Shownotes
In this episode of the Future Proof HR podcast, Thomas Kunjappu, CEO of Cleary, sits down with Stefani Voorhees, Chief Human Resources Officer at Propio Language Services, to explore what it really takes to adopt AI across an organization without losing the human element.
Stefani shares how executive alignment, transparency, and a clear philosophy that “AI makes people better, not replaced” shaped a company-wide shift toward responsible experimentation. From forming an internal AI function to launching small pilots with guardrails, she walks through the practical realities of change management in fast-moving, high-growth environments.
The conversation dives into real use cases across talent acquisition, learning and development, and performance management. Stefani explains how AI-powered recruiting insights are helping HR move from anecdotal feedback to data-backed strategy, while also emphasizing the importance of blending technology with empathy. As automation increases, she argues, HR’s role becomes more strategic, not less.
The episode closes with a candid look at the future of HR. Stefani shares why AI is accelerating the shift from administrative work to business partnership, why “people experience” must remain the north star, and how leaders can stay adaptable when the future is anything but predictable.
Topics Discussed:
- Why AI must be treated as a business decision, not just an HR initiative
- How to align executives quickly around a clear AI philosophy
- Building guardrails with an AI committee and responsible pilots
- Using AI in talent acquisition to turn interview data into strategic insights
- Balancing content creation speed with human tone and quality
- The risks and opportunities of AI in performance management
- Why HR is shifting from administrative to strategic work
- Blending technology and empathy to protect the employee experience
- Leading transparently through rapid change and acquisitions
- Future-proofing HR through adaptability and a fail-fast mindset
If you are an HR leader navigating AI adoption, managing change across teams, or trying to elevate your function from administrative to strategic, this episode offers a practical and grounded perspective on building momentum while staying people-first.
Additional Resources:
Transcripts
And I think when I look at it, I do not see AI as replacing people.
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A machine didn't tell our executive
team, here's what you guys should
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do over the next 12 months.
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We had to come up with those ideas.
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Thomas Kunjappu: 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
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we explore how forward thinking
leaders are navigating disruption
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and redefining the future of work.
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I'm your host, Thomas
Kunjappu, CEO of Cleary.
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Now today's guest is Stefani Voorhees,
the Chief Human Resources Officer at
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Propio Language Services, a fast growing
company in the language services industry
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that's boldly embracing Artificial
Intelligence to enhance human performance.
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Under Stefani's leadership, Propio has
grown from under a hundred employees to
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over 600 in just two years, all while
launching an internal AI team and HR AI
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agent and a philosophy that AI doesn't
replace people it makes people better.
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Stefani, welcome to the podcast.
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Thank you.
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I'm so excited to be here today.
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So there's so much to talk about.
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Could you tell me a little bit just to
set the background, but what is Propio and
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what's been going on over the last couple
of years that's caused so much growth?
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Stefani: What hasn't been
going on the last couple of
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years is really the question.
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So we are in the language services
world and we offer both interpretation
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and translation services.
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We've got clients all over the globe.
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It has been phenomenal.
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I've been here right at two years
coming up on two years in a couple
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of weeks and it's been a wild ride.
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When I first met with Marco and
the leadership team here they
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promised me wild ride and they
have yet to under deliver on that.
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So we've grown both organically
and through acquisition.
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We've completed four acquisitions
over the last 18 months.
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So it has been phenomenal and really
excited to continue to see Propio grow
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and take this next step into the future.
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Thomas: And you're in the language
services space and to go a little bit
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back into like my career, like a while
ago, I worked on some software that
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included a lot of machine translation.
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We're going back well over a decade.
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And we also worked with a lot
of human translators to make
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a bunch of stuff happen there.
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And on the face of it, it seems like
an industry that has always been and
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is completely being rocked by AI.
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So tell me about how that's
happening and how you guys are
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growing despite or because of it.
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Like how is it related?
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We can just talk about the industry
because it's very interesting because
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language services it's like one of
those things where there's a lot of
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applications leveraging AI, right?
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Stefani: Yeah, absolutely.
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And from the beginning, we have
really seen AI not as a threat, but
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really as a catalyst of growth for us.
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We are a people driven business and the
power of AI really is lying with how can
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we enhance the accuracy, the speed and the
insight, not replacing the human element.
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And so we recognized early that
organizations who are leaning in and
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learning fast with AI will really
set the pace in this industry.
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So for Propio and the things that we're
doing here, adopting AI was really
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about staying true to our mission.
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And that's connecting
people anywhere, anytime.
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And we are doing that through technology.
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And we are able to do it at a smarter
and more impressive scale than
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I think others might be able to.
