More Human Than Ever: How HR Can Redefine Work Through Adaptability and AI

Sabrina: 00:00:00

Make work more human to me, is to do what we now have this massive advantage

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to do, which is to remove parts of our job

that are mundane, that are administrative,

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that are what people call paper pushing.

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To remove that from our daily task list

because we are free due to automation and

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the intelligence that AI is bringing us.

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That means you can leverage

people's innate capabilities

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to the highest and best use.

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They keep telling us that it's all over.

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For HR, the age of AI is upon

us, and that means HR should

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be prepared to be decimated.

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We reject that message.

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The future of HR won't be handed to us.

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Instead, it'll be defined by those

ready to experiment, adopt, and adapt.

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Future Proof HR invites these builders to

share what they're trying, how it's going,

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what they've learned, and what's next.

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We are committed to arming HR

with the AI insights to not

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just survive, but to thrive.

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Thomas: Hello and welcome to the Future

Proof HR podcast, where we explore how

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forward-thinking HR leaders are

preparing for disruption and

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redefining what it means to lead

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people in a changing world.

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I'm your host,

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Thomas Kunjappu, CEO of Cleary.

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Today's guest is Sabrina

Sdao, Chief Growth Officer

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at Thursday Strategy.

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Prior to Thursday, Sabrina

spent over a decade at Deloitte

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as a corporate strategist.

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Sabrina now helps organizations navigate

workplace transformation with a focus on

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human-centric growth.

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She believes AI and automation

are powerful tools, not threats,

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if we rethink how we upskill

people and design for creativity

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and not just efficiency.

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Sabrina, welcome to the podcast.

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Sabrina: Thanks, Thomas.

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So let's jump right into

the skills question.

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So what do you think?

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What are the skills that are going

to be most important for workers,

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especially given the pace of change

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in AI and in the workplace overall?

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Yeah, I think skills is a hot

word right now when it comes to

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workforce strategy.

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And if I had to name what I think the

single most important skill is for

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all workers to have, whether you're

the CEO or the CHRO or the HRBP

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or the person on the front line,

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it's adaptability.

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I think everyone should

be asking themselves,

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how can I continue to

learn and grow and adapt

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given this wave of change

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and the impact that AI

is going to have on work.

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I think people are scared of AI,

scared that it's going to take over

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their jobs, et cetera.

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I think the way that I see it is that

AI has this immense capability to take

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on mundane tasks with

greater accuracy and speed.

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And what that can mean

for people is that it can

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really unleash their human potential.

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Even more so now if

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they're being bogged down by things

that could truly be better done

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potentially through automation.

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And this skill of adaptability isn't new.

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I think, as humans, technology

has changed so much.

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I think

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about the advent of the

industrial revolution or the

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introduction of the internet.

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We adapted in

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all of those different instances.

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In both cases, some things changed about

existing jobs and new jobs were created.

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I think this will

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be much the same.

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And there's really unique ways

that companies are showing

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adaptability and also engaging

their workers to be adaptable.

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One cool example is with Ikea.

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What they did was they

used bots in their contact

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center to create efficiencies

and streamline their operations,

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which freed up capacity for

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people that were previously

answering phones.

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And what they did was they

upskilled those people to

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be interior designers and then

transition them into a revenue-driving

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role in the organization

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where they were actually advising clients

on how to design their homes and which

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furniture to buy from the IKEA selection.

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And I cite that example because in

order to do that, you have to have

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people who are willing to

learn and a company that's

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willing to change and evolve.

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And when

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those two things come together, I

think that people can inherently

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be more creative and human.

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Thomas: Before we dive

into that a little bit

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deeper, I think I want to just

acknowledge you're answering this

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other deeper question within this,

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which is that there's this

emotion of fear that is pretty

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prevalent at this particular moment

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with the changes being

more rapid and being

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more of seen as a threat.

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And this is an interesting story

because there's reskilling and you're

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right, it's both corporate vision as

well as employee willingness to grow

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and adapt and learn in this case.

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What do you think that means

for the opportunities for many

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other companies out there as

they're thinking about reskilling?

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Sabrina: I think what that means is there

has to be a culture around adaptability.

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Cultures are formed through behaviors.

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Behaviors occur because they are incented.

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And you need to create that

culture, of adaptability.

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And that starts from the top

of your organization with

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leaders taking on using AI.

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It starts with your entry-level

employees coming in with that

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natural hunger and zeal for

learning, and them being adaptable.

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I think, this podcast is

about future-proofing HR.

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And so I'd be remiss if I didn't talk

about what I think this means for HR.

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And I think HR can be a big lever

for this change in an organization.

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Not only can they use these

AI tools to improve efficiency

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and remove some of the mundane

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work that they do.

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So that an HRBP, for example, has

the capacity to really elevate their

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game and be that true partner

and advisor to a business group

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head or head of technology.

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But it also means that by doing so, HR

can truly steward this change across the

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organization and can build in adaptability

and more specifically adaption of

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AI, which I think is what I mean by

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adaptability here.

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Thomas: The current example of the

meta skill that is, I think what

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you're saying, which is adaptability.

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And you're exhibiting that in

the workforce or in this example,

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as an HRBP by, for example,

leveraging AI in your toolkit.

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So yeah, tell me more about

how HR can adapt in this world.

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Sabrina: Yeah.

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I think that HR by, again,

by adapting these tools

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and demonstrating the case for

the efficiency that it creates,

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it can free up their capacity

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to get deeper into the businesses

and the functions so that they can

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help inform the use cases for these

tools across the organization.

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Because I think what's happening

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right now is that HR is sort of

being included in the conversation,

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but after the business or the

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function has taken off with AI and

its own use cases and applications.

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And while that may seem

natural, I think there is

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an opportunity for them to get

in front of it a little bit more

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or to work alongside the business

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or technology while they

are adopting these tools.

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The way that functions

and business think about

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these tools is: "Let's create

operational efficiency"

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and they do that.

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But with AI, more than ever, we're

tapping into deep work disruption.

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And the sooner HR is a part

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of that conversation, the

more likely the business and

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functions are to realize the full

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utility of AI.

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And what I mean by that is

imagine working more closely with

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your HR business partner on task

disruption, given applications of

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certain AI tools, and then them

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being able to take the lens of how

do we redesign this job, given all

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these tasks that have been disrupted.

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And when we redesign 10,

20, 30 jobs, and then

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we look at how many of those jobs

are dispersed across the entire

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workforce in that business or function.

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How does that better inform strategic

workforce planning for the business?

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And then what is

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a case that needs to be made for

the group CFO, for example, on

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how to shift costs associated with

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headcount and account for

the new costs associated with

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technology and what's that offset.

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So there's a really great opportunity

by HR demonstrating using these

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tools, establishing or freeing up

some of their capacity and really

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digging deep into the business

and functions to say: "We've done

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this" or "We know what this can do

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to your jobs.

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And we have all the tools to redesign

your workforce to better meet your needs

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today, given this tech disruption."

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Thomas: You're using the word

"disruption" and saying it's deeper and

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distinct from prior kind of changes.

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So let me just cook up an example.

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Like maybe in yesteryear, there

might be a CFO in their finance org.

