You start reading the Coke one and it's in red fonts,
got their logo or their colors on it, and they
started talking about here's how we treat people at Coke.
(29:33):
He's important to us at co Cola. And so they're
going through those things. That sort of thing is already
happening where companies are trying to find ways to stand out,
and the best ones are doing a good job of
emphasizing that human that makes them unique, that human connection
that makes them different than everybody else. So I do
think that's an opportunity, and yes, HR has to be
playing a role in that, it's not We sometimes forget
(29:56):
that hiring an attraction is not just about pursuing a candidate,
but they have to look at us and say, I
want what you were offering me. It's not a one
way streets. And when you forget that, you think, well,
do you start to hear things like, well, they should
just be lucky we're even considering them. Let's be lucky
to have a job. And in the real world those
sorts of things don't don't really fly.
Speaker 2 (30:17):
M Okay, last question for you, Ben, wonderful, wonderful discussion.
But if you if you look ten years ahead, do
you imagine close.
Speaker 4 (30:25):
Your eyes for us, Ben, hand on it, close your eyes.
What is the most set, surprising, surprising, underappreciated way that
you think AI is going to reshape the world of HL.
Speaker 5 (30:36):
Specifically, I'm going to tell you a quick story and
then I'll then want to answer your question with part
of that story. So one of my favorite examples to
give when I'm speaking, as I talk about years ago,
I mean years and years and years ago, there was
this fever that was rampaging, and the doctors were trying
(30:56):
to figure out how to even diagnose it. They had
no clue what to do, and this doctor said, hey, listen,
I'm one hundred percent I can diagnose it every single time.
And everybody else was like the medical profession said, how
is this impossible? We can't figure it out. So they
all come together said come on over. So they all
come over there and they're sitting around there watching this doctor.
He's like, here's what I do. Here's how I diagnose it.
So he reaches over into the mouth of a person
(31:18):
who's in fact and they feels their tongue okay, And
then he reaches over into the mouth of a person
who's not sure and he feels their tongue. Immediately thereafter,
he's like, yep, this person has it too, And everybody
around him says, WHOA, that's amazing. We never thought to
do that. Looking back now, we know that's ridiculous and
terrible as a medical practice. You're giving the other person
the disease the second you put your hand in their mouth.
(31:40):
But at the time they thought it was revolutionary and
amazing and brilliant that this doctor had discovered a way
to do this. I do not want us to end
up ten years down the line, twenty years down the line,
thirty years on the line, looking back saying how did
we let AI get to where it was? Talk about
that pendle on the swing earlier? How do we get
it let it get so far that we can never
bring it back to some level, some degree of humanity
(32:02):
and connection. Do I think AI is eating some jobs?
Speaker 2 (32:05):
Yes?
Speaker 5 (32:05):
Do I think AI is changing the tasks where we
need to be folksing gone at work? Yes? But I
really think the biggest thing for me is we have
to be intentional. We have to be intelligent. We have
to recognize our faults as humans in our reliance on
the easy way, the thing we've always known, the way
we've always done it. That's our brains are wired, and
(32:27):
our grooves and our brain are designed to do that
and follow that path. We have to do it differently.
So for me, the surprising way is that we're going
to see all this change and we're going to be
surprised by it. That's what I hope doesn't happen as
we're thinking about how this reshapes HR and work. More broadly,
I hope we are more intentional hands on the wheel
because all ready to early find is coming out from
Harvard and other organizations say that we are perfectly content
(32:50):
on the AI. Just make decisions on its own when
we think it's capable, even when it's not.
Speaker 2 (32:55):
M so interesting, but I love it. Great perspective, pleasure
talking to you. Do share, do share a link to
that research. We're going to put it in the show notes.
We'll also put links to your LinkedIn and and your
books anything else you would like to like to feature
here where we people can reach out to your connect
with you, et cetera.
Speaker 5 (33:15):
The best way to find some of the research or
send your HR team to find the research is lhr
dot io. That's the website and that's where all of
our guests have is shared and published for your charge.
Speaker 4 (33:24):
Linked link linked to that website in the show notes.
Ladies and gentlemen, Thank you so much, Benn. It's been
a pleasure. Thank you guys.
Speaker 1 (33:32):
To make sure that you never miss an episode, subscribe
to the show in Apple Podcasts, Spotify, or your favorite
podcast player, and if you're listening on Apple podcasts, make
sure to leave a rating of the show. Just have
the number of stars you think the podcast deserves. If
you'd like to learn more about how next Thing can
help you improve your digital employee experience, head over to
next think dot com.
Speaker 5 (33:53):
Thank you so much for listening.
Speaker 1 (33:55):
Until next time,
Welcome it. Change Makers to the Deck Show with Tim
Flower and Tom McGraw. Let's get into it.