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And it's really allowed us to innovate
from a position of strength rather
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than reacting from a place of fear.
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Thomas: Was there ever like a moment that
made you say, okay, now we're choosing,
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we're taking a right turn here as a team.
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And now we're going in like that in
terms of being an AI or was it just
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something that happened organically?
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specifically the reason I'm asking is
feel like a lot of companies and HR
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leaders who might be out there listening
are in that mode of deciding or helping
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decide at an executive team level.
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Okay, what is our posture
towards this for our industry
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and for us as an organization?
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So is it a lightning in a bottle moment
or was there just a I don't know,
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hundreds of meetings and hours over years?
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Stefani: Yeah, it was definitely
a conscious decision on our part.
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was about 12 months ago.
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It was September.
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We knew that there was
a lot of buzz around it.
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Our executive team is
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very well versed in the industry.
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And we started hearing
about it more and more.
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So a little over 12 years or 12 months
ago, we made that conscious decision.
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And September of 2024 is when
we took that out to our people.
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Thomas: It sounds like it was a
conscious decision at an executive team
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level, seeing what in your industry
and where you wanted to go as an
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organization to really see it as a...
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you want to be an early adopter, you
want to lean in and also ensure that
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aligns still with your broader mission.
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And it does.
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So once you got past that set
of decisions, what comes next?
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How do you
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do the change management for an entire
organization around AI adoption?
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Stefani: It like you said, it
started at the executive team level.
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We had to have a lot
of those conversations.
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But I think we came to this decision
relatively quickly and we all had the
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same thought around AI should enhance our
people and performance, not diminish them.
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And I think since all of us were
so aligned around that so quickly
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that we were able to expedite some
of those conversations that I'm
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sure companies are having out there
that are taking hours upon hours.
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Once we knew that was our clear principle,
the alignment came pretty quickly.
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Each of our executive team members looked
at how could we use AI in our functions?
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How could it elevate the functions
that we were responsible for?
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From HR to operations product, all of us.
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We really took a hard
look at what could we do.
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And then we jumped in and I think
it was a lot of communication.
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I mentioned this town
hall in September of 2024.
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We just came out and
said, here's our stance.
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We are leaning into this,
but we want you to know that.
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We believe this is enhancing.
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It's making people better.
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It's not better than people.
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And I think when we took the approach
of just going to be really open
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with our employees and our teams and
tell them what we're looking for.
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That kicked it off.
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And then after that, it was how
can we test this responsibly?
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Little small pilots, little trials
and errors, continuously being
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transparent with our communication
around what we're doing.
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We absolutely had to set guardrails.
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We established an AI committee very early
on saying, okay, what are our boundaries?
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And we were honest with that.
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We focused on our quick wins.
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We really demonstrated the
value that AI was bringing.
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So the employees could
get a little bit of that.
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A lot of times we're always
looking for that final win.
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We took little wins with AI.
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And because we had that early
on alignment, we were able to
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have the accountability with
each other to really make AI an
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innovative part of our business.
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Thomas: So it sounds like it was both
in product development as well as like
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internal operations for every department.
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It's as kaleidoscopically
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engaged as possible.
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And the approach you're
advocating for you went through
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is it sounds like transparency.
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It's like you made a decision
fast and you went at it and
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said, here's what we're doing.
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And here's, there's a lot of
open questions, but we're going
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to support people along the way.
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I think even if another stage I hear
about often are executive teams that
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are aligned, but then they're trying
to figure out how should we best
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go about engaging with a broader
employee population around this.
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All the way from like mandates to this
is completely open and experiments,
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promises about L&D in folks and skilling
versus just saying, hey, we need to
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figure things out in a small group first
before we make a bigger announcement.
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What kind of thoughts would you have
about those kind of change management
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decisions that people might be
going through about given executive
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alignment, how to go about that?
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What things would you consider
in forming such a strategy?
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Stefani: I think part of it for us was
we were really honest in saying, nobody
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knows what they're doing 100 % here.
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Like AI is cool to everybody.
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And I think that just us being
willing to say, we're going to mess
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this up 100 and being okay to try a
lot of things, fail fast with them.
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Because nobody has the playbook for AI.
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I think that's one of the most
asked questions for me right
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now, whether it's internally or
externally is what's your playbook?
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We don't have one.
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We're all writing this thing
together and one of our values.
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And I think we'll talk a little bit about
some of our values later with fail fast.
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It was perfect with AI.
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We just had to jump in, try it out.
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And there was some strategy internally
with it and externally as well.
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But on the internal side, it's we
identified groups of people that we knew
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were excited about it or interested in it.