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They are decided that they're

going to start using one piece

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of software for accounting

versus another piece of software.

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Maybe that HRBP who is working

with that finance function probably

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doesn't need to go too deep into the

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differences in one

software versus another.

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But in this case, when

you're going not just to

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that perfunctory level, you're

actually going down to, think

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you said the task is being

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disrupted as well, right?

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The tasks itself would be changing.

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And so in this case, are

you arguing that HRBP

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needs to understand that business process

even more deeply than my previous example,

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where you went from one accounting

software to another to add value?

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Sabrina: I think that if we take a

step back and just think about the

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difference in the technologies, like,

AI is mimicking human intelligence.

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And I think

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what prior tools or big technology

systems are doing is they're

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like more so organizing information

and making it more accessible.

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And that's the big shift.

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And it's not to say that in those

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periods of transformation where you're

implementing a big finance piece of

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software, it didn't change the work.

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I think it did change the work.

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But I think what we're seeing now is

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some tasks may be taken on entirely by AI.

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And I do think that's

fundamentally a bit more disruptive

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than what we've seen with prior tools.

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So that's why I think there's

this deeper opportunity now

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for HR to be more involved in how

AI is being applied to work so that

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they can rapidly be redesigning

jobs and we can start to achieve

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those efficiencies that

the CEOs are expecting.

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And we know there's a bit of a wait and

see happening right now, from executive

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teams on just how effective AI is

going to be to improve efficiencies

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in organizations and free up capacity.

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So I'm optimistic.

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I think HR can play a key role

there if they're not already.

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And what we see sometimes is because

this is functionally or business-led,

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for example, with one organization I

worked with, they prioritize building

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sandboxes around using AI tools, the

AI coding tools, along with a chat

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GPT tool like their own version.

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They prioritized it within

the technology group.

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It was led by technology.

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And the HRBP kind of

came along for the ride.

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I just think that if we put them more

at the center, then we can realize,

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codify what this task disruption is

and realize the impact perhaps sooner.

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Thomas: So what is hindering,

because you said it's not universal,

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but that's a great example there.

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But what do you think is hindering

HR from being part of that or

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informing the AI transformation that's

happening at so many workplaces.

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Sabrina: I think it's really natural

for business leaders within the

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organization to want to test and

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experiment with these tools and

for them to view it as a way to

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improve customer service, let's say.

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Their remit, their function.

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Pardon me?

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Thomas: To improve their remit.

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That's their core remit as a head of

customer success or whatever function.

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Sabrina: 100%.

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And naturally the train

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can start to leave the station

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if representatives from HR aren't

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a part of that initial

thinking because of the way

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business leaders are incented.

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And I think that naturally business

leaders will understand their

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use cases to a degree of depth

that an advisor doesn't always.

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And so I put the HRBP into this

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advisor role.

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And that's what's hindered them in

the past, just the nature of the

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way business decision-making occurs.

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I've seen it

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working with organizations.

243

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I worked with an organization to help

them better enable their frontline

244

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sales team and HR wasn't at the table.

245

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And that wasn't even an

AI application so much

246

00:13:42,736 --> 00:13:43,756

as it was an assessment

247

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of what skills,

characteristics, and behaviors

248

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make your people most successful

249

00:13:48,516 --> 00:13:50,356

and what do they need to enable them.

250

00:13:50,356 --> 00:13:54,026

And it's just sometimes in

a very large organization,

251

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things like that can happen.

252

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All that being said,

253

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I do think that there's a great

opportunity them to be more involved.

254

00:14:00,496 --> 00:14:02,796

Thomas: So I guess it is

organization to organization,

255

00:14:02,806 --> 00:14:04,526

but those stories that you

256

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mentioned are not uncommon.

257

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And it makes me wonder, out loud

is maybe is that just and right?

258

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Is the role for

259

00:14:16,126 --> 00:14:17,896

HR- maybe that is the role, right?

260

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You need to actually be in the

background and kind of focus on the core

261

00:14:22,806 --> 00:14:24,611

outcomes that HR typically does anyway.

262

00:14:24,741 --> 00:14:28,231

In this case, job descriptions and

career laddering and these kind

263

00:14:28,231 --> 00:14:30,941

of the recruiting process and just

264

00:14:30,941 --> 00:14:34,331

how you would evolve all of

those in responding to what

265

00:14:34,331 --> 00:14:35,761

the business leader needs.

266

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You're just like the execution

arm of driving that strategy.

267

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Is that potentially a more natural

home or in terms of being effective

268

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as a partner organization?

269

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Sabrina: So I think having things be

business-led makes a ton of sense.

270

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I think more at a higher

level, I wonder if there's

271

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just a degree of governance that

needs to be put in place to ensure

272

00:15:00,781 --> 00:15:09,761

that - what if the decision is made

in one business to eliminate all jobs?

273

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I'm making a dramatic case, right?

274

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And HR is not at the table.

275

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And the implications of that haven't

been evaluated from the talent

276

00:15:21,671 --> 00:15:24,761

strategy and the people side of

the business, or something's been

277

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overlooked because in establishing a

pipeline of future employees, because

278

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a business decision's been made

about a belief regarding the degree

279

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to which AI can actually

take on internships or

280

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entry-level jobs, for example.

281

00:15:40,040 --> 00:15:44,741

There are some big swings that I

think business leaders can make.

282

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And a lot of organizations

haven't quite established what

283

00:15:49,431 --> 00:15:50,521

is that governance structure

284

00:15:50,521 --> 00:15:51,991

around some of these choices.

285

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And so the business must

be at the table, of course.

286

00:15:55,201 --> 00:15:59,091

I think there's probably a bit

of ethics here as well— on what

287

00:15:59,091 --> 00:16:01,791

is it that we are replacing

288

00:16:02,021 --> 00:16:06,831

human work with and have we

put the right safeguards in

289

00:16:06,831 --> 00:16:09,641

place to actually have humans

290

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still be in the loop when using

some of these tools, which

291

00:16:13,141 --> 00:16:14,141

we know the tools just aren't

292

00:16:14,141 --> 00:16:14,811

good enough yet.

293

00:16:15,271 --> 00:16:17,671

So that's still an important part of this.

294

00:16:18,071 --> 00:16:21,351

And what does that mean for the

structure of your workforce?

295

00:16:21,381 --> 00:16:25,686

How are we thinking about

future-proofing the business

296

00:16:25,716 --> 00:16:28,446

given human capacity in the future?

297

00:16:28,756 --> 00:16:32,086

And I do think that HR

does help play that role.

298

00:16:32,546 --> 00:16:35,526

Maybe in some cases, what

we're seeing is so incremental

299

00:16:35,526 --> 00:16:40,546

that people are questioning why

the business can't just go ahead—

300

00:16:40,546 --> 00:16:41,915

and the business can and they will.

301

00:16:41,915 --> 00:16:45,336

I just think there's value

in HR being part of it.

302

00:16:45,346 --> 00:16:47,646

And we could be taking much bigger swings.