Speaker 2 (00:09):
And then change Makers. Tim and I are back together
on the show once again.
Speaker 3 (00:14):
How you doing, Tim, I'm good time. Yeah, we're just
catching up a little bit on some some PTO time
we each had. And uh, it's a we're recording this
on a Monday, so back in the saddle, so it's
good to good to reconnect with.
Speaker 2 (00:25):
The I'm recording this from from Ireland. I keep I
kept calling it. I learned for ages. If everyone is like,
which island do you go into?
Speaker 4 (00:33):
Okay, Ireland, You've got to add the extra hottle syllable
in the middle, And I got it. I got into
a shout at Tim to friend of the show Sarah, Yeah,
I saw who you know who has facilitated many wonderful
guests that we've had on the show.
Speaker 2 (00:49):
And and I know he's a listener because every now
and then she says, I like the episode you just did,
and so hopefully she's listening to this song becase we've
got to congratulate her on her on her wonderful wedding
in West Cork. Beautiful occasion, a beautiful hotel, beautiful, beautiful
landscape and beautiful weather, which is anyone who's been to
Westcourt knows is not is not a so bing shout
(01:12):
out to uh and and Mark her her husband. So
today onto our guest, him, onto our guest. We're joined
by someone who's been the forefront of exploring how AI
is reshaping the world of work, which is something we
do here quite often, of course, but this gentleman, Ben Ubanks.
Speaker 4 (01:30):
He does it from a perspective of HR. So very
very excited to talk to him. Ben is the chief
research officer at Lighthouse Research and Advisory and a decorated
and celebrated author and podcaster and public speaker.
Speaker 2 (01:46):
And we're just excited to talk to you. Ben. How
are you doing today?
Speaker 5 (01:48):
I'm doing really well, Tom, glad to be here. And
if you ask me how we sit here in the
Southern US, it's Ireland, so that would have been really
easy bout dellan nun.
Speaker 2 (01:58):
But what if it's an island is what are you corral?
Speaker 3 (02:01):
Maybe?
Speaker 2 (02:02):
Oh, it doesn't matter.
Speaker 4 (02:03):
Let's move on, listener, Shalli already well, look Ben, so
excited to talk to you, big big fan of your work.
You bring a very very fresh perspective to something we
spend a lot of time thinking about and talking about
here here on the deck show.
Speaker 2 (02:17):
Hey, look, it's it's obvious to say he like in it.
Speaker 4 (02:20):
Like anything, AI is going to have a like in it. Specifically, rather,
AI is going to have a dual impact on HR
because onmber one hand, it's going to change how HR
carries out its own work. On the other hand, it
has to reshape HR's outward facing role.
Speaker 2 (02:36):
In the business. Right, it's going to influence HR's own
strategy at the very highest level. Could you maybe update
our audience, who isn't your typical HR audience on what's
most significant in these different dimensions of change.
Speaker 5 (02:49):
The very first three words you said there in that question,
I think, will you tell it? It's like in it?
Speaker 3 (02:53):
Right?
Speaker 5 (02:54):
It work is divided to between these very compliance focused,
very pros like checklist sorts of things and other things
where that are high level strategy and impact and what
does this mean and unlock for us in terms of
opportunity and so for me, the perspective is HR is
divided the same way. We have this compliance piece, this
checklist piece, checking it off, just moving along the list.
(03:16):
We also have the strategy side of it. I was
talking to a leader of people analytics for a large
bank recently and he was telling me he's getting pressured
to adopt AI. And he said, they're telling me to
do it around our employee service delivery and how people
answer questions like, yeah, there's there's some good stuff there.
There's also opt curuity here on the strategy side, where
you can answer questions about how we can grow our talent,
(03:37):
how we can meet that business objective, how we can
meet this need. And so there's this sort of fibrication
there between the two different lenses of how that goes,
and I think it's not too similar from how I
teas thees that but doing the compliance things well may
get you little applause, But unlocking the strategy and opportunity
is where the real competitive advantage comes from for employers.
Speaker 2 (04:01):
When when you think about previous ways of digital transformation
that you've witnessed and thought about and analyzed and how
they affected HR strategically, what lessons, first of all, do
you feel do apply to this coming way AI driven
digital transformation And where exactly do you think the lessons
of the past will short in which ways do you see,
(04:22):
a AI transformation is something that's truly uncharted and if
you will, unprecedented, if at all, if.
Speaker 5 (04:29):
At all, oh my goodness, at all, it might they not.
So there's this a I think you might have heard of. No,
so I'll start with this. So when I was writing
the book Artificial Intelligence for HR and the second edition
and the third edition, I kept going back to the research.