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Why not be as hesitant?
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And we tried and we got
those little wins with them.
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And then it was like, wait that's
really cool, I would like to try that.
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And so it became a want what they have.
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And so we were pretty strategic internally
with picking pockets to trial things with.
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And then externally, obviously, so
much of what we do is in healthcare
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and very regulated industries.
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And so we had to be also on our client
teams, they were extremely strategic
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and clients said they started to
have these discussions with, and we
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took it as we're going to have to
try things, we aren't going to get
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it 100 % perfectly, but let's try it.
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But let's be really strategic about how
we try it, who we're trying it with.
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Thomas: So I have to ask them
about the HR element of this.
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Do you feel like as a people leader
within the organization, have you
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been taking on new things, would
you say, with this transformation?
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Or does it feel like other exercises
that the function has historically
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led, whether it's like a digital
transformation or company-wide
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processes that you're rolling out there.
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How does this compare?
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Does it feel like it's adding more
to the already full functions on a
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briefcase?
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Stefani: I think it's
just something different.
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I don't think it's anything
more, and it might just be me.
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I've got a project management
focus when I'm building my HR teams
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and running the people function.
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It's all very project management focus.
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But for me, it wasn't.
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It hasn't been something that's scary
and it's like big overhauling thing.
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Last year we implemented a new HRIS.
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That was not an easy feat.
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We've gone through four
acquisitions and acquired a
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thousand employees every 18 months.
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That's not easy either.
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To me, I didn't let myself get bogged
down in, my gosh, this is something new.
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I've got to figure it out.
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Let's jump in and figure it out.
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What exciting things could
this do for us in the future?
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And so I think a lot of it was the
mindset that I went in with it.
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But I don't think it was any more than
any other change management that HR
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function would do in the business.
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It's just something different.
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Thomas: I love that attitude.
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One of the things that you guys
did was actually build, that is a
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little bit unique as you actually
have now a VP of AI, right?
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So it's a function, right?
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That's like now emerged, which some
organizations are also like thinking about
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or it just may naturally go into existing
functions and it's maybe it becomes
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more bottom up in terms of the strategy.
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Tell me a little bit about what came about
with building this internal AI function.
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How did that come about and why does
it make sense in your environment?
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Stefani: It sense in a lot of ways.
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And our internal AI function
it's not just internally facing.
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That team is doing
internal and external work.
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But just like AI itself, it's evolving.
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It's a very new team.
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just hired the VP of AI this year
and he came in and we immediately
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added a whole function to this group.
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And now we're adding yet another
function because we see yet another
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opportunity and things are going
well and we want to expand on things
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and we want more opportunities.
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So it's very similar to AI
itslef, it's just ever evolving.
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And I know where it sits today isn't
where it's going to be next year.
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It'll look completely different.
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And Proprio is very fortunate.
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We've got not even just the executive, all
of our senior leaders aren't scared of AI.
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And I think that's where a lot of
businesses right now are struggling
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is there is a lot of fear around it.
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And that's something that makes our
management team so strong is some that
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might be a little bit more hesitant
around it, are able to talk to the
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ones that are more like, let's jump all
in and we can balance each other out.
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And so think when you're looking
to build these AI functions.
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We built a committee
as I mentioned earlier.
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You've got to balance it out
because the people that want to
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go all in, they probably need
to be rolled back a little bit.
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There is a reality to businesses, but
also on the other side of it, those
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that are terrified of it, sometimes
they need a little bit of push.
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so ensuring that you have that
balance within the group is how
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you're going to evolve as a business.
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Thomas: Got it.
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Then structurally, could you tell me
like how you got into a point where,
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okay, the strategy is in place,
we're doing some change management,
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bringing people along, and now we
even have this internal function.
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Which is itself evolving over time.
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But what is the structure now if
you want to bring in a new tool or
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bring change a particular process.
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What's been working for you?
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Or what's, what are things that you've
shifted in terms of process that is then
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also enabled by this internal AI function.
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Stefani: Yeah, when we've wanted
to bring in a new tool or try
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something out, it's obviously we've
got to make the business case.
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It can't just be a half-baked idea.
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We're really big into fully
bake the idea, then sell it.
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But we've really been open-minded
to trying out different things.
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We've had a lot of conversations with
external partners of tools we've brought
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in and said, hey, we want to try all this.
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We want to see what limits
we can push with it, where it
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works, where it doesn't work.
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And just having those conversations.
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And then we put stuff
through the AI committee.
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We talk about it as an executive team.
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And I think it's critical when
you're looking at bringing in
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new tools and changing processes.
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I think a lot of times people think,
changing a process, that's HR's job.