303

00:16:47,646 --> 00:16:52,556

And if no one else is at the table to call

out the challenges that we could face,

304

00:16:52,556 --> 00:16:55,736

in the future by doing so,

there just could be a cost

305

00:16:55,746 --> 00:16:57,246

to having to reverse some of

306

00:16:57,246 --> 00:17:01,146

those decisions or you're not

going to achieve the broader buy-in

307

00:17:01,641 --> 00:17:02,951

from the organization if they're

308

00:17:02,951 --> 00:17:04,011

made in a silo.

309

00:17:05,556 --> 00:17:09,496

Thomas: Specifically around the reskilling

example, for example, that you had

310

00:17:09,526 --> 00:17:13,806

about IKEA, I would imagine if you're

going to bring along and try to

311

00:17:13,806 --> 00:17:16,726

reskill a giant department into newer

312

00:17:16,726 --> 00:17:20,586

growing division, that is a

massive change management and

313

00:17:20,586 --> 00:17:22,326

learning and development exercise

314

00:17:22,346 --> 00:17:23,965

that takes significant coordination.

315

00:17:24,326 --> 00:17:29,196

Not to mention you don't want

this dislocation in productivity

316

00:17:29,721 --> 00:17:31,286

that could stretch quarters

317

00:17:31,346 --> 00:17:38,116

if you're executing a big shift in

approach from people to technology without

318

00:17:38,156 --> 00:17:44,146

the right mindset and skillset, which not

uniquely, but I think HR leaders typically

319

00:17:44,156 --> 00:17:46,576

will bring to the table in spades.

320

00:17:46,641 --> 00:17:48,221

But yeah, I love your doomsday thinking.

321

00:17:48,231 --> 00:17:50,961

You got to think about

these scenarios, like things

322

00:17:50,961 --> 00:17:54,571

that can happen when you just

go, all systems go and just

323

00:17:54,631 --> 00:17:56,341

take big swings, as you say.

324

00:17:56,561 --> 00:18:00,586

Have you seen any of these, any

examples of big reversals in

325

00:18:00,586 --> 00:18:05,296

course from companies after going

in one direction, whether it was

326

00:18:05,296 --> 00:18:06,886

about this particular sub problem

327

00:18:06,886 --> 00:18:10,896

of involving HR or not, but just

having to go back and forth.

328

00:18:12,826 --> 00:18:15,256

For me, certainly like return to office

329

00:18:15,476 --> 00:18:18,627

is the whole thing that comes to mind

where companies have gone back and forth.

330

00:18:18,627 --> 00:18:18,712

For me, certainly, like return to office

is the whole thing that comes to mind

331

00:18:18,712 --> 00:18:19,176

where companies have gone back and forth

332

00:18:19,346 --> 00:18:23,756

in different ways, different

policies, but maybe AI adoption

333

00:18:23,766 --> 00:18:25,136

and strategy might be one.

334

00:18:25,216 --> 00:18:30,516

There will definitely be stories, of case

studies in the future, in this era maybe,

335

00:18:30,526 --> 00:18:33,196

where companies did not navigate it

336

00:18:33,246 --> 00:18:34,216

as well as they could have.

337

00:18:35,546 --> 00:18:37,116

Sabrina: Yeah, I think so.

338

00:18:37,166 --> 00:18:41,746

I also think that the technology

isn't quite there yet.

339

00:18:42,266 --> 00:18:45,646

The human intelligence is

not quite replicated yet.

340

00:18:46,016 --> 00:18:52,916

So I do think what we're seeing that's

interesting is with early career workers.

341

00:18:53,226 --> 00:18:53,336

interesting is with early career workers.

342

00:18:53,336 --> 00:18:55,136

And I have some questions around this.

343

00:18:55,216 --> 00:18:59,096

We know that early career workers

have joined the workforce, call

344

00:18:59,096 --> 00:19:01,926

it, they've been in the workforce

between one to five years.

345

00:19:02,256 --> 00:19:06,246

And there was one study

done on this population in a

346

00:19:06,246 --> 00:19:07,636

professional services firm.

347

00:19:08,046 --> 00:19:12,546

And what they found was that

these workers were using AI.

348

00:19:12,556 --> 00:19:14,176

They feel as though it's necessary.

349

00:19:14,176 --> 00:19:16,086

It's helping them free

up some of their time.

350

00:19:16,766 --> 00:19:19,576

They believe it frees them

up to do higher value work.

351

00:19:20,136 --> 00:19:23,006

And that it's ultimately going

to help advance their career.

352

00:19:23,076 --> 00:19:26,336

And so there's a good news story there.

353

00:19:26,336 --> 00:19:28,766

And these early career

workers are, they're Gen Z.

354

00:19:28,766 --> 00:19:30,376

They're digitally native.

355

00:19:30,406 --> 00:19:31,426

They grew up with the internet.

356

00:19:31,486 --> 00:19:33,096

They're digitally savvy.

357

00:19:33,736 --> 00:19:39,406

The flip side of this though is that

they're a population of individuals

358

00:19:39,406 --> 00:19:45,266

that will not have the same foundational

skills as maybe you and I did

359

00:19:45,276 --> 00:19:46,966

going coming into the workforce.

360

00:19:47,306 --> 00:19:52,206

And there's a lot that I learned by

sitting in a meeting and listening

361

00:19:52,216 --> 00:19:53,806

to— not just what people said

362

00:19:53,806 --> 00:19:57,516

that you can read in a Gemini

note taker— but to see how people

363

00:19:57,516 --> 00:19:58,886

interacted with one another.

364

00:19:59,186 --> 00:20:02,516

To understand how conflict was

revolved or how decisions were

365

00:20:02,566 --> 00:20:06,321

actually made and note taking

366

00:20:06,321 --> 00:20:10,416

is a skill beyond just writing

things down, but there is this

367

00:20:10,736 --> 00:20:12,626

perceived degree of learning

368

00:20:12,626 --> 00:20:15,646

around human interaction in the

workplace and how things actually

369

00:20:15,646 --> 00:20:17,416

get done that I think happens.

370

00:20:17,906 --> 00:20:22,286

And some of that might be getting

lost if we don't have some of those

371

00:20:22,286 --> 00:20:23,736

more junior people in the room

372

00:20:23,736 --> 00:20:26,406

and if we have Gemini

taking notes, for example.

373

00:20:26,406 --> 00:20:30,206

There's also the fundamentals There's

also the fundamentals of data analysis.

374

00:20:30,221 --> 00:20:35,176

What does it mean to pull data into a

table and draw conclusions on your own?

375

00:20:35,176 --> 00:20:38,436

And what kind of brainpower

do you use to do that?

376

00:20:38,436 --> 00:20:38,866

And what

377

00:20:39,116 --> 00:20:41,376

sharp skills are you honing?

378

00:20:41,686 --> 00:20:41,996

And

379

00:20:44,406 --> 00:20:45,906

all that leads to experience.

380

00:20:45,916 --> 00:20:48,606

You made a mistake on an analysis in

381

00:20:48,606 --> 00:20:51,726

your second year at your first

job, and you'll never forget it.

382

00:20:51,726 --> 00:20:52,886

And it was great learning.

383

00:20:52,906 --> 00:20:54,866

I think of writing in the same way.

384

00:20:54,976 --> 00:20:57,246

Can you structure a strong argument?