I could find anything old or new that highlighted what
happens to work when this evolution comes through and automation
(04:51):
strips away things. And again, hundreds of years ago, mechanical
automation suddenly farming is easier. Great, okay, But today it's
digital automation. It's changing the work that we do, taking
pieces out that we had to do manually before. It
makes it easier for us. That automation compartment there is great.
That's been a thing for a long time. AI changes
that because it's not just about automation that we've done,
(05:12):
but it's about accelerating things, augmenting things, adapting work itself.
We are having to redefine how work it's done because
some things no longer have to be done by human
and in some cases we're all just thank goodness my
feet of urest for a moment. But in other cases
we're saying, now, what does this make possible? What can
I do now that I couldn't do before because I
was too busy just churn it away at these other
(05:33):
tasks and things. And I think that's the real opportunity
that we have now in front of us, is to
rethink that and what's possible. I think that's the big thing.
It's not just about doing other stuff faster, but giving
us new things we can do that in the past
we're just beyond our reach.
Speaker 3 (05:48):
And so Ben, I'll add my excitement to having on
the show. We've talked about this linkage between HR and
IT for a while, and having you here to share
some of your research and the lessons out of your books,
I think is going to be real big for the audience.
So welcome. You know, we've known for years now that
AI holds this tremendous promise for all sorts of enterprises.
(06:11):
But what do you see are the biggest risks with
AI in the workplace, both in terms of culture. So
I'll lay out a couple here and get my thoughts out.
There's this tremendous promise, but there are also angles where
it can be demonized. How dare you use AI to
create your content? And there's actually AI to detect whether
or not you used AI, And now there's AI to
(06:33):
make my AI production more human, so you can't detect it. Right,
this this back and forth swing on whether it's good
or whether it's bad. And we're also starting I'm starting
to sense some of this internal HR kind of responsibility
to manage the human competition in an enterprise. So what
role does HR play in anticipating and managing and hopefully
(06:59):
mitigating some of these back and forth plays in their
own enterprise.
Speaker 5 (07:05):
Well, if I could snap my fingers and every organization
had access to the same AI tools, the only differentiator
would be in your talent, your people, what they can do,
what they know, and how they do it. I think
that's the real thing. And so there are some very
real risks that are there. Everybody wanted to start out
with with bias and all the pieces of that, And
(07:25):
to me, like, what's interesting is, yes, AI could be
biased if it's programmed the way if it's the data
is trained on or or biased. Yes, but also I
can actually audit that I can't audit that manager in
my business who was always saying, you know what, I
really i'd like to you, I just can't hire a
woman for my team. I just can't you. They can't
cut it, And I can't audit that manager has something
(07:45):
going on in his head that's, you know, shutting that down.
I don't know AI. I can audit and say, hey, look,
it's looking at these indicators. It's turning them down because
they're women. We can fix that and change that. So
I think that's the bias piece. Yes, it's a risk,
but it's also auditible and changeable in a way that
it's not possible with humans. So for me, that's a risk,
but not the full stop, nothing goes forward. We all
(08:07):
have to be pulling our hairt and screaming and running
in circles kind of risk. The other one that gets
me though, the one that's come out more recently. There
was a study by the University of Toronto while back,
and they looked at humans who were using large language
models to do their work and to do some creative tasks,
and they gave them an actual assessment, not just some
questions how do you feel your opinion, but an actual
assessment of creativity, and the people who used large language
(08:31):
models CHAGUPT and others to do their work, their creativity
was lower than people who did not. And the part
that's most scary isn't that, it's that when they brought
them back a little bit later to test them again,
nobody got to use it this time. And that second
group who would use tativity, they were still less creative.
Their ideas were very narrow, very streamlined, very homogeneous, as
(08:52):
the term they use where they all start to sound
the same. But the brainstorming and the creativity from the
other group that had not done that, it was it
was broader, more novel ideas. More creativity was actually show
im proven in the research. So to me, that's the
part that gets me is humans picked the path of
least resistance. Our brains are wired to be lazy and
at the same time going that shortcut route for all
(09:13):
of our brainstorming, all of our creative thinking, not just
automating the simple tasks. When we start doing the higher
order tasks and using it to outsource our thinking, that's
going to start hurting us long term. And that's the
risk that I'm most concerned with because human behavior is
hard to change guys. It's really hard to change people,
and we're wired to take that easy path. So the
(09:34):
thing we're gonna have to do is very carefully, very
very intelligently put some limits around when and where those
are used, and determine which types of work can be
done that way in which we need to stay away
from because the short term win is not worth a
long term loss.
Speaker 3 (09:49):
It's really interesting research. I'm gonna I'll chat with you.