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It is yes, but I would say it's a yes and
for us, I really thought of it as AI at
279
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Propio wasn't, that's not an HR thing.
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That's a business decision.
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HR plays a role in this absolutely,
but because AI is a business decision
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for us, it's a business shift.
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We've really empowered all of our leaders
to bring people along with the change
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and not just put all of that on HR.
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I can write a policy, yes, but I'm
not the one living with these teams.
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I'm not the one sitting
beside them every day.
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And so for us, we've really taken that
perceived burden away from HR and say,
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guys, this is a whole business thing.
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We're all in this together.
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It's going to take all of our
time and all of our effort.
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Thomas: Wow.
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Let's talk about the HR side of it though,
because you mentioned the mandate is what
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you guys have been doing is not just like
implementing AI for your product, but
294
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also every function internally is also
going at it and finding different ways
295
00:16:14,234 --> 00:16:21,034
to pilot and leverage new tools and or
ideas from an HR perspective specifically.
296
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What have been some cool things that
you've tried that's been working?
297
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I'm also just as curious about any
of the experiments from the fail
298
00:16:30,574 --> 00:16:34,784
fast where you fail fast at any kind
of stage of the piloting process.
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Stefani: Yeah.
300
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So tried a few things.
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I got a lot more on the roadmap for 2026.
302
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Now you've got this AI function.
303
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think there's a line out the door.
304
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Who gets to use them the quickest,
but we tried a few things.
305
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think most of it has been in our
learning and development function, as
306
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well as our talent acquisition function.
307
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We tried several tools on the TA side
around reviewing interviews, typing
308
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up their notes, summarizing it.
309
00:17:03,414 --> 00:17:08,679
We get a lot of feedback of and this
candidate only wanted hybrid or fully
310
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remote, or they wanted fully in office.
311
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But we've never been able to provide
data to make business decisions off of.
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And so we implemented, we
tried a couple of AI tools.
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We ended up implementing one that the
recruiters will have a phone conversation.
314
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It writes their notes for it.
315
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But my favorite part is I can go
in and say, how many times was
316
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PTO mentioned in a phone call?
317
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How many times was remote work brought up?
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And so now I'm able to collect this
data and then I can come back and say,
319
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okay guys, we say anecdotically that
this person declined because of XYZ.
320
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I actually have data.
321
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Do we want to make a
change in our programs?
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Do we want to make a
change in our offerings?
323
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Or does the data not support it and
it's actually just something that
324
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like one person said and it got stuck.
325
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So we're able to make a lot
better decisions for the
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00:17:57,209 --> 00:18:00,469
business strategy based off of TA
conversations, which is very unique.
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Thomas: I love that example.
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I've seen it a lot in high ticket B2B
sales for a while where the expectation
329
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is that every call is recorded.
330
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Part of it's like a little
bit almost cultural.
331
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Are we okay with?
332
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having these things, but I think
we're moving in that direction.
333
00:18:15,439 --> 00:18:20,579
But then it's really interesting
because you can take out a lot of this
334
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unstructured data, which is available
in so many transcripts for any kind of
335
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context where a call can be recorded and
then convert that into useful insights.
336
00:18:28,799 --> 00:18:31,279
And that work, even if you
had the recording, like before
337
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this technology you're talking
about, that's a thankless job.
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If you're going to try to take
hundreds of screening calls and
339
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try to come up with a story.
340
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great examples.
341
00:18:41,094 --> 00:18:45,224
So then that's then come back into making
an impact on your processes or maybe
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even the candidate experience or even
the employer value proposition overall
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through in terms of what you're offering.
344
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Stefani: Yeah, absolutely.
345
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And our sales team uses the same tool.
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We've got different platforms,
obviously, but they do use the same tool.
347
00:19:00,904 --> 00:19:04,484
And like you said, my recruiting
team was very nervous at first.
348
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I came to them and said,
Hey guys, guess what?
349
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I'm really excited.
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I'm going to record all of your phone
calls and I can listen to everything.
351
00:19:09,924 --> 00:19:12,059
And the eyes got really
big and I don't want that.
352
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I want the data.
353
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And then when I told them, said,
you guys are saying that we need
354
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to change our PTO policy or we
need to change our this or that.
355
00:19:20,659 --> 00:19:23,309
I've never been able to do or
have these conversations that
356
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don't have the actual data for it.
357
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Guess what?
358
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Now I do.
359
00:19:26,174 --> 00:19:29,844
And I've been able to show
them because of this tool.
360
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One, you guys are saving a ton of time.
361
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You're not writing notes.
362
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You're saving an absorbent amount of time.