385

00:20:57,626 --> 00:20:59,266

And what does that

386

00:20:59,386 --> 00:21:02,246

mean for your ability to be

able to communicate that?

387

00:21:02,286 --> 00:21:03,536

And that is a very human

388

00:21:03,536 --> 00:21:05,486

skill to be able to communicate ideas.

389

00:21:05,496 --> 00:21:07,156

People often learn that through writing.

390

00:21:07,616 --> 00:21:11,736

And imagine we have this population of

people in their early careers who aren't

391

00:21:12,276 --> 00:21:14,986

necessarily getting those opportunities.

392

00:21:14,986 --> 00:21:19,036

Instead, they're skipping those

foundational skills as some of

393

00:21:19,036 --> 00:21:22,006

those tasks are being done by AI.

394

00:21:22,776 --> 00:21:27,446

And we're still expecting that

someone has to review that work.

395

00:21:27,606 --> 00:21:30,556

And if you have these early career

workers, are you expecting that

396

00:21:30,556 --> 00:21:32,476

they're going to be the final review

397

00:21:32,476 --> 00:21:36,406

on a piece of content that's been

produced by a generative AI tool

398

00:21:36,856 --> 00:21:39,586

that could be hallucinating because

the technology is not as good yet

399

00:21:39,606 --> 00:21:41,826

and the person that's

reviewing it at first pass

400

00:21:41,826 --> 00:21:44,076

doesn't have that skill

and experience yet.

401

00:21:44,766 --> 00:21:46,886

And so we're still

relying on senior people,

402

00:21:46,916 --> 00:21:50,196

but will those skills ever

be developed in that cohort

403

00:21:50,306 --> 00:21:52,426

if they don't practice?

404

00:21:52,436 --> 00:21:54,286

I'm not negative on us using these tools.

405

00:21:54,286 --> 00:21:55,606

I'm bullish on it.

406

00:21:55,656 --> 00:21:57,516

If you're not using them, you're behind.

407

00:21:58,106 --> 00:22:00,391

But are we really thinking about

408

00:22:01,661 --> 00:22:05,611

how we grow and develop some of those

core skills and early career workers?

409

00:22:05,611 --> 00:22:08,821

And if we don't, then how do they

gain that experience otherwise?

410

00:22:08,831 --> 00:22:11,241

I think it's an open question

that hasn't been solved for yet.

411

00:22:11,671 --> 00:22:15,881

And if they're relying what's

produced in the AI tools to inform

412

00:22:15,981 --> 00:22:17,461

their experience, then we're

413

00:22:17,461 --> 00:22:19,191

creating this vicious circle too.

414

00:22:19,231 --> 00:22:21,391

So I don't think the

intelligence is there yet.

415

00:22:23,331 --> 00:22:24,491

Yeah, you're not ready for it yet.

416

00:22:24,521 --> 00:22:27,181

You're not ready for it to fully

take over and replace humanity.

417

00:22:27,551 --> 00:22:33,571

But this discussion reminds me of

this concept that every technology

418

00:22:33,621 --> 00:22:35,911

brings its own disease to humanity.

419

00:22:36,281 --> 00:22:39,924

Once we realized that we could get

energy out of coal, pretty soon we

420

00:22:39,924 --> 00:22:43,154

had co-workers with bad lungs, right?

421

00:22:43,204 --> 00:22:49,104

In the social media era, we've

had teenage depression rates and

422

00:22:49,114 --> 00:22:50,514

addiction rates on phones go up.

423

00:22:50,514 --> 00:22:53,524

But then eventually, it takes us

a little bit of time to figure

424

00:22:53,524 --> 00:22:55,664

it out, recalibrate a society

425

00:22:55,664 --> 00:22:57,674

and get safety tools in place.

426

00:22:57,744 --> 00:22:59,324

We're starting with phones.

427

00:22:59,384 --> 00:23:02,754

Let's not bring them into

elementary or middle schools.

428

00:23:02,804 --> 00:23:05,934

Society converges on some solutions.

429

00:23:06,254 --> 00:23:09,929

But I think what you're talking about

with this particular generation, they

430

00:23:09,929 --> 00:23:14,979

might be the generation that gets hit

with the diseases of this particular

431

00:23:15,329 --> 00:23:17,574

stage of this technology as it's maturing.

432

00:23:17,599 --> 00:23:20,839

But hopefully, with both the

education system and also how we

433

00:23:20,839 --> 00:23:22,589

do development within companies,

434

00:23:22,609 --> 00:23:25,869

once they do come in, I think,

which is your point, we'll figure

435

00:23:25,879 --> 00:23:30,899

out ways to fill those gaps so

that they are actually productive.

436

00:23:31,219 --> 00:23:35,379

But you could also flip it

arguably and say that these workers

437

00:23:35,379 --> 00:23:37,779

are coming in, having internet

438

00:23:37,779 --> 00:23:38,679

native generation.

439

00:23:38,689 --> 00:23:41,469

There's folks are going to

be native to using tools.

440

00:23:41,469 --> 00:23:42,639

They don't google stuff.

441

00:23:42,659 --> 00:23:46,319

They're Chat GPT or Gemini

things and getting to some real

442

00:23:46,319 --> 00:23:48,504

quick insights with a particular

443

00:23:48,504 --> 00:23:53,034

workflow or way of doing things that's

natural and faster and maybe has a

444

00:23:53,034 --> 00:23:57,169

different type of productivity that

the rest of us can learn from as well.

445

00:23:57,789 --> 00:23:58,379

Yeah.

446

00:23:58,639 --> 00:24:00,364

I think there's so much good here.

447

00:24:01,074 --> 00:24:05,769

I want to touch on the disease part

because I think there is one danger

448

00:24:06,054 --> 00:24:10,854

that we've, there's probably many, but

we saw one recently and I think people

449

00:24:10,854 --> 00:24:18,394

using chat GPT or generative AI

tools for mental health support is

450

00:24:18,394 --> 00:24:21,134

definitely a danger in this generation.

451

00:24:21,464 --> 00:24:22,004

I think

452

00:24:25,254 --> 00:24:25,884

that's a big

453

00:24:25,884 --> 00:24:28,004

watch out for employers too, right?

454

00:24:28,004 --> 00:24:31,044

People are using these tools

perhaps for personal reasons.

455

00:24:31,334 --> 00:24:33,874

And there is there's that

we need to think about.

456

00:24:33,994 --> 00:24:38,934

But on the flip side,

there's such a benefit

457

00:24:39,044 --> 00:24:42,214

to having people in their early

careers use these tools and I think

458

00:24:42,214 --> 00:24:47,809

you're right like they're wired to

do that and grew up with technology.

459

00:24:47,809 --> 00:24:52,124

I see even my kids— my four-year-old

asked for his Yoto player this morning.

460

00:24:52,134 --> 00:24:53,404

That was the first thing he asked for.

461

00:24:53,404 --> 00:24:57,554

It's a little electronic story reader you

put cards in and it reads you a story.

462

00:24:57,724 --> 00:25:00,084

And of course, he still loves when we read

463

00:25:00,324 --> 00:25:01,014

him stories.