Maybe we can put in the speaker notes where folks
can get that research. Because as a semi creative person myself,
I feel like my creative ideas are actually augmented by
some AI collaboration. Right, it's and maybe this is maybe
this is collaboration with people versus creative collaboration with AI,
(10:12):
but it's it's a curious take. I do a lot
of my creative ideas I feel have have really taken
off with some of that, with some of that AI
back and forth. But I'll ruminate on that a little
bit more. But there's strong opinions on both sides even
to take this and step further that some of this
AI capability is actually going to take jobs, and if
(10:35):
those jobs become more siloed, less creative. It's an interesting
it's an interesting implication. But we're also at this kind
of we're the middle of also some talent scarcity right
in many areas that the there's there's an inability to
(10:58):
find the right people with the right talents. I'm curious
how you reconcile those two conundrums, right the it's going
to take my job, but we're gonna, uh, we don't
have the right talent to actually run AI models. How
do you reconcile and see those two things converging in
the future.
Speaker 5 (11:16):
The first thing I think of is there was a
study to my key research. I mean, maybe it's probably
not ten years ago, but it's it's been a while
now since the early days of AI being a conversation
and just in public. And they surveyed American workers said, hey,
how do you think that AI is going to change
work and change jobs? And it was something like, you know,
(11:36):
three quarters them said yes. I said, how many of
you think it's going to change your job? And you're
like no, no. Generally, you know, people are like, no,
it won't change my job, it's going to change everybody else's.
And so our brains have this like hardwired defense mechanism
and says, well, this is risky and scary, and look
at our horizon. I'll probably be okay because my I know,
my work is too creative for that. So that's that's
(11:57):
the first place my mind goes. So in in the
book I wrote Talent scarcity, it really looks at the
reasons that it's hard to find good quality of people.
You mentioned in some field, some professions. The lack of
skills there is very real. So a couple of different
thing we're trying to unpack this big question. Number one,
AI is taking tasks, not jobs right now, that's what's happening.
(12:19):
So someone if you have a marketing team and you
had a content person that was doing that as part
of their tasks. Some of the content things they were doing,
we can now do like that staff of a finger
with AI, and that person's tasks they were doing all
around that writing, creating, editing, researching, Those pieces of their
job go away. Now does a company get rid of
(12:39):
that person entirely and offload the rest of their work
to other people maybe, or do they somehow streamline that
job and change it. It depends on the company. Depends
on the culture of the budget, all the things. But
that's what's really happening. The task's not the job now,
that piece of it. Let's set that aside for a second.
One of the things that concerns me again, I'm the
HR nerd. I'm a data nerd. In most rooms, I
was almost an e commomy and decided to go to
(13:01):
HR instead. Still a study of human behavior every day.
And one of the things that I wrote about in
the book is there's this demographic cliff that's out there,
and if anyone has heard some of the stories around this,
they're pretty much all true. Every developed nation in the
world has a birth rate that's below replacement rates, so
they are steadily going to be shrinking. And we see
(13:21):
this in some countries that are very far down this path,
like Japan, where they don't have enough working people to
pay for the social security to take care of the
people who are already at retirement age, and that sort
of social structure breakdown is again lots of fun reading
on the weekends, but it gives you this idea of like,
there's a lot of fear there. There was a one
(13:43):
of the Russian Ministers of Work of labor a few
years ago was on the news saying, hey, when you
get a break from work, go pro create. That was
there on the news are saying this because they're trying
to make sure their citizens are creating enough people, because
they're worried about that. We're losing people to retirement every day,
so it's stretching the workforce, and so that's a real problem.
In the book, I talked about how AI, automation, robotics,
(14:05):
those sorts of things give us a way to potentially
close that gap in some way. But there's a problem
with that. When we look at the job growth in
the last few quarters. The jobs that are actually out
there are standing jobs, not sitting jobs, and AI is
really well suited to sitting jobs, standing jobs, home health,
I need a person there checking on someone in person,
making sure they're okay. We're building something in a plant.
(14:28):
We have things like retail. AI is not doing those
type of jobs that it can't right now. So there
could be an opportunity for that down the line, but
right now it's really affecting for those sitting jobs and
white collar work and not as much of those standing
jobs where we're still trying to hire people still trying
to bring them in and we still have the shortage.
It's a weird sort of labor market issue.
Speaker 2 (14:50):
It's bad news for us sit as Tim.
Speaker 5 (14:52):
Yeah, all of us are sitting as well. That's you know,
we have a standard or the rest of this.
Speaker 3 (14:57):
Yeah, can I is it job security if I push
my standing best at the top and start standing up
for the calls. Yeah. And so a lot of the
functions that we talk about here right, therapy, finance, feedback,
any consultative work We've talked about in other shows, where
(15:18):
knowledge and education are becoming free, so you can find
your answers a lot easier. I'm curious, as HR in
itself becomes more technical through AI adoption, how do they,
as an HR function avoid losing their core purpose keeping
people at the center of the strategy. What practices or
principles help maintain that balance.