363
00:19:34,244 --> 00:19:36,564
I'm very compliant from
a note taking standpoint.
364
00:19:37,494 --> 00:19:41,504
And I now have actual data and I'm
helping you guys and it is proven itself
365
00:19:41,734 --> 00:19:44,019
a couple of times where they love it.
366
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Thomas: I love that example because
often part of the journey is the change
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management internally with a team that
has a process that they're comfortable
368
00:19:54,394 --> 00:19:55,874
with and is getting to some results.
369
00:19:55,944 --> 00:19:58,144
Now you got to really have the motivation.
370
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There's some time saving element
here, obviously for recruiters, but
371
00:20:01,184 --> 00:20:05,444
then there's also this carrot of we
can actually make a case to help you
372
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convert, like in your case, have a
better employer value proposition and
373
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convert candidates better if we're able
to improve the offering effectively.
374
00:20:14,504 --> 00:20:14,544
That's
375
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interesting because I see the
parallels with sales, of course,
376
00:20:20,834 --> 00:20:23,124
but then also it's the...
377
00:20:23,134 --> 00:20:28,954
would you say that like your recruiters
were after that initial time where
378
00:20:28,954 --> 00:20:33,434
you're getting them board, did you
go through a pilot and then you got
379
00:20:33,434 --> 00:20:35,954
everyone's feedback and now we're
just like off and standardized that
380
00:20:35,994 --> 00:20:38,084
as a generally speaking as a process?
381
00:20:38,754 --> 00:20:39,121
Stefani: No, I just threw them in.
382
00:20:39,121 --> 00:20:40,974
said, They're rusting a pilot.
383
00:20:41,124 --> 00:20:42,044
I said, we're doing this.
384
00:20:42,884 --> 00:20:44,784
If it's terrible, I'll fix it.
385
00:20:44,974 --> 00:20:45,746
But let's try it.
386
00:20:45,746 --> 00:20:46,774
think it's going to be great.
387
00:20:46,839 --> 00:20:48,734
Our sales team was using it beforehand.
388
00:20:48,734 --> 00:20:52,244
And so I was able to sit down with
our SVP of sales and I'm like, show
389
00:20:52,244 --> 00:20:54,124
me your ways, show me the value.
390
00:20:54,124 --> 00:20:57,464
And I really did a ton of due
diligence on the front end.
391
00:20:57,564 --> 00:21:01,264
And then I said, they're going
to panic about the recording.
392
00:21:01,274 --> 00:21:02,114
I was right.
393
00:21:02,634 --> 00:21:04,394
But then they saw the value very quickly.
394
00:21:04,834 --> 00:21:08,104
And so I just, I jumped right in
and I showed them all of the why's.
395
00:21:08,714 --> 00:21:11,494
And I showed them all the
value and brought them along.
396
00:21:11,684 --> 00:21:16,254
And then they learned pretty quickly
that I was not incorrect in my selling.
397
00:21:17,341 --> 00:21:19,471
This has been a fantastic
conversation so far.
398
00:21:19,711 --> 00:21:22,501
If you haven't already done so,
make sure to join our community.
399
00:21:22,741 --> 00:21:25,411
We are building a network of the
most forward-thinking, HR and
400
00:21:25,411 --> 00:21:28,591
people, operational professionals
who are defining the future.
401
00:21:29,071 --> 00:21:31,681
I will personally be sharing
news and ideas around how we
402
00:21:31,681 --> 00:21:33,691
can all thrive in the age of ai.
403
00:21:34,051 --> 00:21:37,036
You can find it at go cleary.com/cleary
404
00:21:37,466 --> 00:21:38,076
community.
405
00:21:38,701 --> 00:21:39,541
Now back to the show.
406
00:21:40,564 --> 00:21:44,034
Thomas: And it's also an example where,
so you're at the level of setting the
407
00:21:44,034 --> 00:21:47,204
strategy and saying, Hey, we're going
to all do this at a company level.
408
00:21:47,204 --> 00:21:50,864
But then in your own function,
because arguably recruiters and
409
00:21:51,134 --> 00:21:53,944
any team member could potentially
propose any of these ideas.
410
00:21:53,984 --> 00:21:58,019
But yeah, I think at least what I'm
hearing is as a leader, doesn't.
411
00:21:58,639 --> 00:21:59,719
You don't have to stop there.
412
00:21:59,809 --> 00:22:03,079
You can go all the way into
let's try this particular tool
413
00:22:03,079 --> 00:22:04,529
for this particular process.
414
00:22:04,549 --> 00:22:07,639
And let's try that starting next
week and let's really roll up our
415
00:22:07,639 --> 00:22:11,719
sleeves and go and see where we
end up to really force the issue.