464

00:25:01,014 --> 00:25:06,254

But it's this little electronic

that he carries around with him.

465

00:25:06,254 --> 00:25:08,134

And it's like his version of tech.

466

00:25:08,544 --> 00:25:09,574

I didn't have that.

467

00:25:09,574 --> 00:25:12,934

And that's going to become

more advanced as time goes on.

468

00:25:14,174 --> 00:25:17,414

And what I do think this generation

does have the opportunity to

469

00:25:17,414 --> 00:25:18,854

do, it's not all doom and gloom

470

00:25:18,854 --> 00:25:19,144

for them.

471

00:25:19,274 --> 00:25:20,974

They could vibe code anything.

472

00:25:21,134 --> 00:25:22,154

It's second nature.

473

00:25:22,164 --> 00:25:25,494

The job market isn't

great for them right now.

474

00:25:25,504 --> 00:25:30,224

We know that for many factors,

there's volatility in the economy.

475

00:25:30,284 --> 00:25:32,394

AI has gotten much better at coding.

476

00:25:32,394 --> 00:25:37,039

Voting, for example, there's that really

famous article in the New York Times

477

00:25:37,049 --> 00:25:41,799

this month about how people graduating

from computer and data science degrees

478

00:25:41,809 --> 00:25:43,409

said they're struggling to find jobs.

479

00:25:43,799 --> 00:25:49,539

This generation has so much capability and

so much native experience with technology,

480

00:25:49,589 --> 00:25:53,849

yet when we've told them that they should

be focusing on that and on those skills,

481

00:25:53,859 --> 00:25:58,519

now they're being shut down from these

six-figure jobs that they were promised.

482

00:25:58,519 --> 00:26:02,789

And we're seeing higher unemployment

rates amongst computer science

483

00:26:02,789 --> 00:26:03,899

and computer engineering majors.

484

00:26:03,899 --> 00:26:08,359

They're double that of biology

and art history majors.

485

00:26:09,469 --> 00:26:14,389

And I want to pause because I

think we've put so much emphasis

486

00:26:14,389 --> 00:26:16,229

on some of these technical skills.

487

00:26:16,229 --> 00:26:24,299

And realistically, the faster

that the AI is able to mimic human

488

00:26:24,299 --> 00:26:28,099

intelligence, the less relevant

those skills are going to be.

489

00:26:28,109 --> 00:26:30,179

I had a conversation

with someone recently.

490

00:26:30,569 --> 00:26:36,739

They run a software engineering

outsourcing firm, and they have big

491

00:26:36,749 --> 00:26:38,419

questions around what is the future of

492

00:26:38,419 --> 00:26:39,359

that profession.

493

00:26:40,119 --> 00:26:45,069

And if AI can generate code,

and if the code's pretty

494

00:26:45,069 --> 00:26:46,879

good, and gets to that point,

495

00:26:46,889 --> 00:26:49,789

and no one really needs to

review it, and it doesn't matter

496

00:26:49,839 --> 00:26:51,809

how well it's truly written,

497

00:26:51,809 --> 00:26:56,559

if that craft has become something

that can be done just as well,

498

00:26:56,559 --> 00:26:58,379

if not better from automation,

499

00:26:59,249 --> 00:27:01,519

have we wiped out an entire profession?

500

00:27:03,329 --> 00:27:06,639

I think there's a mini

step in between right now,

501

00:27:06,639 --> 00:27:10,639

which is that software engineers

are using AI coding tools and

502

00:27:10,849 --> 00:27:12,409

it's augmenting their work.

503

00:27:13,029 --> 00:27:18,459

And that's also a skill that people

in computer science and data science,

504

00:27:18,809 --> 00:27:22,699

like undergraduate college programs,

they're not learning that in school.

505

00:27:22,739 --> 00:27:27,719

So they're having trouble

getting jobs because their AI

506

00:27:28,309 --> 00:27:29,469

is getting a little bit better.

507

00:27:29,469 --> 00:27:30,779

The job market's a little bit weak.

508

00:27:30,789 --> 00:27:32,969

It's slowing down in at

least Canada and the US.

509

00:27:33,619 --> 00:27:37,089

And there are some key skills that

weren't part of their education

510

00:27:37,099 --> 00:27:38,729

that employers are looking for,

511

00:27:38,729 --> 00:27:40,309

which is using some of these tools.

512

00:27:40,899 --> 00:27:45,649

And while I think this generation is

very well equipped to use technology,

513

00:27:45,649 --> 00:27:48,634

there's a bit of a hiccup that's

happening for some of the folks

514

00:27:48,634 --> 00:27:51,924

in this generation that have

focused so heavily on tech skills.

515

00:27:52,334 --> 00:27:55,614

If they haven't also focused on

some of those more human skills

516

00:27:55,624 --> 00:27:57,984

that are becoming important.

517

00:27:57,994 --> 00:28:01,834

So like in the age of AI, can

you ask an effective question?

518

00:28:02,084 --> 00:28:05,314

Can that translates well

into prompting, for example?

519

00:28:05,794 --> 00:28:08,079

A human or an LLM?

520

00:28:09,029 --> 00:28:09,359

Both.

521

00:28:09,904 --> 00:28:10,349

Both.

522

00:28:10,769 --> 00:28:17,429

Are we raising a generation that's really

strong in critical thinking that can

523

00:28:17,429 --> 00:28:24,929

discern when Gen AI is producing something

that is incorrect, that's a hallucination?

524

00:28:25,179 --> 00:28:31,219

Are we developing skills related

to empathy so that we can be better

525

00:28:31,219 --> 00:28:33,159

human-centered designers and create better

526

00:28:33,159 --> 00:28:34,079

experiences.

527

00:28:34,079 --> 00:28:38,359

Because in theory, if AI is

taking on all these mundane

528

00:28:38,389 --> 00:28:39,959

tasks, we should have more time

529

00:28:39,959 --> 00:28:41,399

for improved experiences.

530

00:28:41,399 --> 00:28:45,969

And I think people's expectation of

experiences is so high because of all the

531

00:28:45,969 --> 00:28:48,629

data that's collected on us as consumers.

532

00:28:48,719 --> 00:28:51,919

And I could go on, but there's

so many human skills that

533

00:28:53,019 --> 00:28:56,149

are so important that I just

534

00:28:56,149 --> 00:28:59,789

wonder if in this generation, like we

might just see a bit of a hiccup and

535

00:29:02,309 --> 00:29:03,519

a bit of catch up, maybe.

536

00:29:03,519 --> 00:29:08,059

If the emphasis has been so heavily placed

on technical skills that I don't know that

537

00:29:08,409 --> 00:29:10,239

all people have taken that perspective.

538

00:29:10,239 --> 00:29:14,419

I think overall, it's good that the

Gen Z knows how to use this technology

539

00:29:14,419 --> 00:29:16,099

and it can enable them in some ways.

540

00:29:16,129 --> 00:29:22,219

But we can't forget the human side of

ourselves and what that means to be

541

00:29:22,269 --> 00:29:24,309

good workers and good people in society.

542

00:29:24,967 --> 00:29:27,097

This has been a fantastic

conversation so far.