Speaker 5 (15:40):
So we actually did a piece of research earlier this
year and we surveyed almost a thousand different organizations across
the globe asking them about their people practices. And I
know this is not an HR show, but there's a
very good tie into that question where they we asked
them what's more important? Is it more important? To be
data oriented, really thinking about the numbers, the evidence, the metrics,
those things, or is it more important to be people focused.
(16:04):
And we found is a company that picked one of
those two things versus the catch all you know, the
cheat answer, like both are important. If they picked one
or the other of those, their results were horror. Their
perspective is were more limited, their impact was less. And
so those teams that say it's about all the AI
(16:24):
is great, let's go do all the things, and we're
using that to sacrifice the connection with people. You just
to sacrifice the opportunity we have to serve people. Those
companies may get again that short term gain and look
like they're winning in a long term loss. It reminds
me of the Clarna story where they replaced hundreds of
their customer service agents with an algorithm with an AI tool.
(16:44):
They're like, look at us, We're great, and then a
year later like, oh yeah, we need people again. And
so they learned the hard way, and we're going to
see that pendulum swing too far. I think on the
talent side too, and you see that in some cases
where hey, this company automated their whole hiring process. There's
not a human to be heard or with or connected
to during that process, and when you go and you
look on Reddit and these other places, people like I
(17:05):
will never ever work in this company because that's terrible.
That's horrible. I need to connect with the human to
know if it's the right job for me. So for me,
the philosophical breakdown is do we use the technology to
keep people at arm's lengths or do we use the
technology to understand more about them so we can serve
them more deeply? And for hr people out there who
have that heart of service, they care about their teams,
I think that's where their strategy is going to lie.
(17:27):
Their best opportunity lies is they can now know more
about their people, not in the creepy stalker way, but
no more about their people, like what do they need
from us? How do we serve them better? What unique
benefits can we offer to Ben's family because they need
this thing right now from us versus Tim's family. They
need something different. And that level of understanding and awareness
that AI gives us is what's going to set those
(17:48):
companies apart that take this in the best positive direction.
Speaker 3 (17:53):
Just some free thought based on a reaction based on
some of the commentary it's not a far stress, which
if AI is taking accountability for hiring people, that AI
eventually takes accountability for firing people too. Right, we're in this.
If we don't get a manage on this soon, we're
going to be in a We're going to be in
a tough place. And I think there's enough smart people
(18:15):
that are seeing it. It's a matter now what do
we do? And in that regard, who takes accountability for it? Right?
Uh uh? Corporate functions are very easily siloed off. HR
only does HR, it does it, procurement does procurement, but
the rework the redesign of work that's AI driven. If
(18:37):
a business wants to take on those functions like you're
talking about of how does it? How do we redesign
the hiring function without just turning it all over to AI?
How do we use AI to redesign that function? It
sits squarely in the middle of it, and HR one
silo can't do it alone or without the other. So
how do those two functions converge to meet this moment?
Speaker 5 (19:01):
I think we armed both sides in a deathmatch and
let seek standing after we're all done that. This seems
likely easiest for that. I think a lot of sharpening
my battle acts over here, So I'm ready to I'm
ready for it. On said it, it's finally someone knows.
So I've always been an advocate that HR and ID
stronger ties. So we did a piece of research a
(19:22):
couple of years ago now where we surveyed an audience
of HR leaders and IT leaders around some technology implementations
relevant to HR tech. But to me, the the interesting
takeaway overall across the board every respondent when we said
is your organization ready for what's next? Are you adaptable?
Are you ready for the future. The ones that said yes,
we asked them about the technologies and tools are using
(19:43):
to manage their people. How big of a role does
that play? Ninety seven percent of people said it plays
a key role. And then being agile and responsive as
an organization. And to me, that blows me away because
statistically that never happens. That's like getting one hundred people
in a room and saying what shweet for a lot
much and ninetie Ever for some people said the same things.
That's ridiculous to even saying a load, But that happened
(20:06):
in the research, So to me, they gives me strong
hope that that's possible. The thing that got me though
in the research we started looking at the two different audiences.
When we asked about implementations, it generally said, hey, listen,
we're here, we're ready, put me in coach. I'm ready
to help out whatever you need. We've got this extensive experience,
we know what we're doing. Just let us let us help.