416
00:22:11,774 --> 00:22:13,629
It's like, see if you
can get to some results.
417
00:22:14,149 --> 00:22:17,349
But I'm very curious also about
the other one that you use case you
418
00:22:17,349 --> 00:22:21,789
mentioned on the L&D side, what's
been working or not working there.
419
00:22:23,599 --> 00:22:23,809
Stefani: Yeah.
420
00:22:24,049 --> 00:22:27,169
So content creation has been
the name of the game with that.
421
00:22:27,229 --> 00:22:29,859
We've used AI a lot on
the content creation side.
422
00:22:30,089 --> 00:22:35,839
But we're also starting to explore AI
on the L&D side around recommendations.
423
00:22:36,489 --> 00:22:38,959
So we don't have this one
100 % figured out yet.
424
00:22:39,029 --> 00:22:41,679
We're trying out some tools right
now where it can say, hey, the
425
00:22:41,679 --> 00:22:43,919
employee's performance is showing X.
426
00:22:44,449 --> 00:22:47,769
Maybe they need Y training.
427
00:22:48,114 --> 00:22:50,449
Or hey, the feedback is here.
428
00:22:51,099 --> 00:22:51,889
We recommend this.
429
00:22:51,889 --> 00:22:56,879
And so actually making recommendations,
I am transparently little more
430
00:22:56,889 --> 00:23:01,409
hesitant of how that works than I
was on the content creation side, but
431
00:23:01,439 --> 00:23:06,429
my L&D team is definitely using AI
significantly in content creation.
432
00:23:06,429 --> 00:23:07,279
It's speeding up.
433
00:23:07,539 --> 00:23:11,479
We've got a small but mighty L&D team
here and they're able to produce a lot
434
00:23:11,689 --> 00:23:16,099
more quickly the content that they're
supplying out to the organization.
435
00:23:16,739 --> 00:23:19,219
Thomas: Isn't there a similar risk
with that content creation side too?
436
00:23:19,229 --> 00:23:21,329
You're putting out AI slop.
437
00:23:21,384 --> 00:23:23,149
Usually you'd have really.
438
00:23:23,379 --> 00:23:26,999
Well thought through content for
a manager training or a specific
439
00:23:27,364 --> 00:23:28,639
functional kind of training.
440
00:23:28,639 --> 00:23:30,599
But now you're just, I
441
00:23:33,239 --> 00:23:34,429
don't know, expected to do more.
442
00:23:34,429 --> 00:23:36,229
Like we're to do 10
trainings instead of two.
443
00:23:36,229 --> 00:23:39,359
And then you devolve towards
stuff that's not as good
444
00:23:39,359 --> 00:23:41,189
basically, or not as effective.
445
00:23:41,459 --> 00:23:43,889
Like what are the guardrails
or how do you feel like you're
446
00:23:43,909 --> 00:23:45,259
on the content creation side?
447
00:23:45,259 --> 00:23:48,689
Cause I feel like that's the place
where it's easiest to start, but
448
00:23:48,689 --> 00:23:49,809
how do you protect against that?
449
00:23:49,899 --> 00:23:53,279
The quality not being to the same
level as you used to have it.
450
00:23:53,879 --> 00:23:54,149
Stefani: Yeah.
451
00:23:54,799 --> 00:23:59,209
This is definitely an area that my
team had to learn a little bit from
452
00:23:59,209 --> 00:24:03,789
when we first started this journey
a little over a year ago to today.
453
00:24:03,829 --> 00:24:06,924
And I did quarterly town halls
with all of my people team.
454
00:24:06,924 --> 00:24:09,114
And the last two, said,
okay, we're talking about AI.
455
00:24:09,114 --> 00:24:11,664
We have a whole section on AI
and we're going to talk about it.
456
00:24:11,984 --> 00:24:13,844
And it really has been around.
457
00:24:13,984 --> 00:24:15,864
I love that you guys are using it.
458
00:24:16,594 --> 00:24:19,994
I don't want to know that you're using
it by the product that's being produced.
459
00:24:19,994 --> 00:24:24,734
And so reminded my team of the ChatGPT's
of the world writing our emails.
460
00:24:24,774 --> 00:24:25,504
That's awesome.
461
00:24:25,644 --> 00:24:26,914
I love this for us.
462
00:24:27,464 --> 00:24:30,504
However, I don't want it to
sound like ChatGPT or your email,
463
00:24:30,514 --> 00:24:31,834
please make it sound like you.
464
00:24:31,884 --> 00:24:37,084
And so I really have had to actually take
examples of work product that I have seen.