543

00:29:27,337 --> 00:29:30,127

If you haven't already done so,

make sure to join our community.

544

00:29:30,367 --> 00:29:33,037

We are building a network of the

most forward-thinking, HR and

545

00:29:33,037 --> 00:29:36,217

people, operational professionals

who are defining the future.

546

00:29:36,697 --> 00:29:39,307

I will personally be sharing

news and ideas around how we

547

00:29:39,307 --> 00:29:41,317

can all thrive in the age of ai.

548

00:29:41,677 --> 00:29:44,662

You can find it at go cleary.com/cleary

549

00:29:45,092 --> 00:29:45,702

community.

550

00:29:46,327 --> 00:29:47,167

Now back to the show.

551

00:29:48,206 --> 00:29:50,696

Thomas: Yeah, it's hard to separate

out, at least for the moment.

552

00:29:50,706 --> 00:29:53,856

In a couple of years from now, when

we're looking back at it, it'll make

553

00:29:53,856 --> 00:29:58,116

more sense, like how much of the current

state with the job market, especially

554

00:29:58,116 --> 00:30:03,086

for entry-level workers, how much of

that is driven by the broader economy

555

00:30:03,086 --> 00:30:05,216

where there is uncertainty and a

556

00:30:05,216 --> 00:30:09,561

general pausing and maybe a lot

of companies, relatively speaking,

557

00:30:10,141 --> 00:30:12,621

overhiring in a low interest rate

environment in the previous years

558

00:30:12,621 --> 00:30:17,111

and just holding steady versus how

much productivity is being gained

559

00:30:17,121 --> 00:30:20,921

using AI tools, which makes your mid

560

00:30:20,941 --> 00:30:25,841

and senior level career workers more

productive and or take the carrying

561

00:30:25,841 --> 00:30:29,911

water tasks that we all had as we

first get into the workforce, those

562

00:30:29,931 --> 00:30:34,121

being the roles or the tasks that

are most quickly replaced by AI.

563

00:30:34,121 --> 00:30:37,531

But it's a little bit hard to

tell from my vantage point.

564

00:30:37,531 --> 00:30:41,581

But that's all, I think, a

preamble to, I think, your point

565

00:30:41,641 --> 00:30:42,971

about where this is all headed.

566

00:30:43,031 --> 00:30:47,271

However it all shakes out with this

hiccup, as you say, you're telling me

567

00:30:47,271 --> 00:30:51,181

that you think work needs to be more

human, if anything, going forward.

568

00:30:51,731 --> 00:30:53,261

What do you mean by that exactly?

569

00:30:53,261 --> 00:30:56,261

And how is work not human?

570

00:30:58,201 --> 00:31:02,511

Sabrina: I think work is

human, it can be more human.

571

00:31:03,471 --> 00:31:04,251

I want to answer that.

572

00:31:04,251 --> 00:31:07,281

But I want to address what you

mentioned about volatility in the

573

00:31:07,281 --> 00:31:09,751

economy, because I want to make

sure that I've been clear there.

574

00:31:09,801 --> 00:31:15,341

What we're experiencing in the job

market right now is very multifaceted.

575

00:31:15,391 --> 00:31:20,341

I zeroed in on computer science

and computer science graduates,

576

00:31:20,361 --> 00:31:21,661

for example, because I think

577

00:31:21,661 --> 00:31:25,331

it's a fascinating data

point and Gen Z, in general.

578

00:31:25,331 --> 00:31:29,281

But I think broadly, we're seeing

a lot of volatility in the economy.

579

00:31:29,721 --> 00:31:33,691

We know that the unemployment rate

has slowly climbed in North America.

580

00:31:34,291 --> 00:31:38,621

And I center myself on that just because

that's a market I know better than others.

581

00:31:38,631 --> 00:31:42,781

So I can say that confidently

and that there's two things

582

00:31:42,781 --> 00:31:43,901

that are happening right now.

583

00:31:43,911 --> 00:31:47,061

One is that there's labor

hoarding that's happening.

584

00:31:47,061 --> 00:31:47,871

So employers,

585

00:31:48,211 --> 00:31:53,451

again, in a low interest rate environment,

they did hire a lot more people and

586

00:31:53,451 --> 00:31:59,591

they know from previous experience

the cost associated with downsizing.

587

00:31:59,651 --> 00:32:03,011

And then when the economy turns

again and the pendulum will swing,

588

00:32:03,011 --> 00:32:06,831

we know that's the economic cycle,

that they'll need to hire quickly.

589

00:32:06,831 --> 00:32:09,311

So we know people have learned from

that so they're labor hoarding.

590

00:32:09,321 --> 00:32:12,081

And on the other side of

things, people are job hugging.

591

00:32:12,451 --> 00:32:16,421

So people don't want to leave their

jobs because they're worried about

592

00:32:16,421 --> 00:32:17,561

the volatility in the economy.

593

00:32:17,561 --> 00:32:18,211

I think you're right.

594

00:32:18,271 --> 00:32:22,141

I cite those two kind of examples on

the supply and demand side, because

595

00:32:22,161 --> 00:32:25,071

I think it's a complicated concept.

596

00:32:25,101 --> 00:32:30,351

And I don't want to simplify it to say

that, the reason why entry-level workers

597

00:32:30,361 --> 00:32:33,811

are having challenges finding jobs

with computer science degrees is not

598

00:32:33,811 --> 00:32:35,831

an absence of that kind

of broader picture.

599

00:32:35,831 --> 00:32:36,671

It's all connected.

600

00:32:37,331 --> 00:32:43,641

To make work more human, to me, is to do

what we now have this massive advantage

601

00:32:43,641 --> 00:32:48,271

to do, which is to remove parts of our job

that are mundane, that are administrative,

602

00:32:48,301 --> 00:32:53,941

that are what people call paper pushing,

to remove that from our daily task list

603

00:32:53,951 --> 00:32:59,951

because we are free due to automation and

the intelligence that AI is bringing us.

604

00:33:00,341 --> 00:33:04,311

That means you can leverage

people's innate capabilities

605

00:33:04,311 --> 00:33:05,851

to the highest and best use.

606

00:33:06,181 --> 00:33:09,001

It means that employers need to

decide what they're going to do with

607

00:33:09,001 --> 00:33:10,131

that freed up capacity.

608

00:33:10,421 --> 00:33:14,291

But to me, there's two different ways

different ways and they can both converge.

609

00:33:14,531 --> 00:33:18,671

One is inspiring people to

innovate for the organization.

610

00:33:18,946 --> 00:33:23,321

And the IKEA example is one way

that they did that, like to reapply

611

00:33:23,321 --> 00:33:26,921

capacity, upskill people, and they

can do something that's inherently

612

00:33:26,921 --> 00:33:28,361

more human, which is providing

613

00:33:28,721 --> 00:33:34,511

good design advice versus maybe

tech support or information on

614

00:33:34,591 --> 00:33:37,721

an IKEA return that a client

could engage with differently.

615

00:33:37,731 --> 00:33:40,551

I think that's like upskilling people.

616

00:33:40,611 --> 00:33:43,711

That's giving them growth and

development in their career.