(20:26):
And HR's general response and that was, we'll call you
if we need you. Strangely enough, later on in the survey,
HR is much more likely than it to say, we
see these problems pop up in implantations, we're not sure
how to deal with them, and they were unexpected, and
so you're like, you've got a great advisor and expert
right here saying let me know we need help, and
you ignore them, and then later on you say, man,
(20:46):
I wish I would have gotten some help. So I'm
hoping those sorts of messages, those are the stories help
our friends across the aisle come together, because the opportunity
there when we do see this together, you see organizations
that are trying to combine those roles, and whether that's
a good decision or not, we can we could probably
debate that, but I do think the opportunity is there.
All Right, one more thing I'll tell you on that,
(21:08):
just to give you a picture of how this could be.
So a couple of years ago, when everyone was hiring
in a frenzy, you couldn't pay people enough money to
get them to come to your organization. It was wild.
I put together this panel with a compensation leader and
a recruiting leader, because in every conversation I was here
with recruiting, they're like, comp want adjust the pay rates,
and they're they're they're out of their minds. So what
(21:30):
do they think they're doing. We're losing good people? And
I thought the comp leaders are saying, what is wrong
with the people in recruiting. They don't understand we have budgets,
we have we have controls, we have to you know,
may be fair. They don't know what's going on. And
so each of them was sort of saying the same thing.
We want to be competitive, we want to be fair,
we want to treat people right. But they were both
accountble for different things. They both had different objectives in
(21:51):
the moment that we're trying to accomplish. But at the
end of the day, if I pressed them, they would say,
we both want to make sure we're doing the right
thing to set us up for success long term and
hiring the best peace people, and so the same sort
of thing there. If we could adapt that to this,
IT leaders and HR leaders saying get together with your
own counterpart and your own organization, anyone listen to me
right now and talk to them about what they're accountable to,
(22:14):
what things they're prioritizing, what they're worried about. Because you
would be surprised how often something comes across and there's
an overlap where you can step in and support and
serve and build a bridge versus building a barrier. That's
what I think is the real opportunity for us.
Speaker 3 (22:28):
So who takes the lead right not just on governance
for AI, but all the other operational aspects of this.
Does HR report to it or vice versa? Is it
cross functional body, is it one leader or organization that
owns both. What's the operational the organizational model look like
in terms of ownership and leadership. You see some organizations
(22:49):
that are actually hiring someone to lead AI in the business,
and I don't think that's a bad thing to do,
to have someone with that perspective across all the different
disciplines and functions and roles and use cases and opportunity
there within its own realm. Though, HR generally is trying
to think about again, our problems are hiring, retention, benefits, composition.
Those sorts of things are our priorities for us. It's
(23:11):
problems are not those same problems, and so we need
to have some ownership within our our space as an
HR function.
Speaker 5 (23:18):
Yes, it's like global governance and local flexibility as sort
of how I see companies implement policies like here's what
it means across the globe, but within your local region,
we know that you can't work on this day of
the week because of religious holidays, so we'll give you
flexibility to accommodate that. And the same thing is true here.
We need this big picture vision. We need to get
together and say this is who we want to be.
Do we want to be a company that automates all
(23:42):
the people, roles, gets everybody out of the business, tries
to just go straight technology. What do we want of
those companies that relies on our competitive advantage, which is
our people, And we're going to use those as our
differentiator and You've said it earlier. We're going to use
people to actually create content what no, really, Yes, that
will be our that will be our advantage over someone
else because they're creating things that again very nearro very homogeneous,
(24:05):
they're all going to start to sound the same. We're
going to use our people for the unique stories they
can tell, the differentiators, the connections they can make with
our audience. And so I think that's the opportunity really is. Yes,
has overarching sort of perspective, whether it is having a
person dedicated to it or having a counsel around that.
But within your own disciplines, you're going to have to
have the flexibility because the problems you're trying to solve
(24:26):
day to day are different than the problems trying to
be solved from marketing or sales or HR in this case.
Speaker 2 (24:32):
And do you think that might be a part of
a role for HR as a management in its management
of employer brand? You know, like this is the kind
of organization where you know, AI is kept at this level.
Do you know what I mean like weight, weight based,
a human centric policy towards hiring, et cetera. I mean
and and and and how does how does hr play
(24:53):
that role in communicating externally about that brand.
Speaker 5 (24:57):
I have actually not thought about that, and I think
that's a to question. Honestly, you see companies talking about
their fair treatment of people you think their company. You
see companies talking about what it's like to work here.
They share all these kind of details transparently in their brand,
trying to attract the right people, trying to discourage the
people who are like, oh, they work hard, that's a
fast paced I want some the solar pace. I'm gonna
(25:19):
find another company to work for. They're using their brands
for those things. I don't think it's a far cry
to say we should be talking about how we see
AI as a part of the evolving model of work
and the evolving nature of work, and say we expect
you to come here and be able to use those things.