465
00:24:37,264 --> 00:24:40,824
I review a lot of the things before
they go out to the organization,
466
00:24:40,854 --> 00:24:43,984
but I've had to take and say, look,
I knew this when we were in my AI.
467
00:24:43,994 --> 00:24:48,644
Here's how I knew and i've compared
it to things and I think showing them
468
00:24:48,644 --> 00:24:50,584
and just having that, I'm not upset.
469
00:24:50,594 --> 00:24:52,874
I'm the one that told you to go do this.
470
00:24:52,924 --> 00:24:54,474
I'm not upset at all.
471
00:24:54,489 --> 00:24:59,314
I just want you guys to understand
that there is a balance to it.
472
00:24:59,314 --> 00:25:01,054
AI is making us more efficient.
473
00:25:01,244 --> 00:25:05,754
AI is providing us a lot of value,
saving us a ton of time, but we
474
00:25:05,754 --> 00:25:08,354
are still responsible for humans.
475
00:25:08,414 --> 00:25:11,474
And there's a human on the other
side of every single thing that we
476
00:25:11,474 --> 00:25:13,254
do and we cannot lose sight of that.
477
00:25:13,609 --> 00:25:16,384
So even when it comes as
far as to automation, I'm
478
00:25:17,364 --> 00:25:18,844
pushing them to think through.
479
00:25:18,844 --> 00:25:20,854
If you received that as your response.
480
00:25:20,854 --> 00:25:24,934
If your chatbot responding that
way, how would you feel about that?
481
00:25:25,704 --> 00:25:30,524
If an employee uses the chatbot and
says, my mother just passed away.
482
00:25:32,194 --> 00:25:36,164
I do not want that chatbot to just respond
with here is the bereavement policy.
483
00:25:36,684 --> 00:25:39,094
We need to build it to notify us.
484
00:25:39,114 --> 00:25:42,334
And so a human can respond to
that because you need to know how
485
00:25:42,344 --> 00:25:44,034
you would feel if you got that.
486
00:25:44,364 --> 00:25:45,844
And so I'm doing that on the content side.
487
00:25:45,844 --> 00:25:49,624
If you were sitting in a room going
through this, are you going to
488
00:25:49,624 --> 00:25:54,364
feel like a machine did this or you
have to like a human invested time.
489
00:25:54,684 --> 00:25:57,504
So it's definitely a balance and
it's an area that we had to learn.
490
00:25:57,504 --> 00:26:01,494
And like I said, I was okay with saying,
I pushed you guys, but now I'm going
491
00:26:01,494 --> 00:26:03,164
to show you how we can get better.
492
00:26:03,294 --> 00:26:05,514
And we iterated together as a team.
493
00:26:05,524 --> 00:26:08,274
Thomas: Can't be the high school teacher
telling your kids to use ChatGPT and
494
00:26:08,274 --> 00:26:09,384
then complaining about plagiarism.
495
00:26:09,384 --> 00:26:09,414
But
496
00:26:11,924 --> 00:26:12,869
yeah, there's a balance here.
497
00:26:13,004 --> 00:26:15,674
like your approach of just thinking about
it from the customer standpoint, right?
498
00:26:15,689 --> 00:26:17,379
It's like an age old advice, right?
499
00:26:17,379 --> 00:26:18,819
That's still relevant.
500
00:26:18,869 --> 00:26:22,859
Put yourself in the customer's
shoes and what would you think?
501
00:26:22,859 --> 00:26:23,059
Right.
502
00:26:23,059 --> 00:26:24,669
And if people follow that.
503
00:26:24,759 --> 00:26:27,964
Because if you chase efficiency to
the end, you have to balance that
504
00:26:27,964 --> 00:26:31,714
right a little bit with the quality
from the customer's perspective.
505
00:26:32,084 --> 00:26:35,534
So it's like there's content creation,
but then you're playing with the idea
506
00:26:35,534 --> 00:26:39,019
of recommendations to keep people
think about what they could take next.
507
00:26:39,129 --> 00:26:41,679
So then you said there's a
whole roadmap of other ideas.
508
00:26:41,829 --> 00:26:44,164
What else are you like
excited about for 2026?
509
00:26:44,174 --> 00:26:48,409
What opportunities do you see and for
the organization to leverage more?
510
00:26:49,259 --> 00:26:51,869
Stefani: Yeah, our biggest area
that we went to best in from
511
00:26:51,869 --> 00:26:54,399
the people team is performance.
512
00:26:55,119 --> 00:26:59,209
I still think there's some more I can
add into the talent acquisition function.