617

00:33:44,011 --> 00:33:47,001

It's also driving a new stream

of revenue for your business.

618

00:33:47,011 --> 00:33:52,561

So you can foster, make the workplace more

human by giving people a bit more purpose

619

00:33:52,581 --> 00:33:56,241

and meaning in their work by doing

things that are less mundane and

620

00:33:56,241 --> 00:33:57,921

fundamentally more challenging, require

621

00:33:57,921 --> 00:33:59,431

critical thinking and creativity.

622

00:33:59,821 --> 00:34:02,891

I think that another way that

you can make work more human

623

00:34:02,891 --> 00:34:04,226

is you can actually leverage

624

00:34:04,266 --> 00:34:08,315

the data that we know about people

to make their actual experience as

625

00:34:08,315 --> 00:34:11,585

an individual, no matter what they're

doing, way more tailored to them.

626

00:34:11,755 --> 00:34:12,926

We have a really high bar

627

00:34:12,926 --> 00:34:15,045

on the experiences that we engage in.

628

00:34:15,085 --> 00:34:18,056

Apple, Spotify, Google,

they know us so well.

629

00:34:18,636 --> 00:34:22,326

Spotify is creating playlists for

me based on all my prior behaviors.

630

00:34:22,341 --> 00:34:24,726

What if your workplace actually

631

00:34:24,735 --> 00:34:29,360

designed your ideal workday based

on what you've told the system your

632

00:34:29,420 --> 00:34:32,821

priorities are and helps you better design

633

00:34:32,821 --> 00:34:37,311

your day so that you can maximize your

time so that you can then spend time

634

00:34:37,311 --> 00:34:38,471

on things that are important to you.

635

00:34:38,491 --> 00:34:41,971

Maybe you want to do something

for yourself in the evening.

636

00:34:41,981 --> 00:34:45,991

You want to see a friend or you don't want

to cancel plans for the third time or you

637

00:34:45,991 --> 00:34:47,588

want to pick up your kid from school.

638

00:34:47,987 --> 00:34:53,007

And you inform your HR information

system about your personal needs

639

00:34:53,007 --> 00:34:54,098

and your professional needs.

640

00:34:54,098 --> 00:34:57,968

And they help steer you based on what

they know your goals are and the data that

641

00:34:57,968 --> 00:34:58,988

you put into the system.

642

00:34:58,988 --> 00:35:00,908

And that data can be your calendar data.

643

00:35:01,188 --> 00:35:03,378

It could be your email traffic.

644

00:35:03,838 --> 00:35:08,388

It could be the data that you've

put into your HRIS about your

645

00:35:08,388 --> 00:35:11,848

skills, your capabilities, the

career path you want to be on.

646

00:35:12,248 --> 00:35:17,738

And that could be combined with whatever

professional or personal assessments

647

00:35:17,738 --> 00:35:21,318

the business has taken the initiative

to take and inform their leaders on.

648

00:35:21,768 --> 00:35:29,438

And there's this huge opportunity to make

work feel so custom to the individual.

649

00:35:29,768 --> 00:35:32,218

And when we see the pendulum sling

650

00:35:32,228 --> 00:35:35,918

back, when we see the economy

improve, and when we see the job

651

00:35:35,918 --> 00:35:37,698

market improve, and when it becomes

652

00:35:38,078 --> 00:35:41,678

an employee market versus an

employer's market, some of these

653

00:35:41,688 --> 00:35:45,058

things are going to make the difference

if employers get ahead of it.

654

00:35:45,088 --> 00:35:49,508

I think that's strategic HR to

actually get ahead of the shift

655

00:35:49,728 --> 00:35:50,948

we will see in the market.

656

00:35:51,128 --> 00:35:51,908

Things will change.

657

00:35:52,178 --> 00:35:54,408

And I think employers will

once again have the power

658

00:35:54,408 --> 00:35:56,018

and our employees will have the power

659

00:35:56,018 --> 00:35:58,558

and how do you actually

create the circumstance

660

00:35:58,748 --> 00:36:02,658

upon which you are competing

for top human talent?

661

00:36:02,688 --> 00:36:04,048

We won't all be replaced,

662

00:36:04,818 --> 00:36:06,808

but some of our mundane tasks will be.

663

00:36:07,218 --> 00:36:07,918

That's for sure.

664

00:36:09,888 --> 00:36:11,938

Thomas: I love that vision for the future.

665

00:36:11,938 --> 00:36:18,038

So then when you're advising your clients

or just in general, as you're talking

666

00:36:18,038 --> 00:36:25,618

to executives, leaders, CHROs who are

coming to you with the latest problems to

667

00:36:25,618 --> 00:36:28,398

solve these days, what are you hearing?

668

00:36:28,398 --> 00:36:30,588

What is top of mind?

669

00:36:30,688 --> 00:36:33,388

Is it top of mind to make work more human?

670

00:36:34,378 --> 00:36:39,288

Or what are the problems that executive

teams are struggling with in this moment?

671

00:36:42,348 --> 00:36:47,358

Sabrina: I think that the economy has been

a big topic for executive teams and how

672

00:36:47,358 --> 00:36:54,758

to safeguard against the unforeseen and

the volatility that we've experienced.

673

00:36:54,758 --> 00:36:59,938

I think that's definitely what's

keeping executives up at night and doing

674

00:36:59,938 --> 00:37:06,288

whatever they can within their control

to sustain and grow their businesses.

675

00:37:06,738 --> 00:37:08,678

We're seeing bankruptcies happen.

676

00:37:08,708 --> 00:37:09,958

Companies are getting liquidated.

677

00:37:09,958 --> 00:37:11,628

They're not meeting

their debt obligations.

678

00:37:11,628 --> 00:37:15,863

I think things like that due to the

volatility in the economy are truly

679

00:37:15,863 --> 00:37:18,863

what's keeping top executives up at night.

680

00:37:19,463 --> 00:37:23,683

And I think that what that means is

they're looking for ways to improve

681

00:37:23,683 --> 00:37:25,013

efficiencies in the business.

682

00:37:25,063 --> 00:37:27,633

AI is one way to achieve efficiencies.

683

00:37:27,773 --> 00:37:32,943

It also requires an investment,

not just in technology, but also in

684

00:37:32,943 --> 00:37:38,893

compliance and meeting regulatory

requirements to safeguard data and

685

00:37:38,893 --> 00:37:45,048

It requires the people change, the

learning, the incentives for adoption,

686

00:37:45,368 --> 00:37:50,838

the behavior change on a daily basis,

not just the three things you do this

687

00:37:50,838 --> 00:37:52,568

year to get better at using this tool.

688

00:37:52,568 --> 00:37:54,318

It's like, how are you using it every day?

689

00:37:54,918 --> 00:37:57,068

And then it's improving processes.

690

00:37:57,428 --> 00:38:05,158

So to actually maximize where in processes

can you create shortcuts or streamline

691

00:38:05,168 --> 00:38:07,878

because you're using AI and automation.

692

00:38:08,248 --> 00:38:12,488

So that's a macro factor

that's impacting businesses.