Use it during your hiring process. You're gonna be using
it at work every day. We want you to push
the boundaries what's possible or Hey, we're gonna be using
(25:39):
this the tool just like we would any other tool, email,
whatever else. But also we are going to prioritize and
emphasize and lean on the human as the key part
of this because there are things that transparently AI can't do.
AI can't take responsibility for things. AI can't build relationships
with other people. A I can't mentor others, and those
(26:00):
other things that it can't do is where we should
be spending more of our time. I've had this weird
sort of love hate conversation in the last few years
with that discussion around AI being, Oh, we don't do
all the routine stuff, so we can be more strategic
after like we'll put my hands on my hips like
a superhero pose strategic. And people have said that so
many times, like Okay, what do you mean by that?
(26:21):
We actually have data. We actually collected data on talent
acquisition leaders, people who are responsible for hiring in their businesses,
asking them, are you more efficient? Are you using AI?
Speaker 3 (26:30):
Okay?
Speaker 5 (26:31):
If so, yes to both of those questions. What are
you doing with that freed up time? Are you sitting
around playing games on Facebook or watching TikTok videos or
are you doing something useful? And what we find is
they're spending more time building relationships with candidates. So we
talked about this, right that key connection with a candidate
out there, not automating that they're spending more time building
relations with stakeholders. I've heard it is a stakeholder of
(26:54):
HR and vice versa, right, And they're also spending more
time proving to the business the value what they're doing
every day. So they're leaning those other areas that right
now they're like, that's just out of my grasp. I
can't reach it. And once they have that time for it,
they lean in. So we have some data around that,
And to me, that's that's encouraging because I was a
little bit skeptical. It was like, we'll be more strategic,
what does they even mean? And now I've gotten to
(27:14):
the data of proving that, yes, that's happening in this role,
and if it's happening here, the opportunities there in other
roles as well.
Speaker 4 (27:22):
I quite like your contempt for the word strategic, ben
is it is? It is a great hollow word in business,
isn't it?
Speaker 3 (27:29):
Yes?
Speaker 5 (27:30):
Again, every throws it around.
Speaker 3 (27:32):
We gotta let's back it up. What's some proof?
Speaker 4 (27:34):
Yeah, So you know, use that word to modernization earlier
as a potential consequence of lazy or excessive ai US,
you know, And it strikes me that that danger isn't
isn't I don't know if business is fully realized the
dimensions of that danger and what it could mean for them,
right like, because what could be worse for a business
(27:57):
than being completely homogenized.
Speaker 2 (27:58):
And against this competitive you lose your entire competitive edge.
Rest of all, do you think that that's true? Second
of all, does a char's role become therefore more hands on?
Speaker 3 (28:09):
Hips?
Speaker 2 (28:09):
It's true?
Speaker 5 (28:10):
Tag, So let's see, I do believe that. If ever here,
I'll give you an experiment. So we were talking with
one of our clients. Basically did an experiments across the
fortune one hundred, looked at all of their career sites,
pulled them together, did an analysis of the keywords, how
they talked about their cultures, all those things, and what
(28:31):
they found was substantially the majority of them. You could
have swapped out the logo and it would have all
sounded pretty much the same. They all stand for the
same things, they all believe the same things. There's no
difference between them. And that's not employer branding, that's employer blanding.
It all sounds exactly the same. There's no excitement, there's
no novelty. There's no reason for me to go work
(28:51):
here or there, and We did an experiment. I was
speaking at an events in for a group in India recently,
and I pulled together the age old debates here in
the States Coke versus Pepsi, and so I grabbed the
job from Coke India and Coke PEPs and Pepsi India
and put them together and showed the different jobs and
was asking the audience like, which one of these companies
(29:11):
want would you want to apply for? And so I'm
going through showing the job, posting themselves and no other
details from the website. You can't even tell eight clicks
in scrolling endlessly on the Pepsi one, who the company is.
It doesn't mention the company, it doesn't tell what they do.
You start reading the Coke one and it's in red fonts,
got their logo or their colors on it, and they
started talking about here's how we treat people at Coke.
(29:33):
He's important to us at co Cola. And so they're
going through those things. That sort of thing is already
happening where companies are trying to find ways to stand out,
and the best ones are doing a good job of
emphasizing that human that makes them unique, that human connection
that makes them different than everybody else. So I do
think that's an opportunity, and yes, HR has to be
playing a role in that, it's not We sometimes forget
(29:56):
that hiring an attraction is not just about pursuing a candidate,
but they have to look at us and say, I
want what you were offering me. It's not a one
way streets. And when you forget that, you think, well,
do you start to hear things like, well, they should
just be lucky we're even considering them. Let's be lucky
to have a job. And in the real world those
sorts of things don't don't really fly.
Speaker 2 (30:17):
M Okay, last question for you, Ben, wonderful, wonderful discussion.