693

00:38:12,938 --> 00:38:16,428

When I talk about talent

strategy, in the way that I just

694

00:38:16,428 --> 00:38:18,138

have about how you future proof

695

00:38:18,138 --> 00:38:25,078

and get ready for the pendulum to

swing, to me, there should always

696

00:38:25,088 --> 00:38:26,788

be someone in the organization

697

00:38:26,938 --> 00:38:30,568

or group of people that are thinking

about that and not losing sight

698

00:38:30,568 --> 00:38:32,408

of it, even amidst volatility.

699

00:38:32,688 --> 00:38:35,748

I think that we live in a volatile world.

700

00:38:36,258 --> 00:38:38,348

I'm not sure that's going to change.

701

00:38:38,368 --> 00:38:42,788

I just think that's been combined with

some other factors that are leading

702

00:38:42,788 --> 00:38:46,418

to slow growth in certain industries.

703

00:38:46,878 --> 00:38:51,238

And the geopolitical climate

has also impacted that as well.

704

00:38:51,958 --> 00:38:57,413

I don't think it means that you

stop thinking strategically.

705

00:38:57,418 --> 00:39:01,678

I think that as soon as you do that,

you are at risk of being mediocre.

706

00:39:01,868 --> 00:39:05,208

And that's never advice

that I would give anyone.

707

00:39:06,498 --> 00:39:08,868

Thomas: There's always the next headline.

708

00:39:09,368 --> 00:39:13,508

And the negative headlines will

get you more clicks and views if

709

00:39:13,508 --> 00:39:14,498

you're on the media side.

710

00:39:14,978 --> 00:39:18,168

But you can't always be reactive,

you need to be strategic, right as an

711

00:39:18,183 --> 00:39:23,203

organization to invest the appropriate

kind of way, but you're right to call out

712

00:39:23,203 --> 00:39:25,493

there's, there's real pain out there for

713

00:39:25,493 --> 00:39:30,053

some organizations and really trying to

sort through what the future looks like.

714

00:39:30,183 --> 00:39:35,813

So speaking specifically to the HR

function, what do you think if you had

715

00:39:35,813 --> 00:39:41,423

any parting thoughts for an HR function

leader to help navigate volatility.

716

00:39:41,783 --> 00:39:44,933

Any closing thoughts for such a

leader who is trying to figure

717

00:39:44,933 --> 00:39:46,483

out exactly how to engage

718

00:39:46,483 --> 00:39:51,223

with the executive team and also

their team in these conversations

719

00:39:51,223 --> 00:39:56,663

about reskilling, workforce

planning and process shifting?

720

00:39:58,313 --> 00:40:02,643

Sabrina: I think that HR often isn't

the first to get access to some

721

00:40:02,643 --> 00:40:04,333

of these tools and technologies.

722

00:40:04,773 --> 00:40:09,623

And if I'm an HR leader, a way to stay

ahead is to actually demonstrate that

723

00:40:09,623 --> 00:40:13,833

they're using these AI tools and they're

leveraging them to create efficiencies

724

00:40:14,193 --> 00:40:17,953

and creating cases for why they actually

work and how work can be disrupted.

725

00:40:17,953 --> 00:40:24,803

And I think that's one way that HR can

continue to stay relevant and provide

726

00:40:24,803 --> 00:40:29,738

great advice to the business and

continue to demonstrate how to upskill

727

00:40:30,058 --> 00:40:34,158

because they're upskilling, how to use

the tools to create capacity because

728

00:40:34,158 --> 00:40:36,678

they're creating capacity, and how to

729

00:40:36,678 --> 00:40:41,228

to reapply that capacity to generate

greater value for the business

730

00:40:41,228 --> 00:40:42,498

because they're actually doing it.

731

00:40:42,588 --> 00:40:46,258

So I think they have to walk

the walk, talk the talk, be

732

00:40:46,258 --> 00:40:50,213

using automation to do things

733

00:40:50,213 --> 00:40:55,973

like improve tier one employee support,

let's say, or to craft job canvases.

734

00:40:55,973 --> 00:40:57,623

So that's one way.

735

00:40:57,663 --> 00:40:58,863

I think HR can do that.

736

00:40:58,863 --> 00:41:03,093

The other is keeping one foot in

the now and one always in the future

737

00:41:03,313 --> 00:41:06,913

and not taking for granted whatever

the position it is that you hold in

738

00:41:06,913 --> 00:41:14,573

the market today, because someone can

always compete with you for top talent.

739

00:41:14,763 --> 00:41:18,463

And if you wake up believing

that your position could always

740

00:41:18,463 --> 00:41:20,033

be shaken, what is it that you

741

00:41:20,033 --> 00:41:24,223

can do to keep your finger on the

pulse of what employees really need?

742

00:41:24,773 --> 00:41:28,973

I'd be thinking of more specifically,

what is your employee value proposition?

743

00:41:29,323 --> 00:41:31,623

And have you been refining that?

744

00:41:31,623 --> 00:41:32,783

Are you keeping up with it?

745

00:41:32,783 --> 00:41:35,813

Or have we been stalled because

we're focused on other priorities?

746

00:41:35,853 --> 00:41:39,523

And we know that employee

value propositions, first

747

00:41:39,523 --> 00:41:40,333

and foremost, there's so

748

00:41:40,333 --> 00:41:41,803

many generations in the workforce.

749

00:41:42,023 --> 00:41:43,293

They have very needs.

750

00:41:43,763 --> 00:41:46,333

And Gen Z has very specific needs that are

751

00:41:46,333 --> 00:41:50,728

so different than the retiring

workforce, but they're all important.

752

00:41:51,138 --> 00:41:52,438

And are you keeping pay

753

00:41:52,438 --> 00:41:53,128

at pace?

754

00:41:53,298 --> 00:41:54,358

That's the baseline.

755

00:41:54,468 --> 00:41:55,888

Cost of living has risen.

756

00:41:56,198 --> 00:41:58,228

Have you been keeping

up with cost of living?

757

00:41:58,278 --> 00:41:59,918

What benchmarks are you using?

758

00:42:00,258 --> 00:42:02,318

I think if you get that,

that's foundational.

759

00:42:02,448 --> 00:42:04,928

And there's all sorts

of things I'd say on the

760

00:42:04,928 --> 00:42:07,628

growth side of the equation and the

perk side of the equation when it

761

00:42:07,628 --> 00:42:09,428

comes to employee value propositions.

762

00:42:09,438 --> 00:42:14,338

But on the growth side, do people

feel like, Gen Z wants to feel they

763

00:42:14,338 --> 00:42:18,618

have agency, that they have influence

in the work that they're doing.

764

00:42:18,908 --> 00:42:19,718

They want to learn.

765

00:42:19,728 --> 00:42:20,868

They want to get feedback.

766

00:42:20,868 --> 00:42:28,088

I was chatting with someone recently

about how they're using Gemini to gauge

767

00:42:28,348 --> 00:42:30,728

what their manager's feedback might say.

768

00:42:30,928 --> 00:42:36,458

So prior feedback from a manager is being

put into GPT combined with feedback from,

769

00:42:36,468 --> 00:42:39,748

let's say, a therapist is put into GPT.

770

00:42:39,748 --> 00:42:42,648

And then you put it in your most

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