But if you if you look ten years ahead, do
you imagine close.
Speaker 4 (30:25):
Your eyes for us, Ben, hand on it, close your eyes.
What is the most set, surprising, surprising, underappreciated way that
you think AI is going to reshape the world of HL.
Speaker 5 (30:36):
Specifically, I'm going to tell you a quick story and
then I'll then want to answer your question with part
of that story. So one of my favorite examples to
give when I'm speaking, as I talk about years ago,
I mean years and years and years ago, there was
this fever that was rampaging, and the doctors were trying
(30:56):
to figure out how to even diagnose it. They had
no clue what to do, and this doctor said, hey, listen,
I'm one hundred percent I can diagnose it every single time.
And everybody else was like the medical profession said, how
is this impossible? We can't figure it out. So they
all come together said come on over. So they all
come over there and they're sitting around there watching this doctor.
He's like, here's what I do. Here's how I diagnose it.
So he reaches over into the mouth of a person
(31:18):
who's in fact and they feels their tongue okay, And
then he reaches over into the mouth of a person
who's not sure and he feels their tongue. Immediately thereafter,
he's like, yep, this person has it too, And everybody
around him says, WHOA, that's amazing. We never thought to
do that. Looking back now, we know that's ridiculous and
terrible as a medical practice. You're giving the other person
the disease the second you put your hand in their mouth.
(31:40):
But at the time they thought it was revolutionary and
amazing and brilliant that this doctor had discovered a way
to do this. I do not want us to end
up ten years down the line, twenty years down the line,
thirty years on the line, looking back saying how did
we let AI get to where it was? Talk about
that pendle on the swing earlier? How do we get
it let it get so far that we can never
bring it back to some level, some degree of humanity
(32:02):
and connection. Do I think AI is eating some jobs?
Speaker 2 (32:05):
Yes?
Speaker 5 (32:05):
Do I think AI is changing the tasks where we
need to be folksing gone at work? Yes? But I
really think the biggest thing for me is we have
to be intentional. We have to be intelligent. We have
to recognize our faults as humans in our reliance on
the easy way, the thing we've always known, the way
we've always done it. That's our brains are wired, and
(32:27):
our grooves and our brain are designed to do that
and follow that path. We have to do it differently.
So for me, the surprising way is that we're going
to see all this change and we're going to be
surprised by it. That's what I hope doesn't happen as
we're thinking about how this reshapes HR and work. More broadly,
I hope we are more intentional hands on the wheel
because all ready to early find is coming out from
Harvard and other organizations say that we are perfectly content
(32:50):
on the AI. Just make decisions on its own when
we think it's capable, even when it's not.
Speaker 2 (32:55):
M so interesting, but I love it. Great perspective, pleasure
talking to you. Do share, do share a link to
that research. We're going to put it in the show notes.
We'll also put links to your LinkedIn and and your
books anything else you would like to like to feature
here where we people can reach out to your connect
with you, et cetera.
Speaker 5 (33:15):
The best way to find some of the research or
send your HR team to find the research is lhr
dot io. That's the website and that's where all of
our guests have is shared and published for your charge.
Speaker 4 (33:24):
Linked link linked to that website in the show notes.
Ladies and gentlemen, Thank you so much, Benn. It's been
a pleasure. Thank you guys.
Speaker 1 (33:32):
To make sure that you never miss an episode, subscribe
to the show in Apple Podcasts, Spotify, or your favorite
podcast player, and if you're listening on Apple podcasts, make
sure to leave a rating of the show. Just have
the number of stars you think the podcast deserves. If
you'd like to learn more about how next Thing can
help you improve your digital employee experience, head over to
next think dot com.
Speaker 5 (33:53):
Thank you so much for listening.
Speaker 1 (33:55):
Until next time,
Popular Podcasts
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
Cardiac Cowboys
The heart was always off-limits to surgeons. Cutting into it spelled instant death for the patient. That is, until a ragtag group of doctors scattered across the Midwest and Texas decided to throw out the rule book. Working in makeshift laboratories and home garages, using medical devices made from scavenged machine parts and beer tubes, these men and women invented the field of open heart surgery. Odds are, someone you know is alive because of them. So why has history left them behind? Presented by Chris Pine, CARDIAC COWBOYS tells the gripping true story behind the birth of heart surgery, and the young, Greatest Generation doctors who made it happen. For years, they competed and feuded, racing to be the first, the best, and the most prolific. Some appeared on the cover of Time Magazine, operated on kings and advised presidents. Others ended up disgraced, penniless, and convicted of felonies. Together, they ignited a revolution in medicine, and changed the world.
The Joe Rogan Experience
The official podcast of comedian Joe Rogan.