513
00:26:59,309 --> 00:27:03,109
Our big joke is we actually use
ChatGPT to find our VP of AI.
514
00:27:03,204 --> 00:27:06,954
Very roundabout way, but it was
involved in the hiring of our VP of AI
515
00:27:07,144 --> 00:27:08,544
and it's one of our favorite stories.
516
00:27:08,554 --> 00:27:08,574
We
517
00:27:10,824 --> 00:27:14,514
want to really focus on the
performance side of things.
518
00:27:14,744 --> 00:27:19,334
Performance takes a lot of time
and not everybody loves it.
519
00:27:19,344 --> 00:27:25,294
Not everybody is as good from a leader
standpoint in having those discussions.
520
00:27:25,704 --> 00:27:28,864
There are several tools that we're
currently evaluating right now that can
521
00:27:28,864 --> 00:27:35,554
help us with some level of automation
with nine box AI performance review
522
00:27:35,554 --> 00:27:38,754
writing, which sounds very scary, but
that is where I'm checking a lot of
523
00:27:38,764 --> 00:27:42,444
boxes of saying, okay, but we have to
make sure the manager is able to say,
524
00:27:42,994 --> 00:27:45,664
yes, that is what I want it to say.
525
00:27:45,989 --> 00:27:50,084
And so that's really where we're
taking at least the first half of 2026.
526
00:27:50,084 --> 00:27:52,454
knows what the second half will
hold for us, but really that
527
00:27:52,454 --> 00:27:55,604
first half is continuing to invest
on the talent acquisition side.
528
00:27:56,544 --> 00:28:00,224
And then implementing some AI
enhanced performance tools.
529
00:28:00,414 --> 00:28:04,994
There's a lot of debate around this,
but AI can be less subjective when it
530
00:28:04,994 --> 00:28:09,484
comes to performance the tools that we're
currently looking at can pull data from
531
00:28:09,484 --> 00:28:11,474
a lot of areas and make recommendations.
532
00:28:11,504 --> 00:28:13,684
And I think at a minimum,
it's going to make the leader
533
00:28:13,684 --> 00:28:15,044
stop and go, you know what?
534
00:28:15,334 --> 00:28:16,114
That's probably correct.
535
00:28:16,204 --> 00:28:18,539
Thomas: That's an
interesting can of worms.
536
00:28:18,549 --> 00:28:25,639
Is AI more or less objective than
a human in its very context and
537
00:28:25,639 --> 00:28:28,919
model dependent, I'm sure the answer
there, but it's just intriguing
538
00:28:28,919 --> 00:28:30,239
that we can even ask that question.
539
00:28:30,589 --> 00:28:31,019
So yeah.
540
00:28:31,019 --> 00:28:35,239
There's so much value if you get it
right on the performance management side.
541
00:28:35,579 --> 00:28:38,109
But when you're talking about
that, my mind went to just your
542
00:28:38,109 --> 00:28:39,849
previous point immediately was...
543
00:28:40,969 --> 00:28:42,859
imagine now it's a higher stake, right?
544
00:28:42,859 --> 00:28:47,559
So if you're delivering L&D course
with some AI like looking wording
545
00:28:47,559 --> 00:28:50,649
in there that's one thing you're
telling someone you're probably
546
00:28:50,649 --> 00:28:54,499
going to go on a performance
improvement plan through AI writing.
547
00:28:54,519 --> 00:28:58,179
That's like a whole other impact
from the customer standpoint, you
548
00:28:58,299 --> 00:29:00,089
really have to guard against, right?
549
00:29:00,504 --> 00:29:03,954
If you're zooming out then a little bit
with me then, and we're just talking
550
00:29:03,954 --> 00:29:07,704
about the future in general, you have
so many different examples of ways that
551
00:29:07,704 --> 00:29:12,254
you're executing area by area, trying
different things and going with AI.
552
00:29:13,294 --> 00:29:16,544
What do you think, and that's a
crux of a lot of what we think about
553
00:29:16,644 --> 00:29:19,774
on the Future Proof HR podcast.
554
00:29:19,794 --> 00:29:22,754
What is the HR function in
the future like look like?
555
00:29:22,754 --> 00:29:26,874
What skills are important or
what's less and more expressed?
556
00:29:26,884 --> 00:29:27,764
How's it all shifting?
557
00:29:30,564 --> 00:29:33,314
Stefani: Yes, I continue
to be asked this question.
558
00:29:33,334 --> 00:29:33,654
And
559
00:29:36,324 --> 00:29:42,094
I think I see HR as a little bit
different over the last five years.
560
00:29:42,214 --> 00:29:43,864
I think the industry has seen it.
561
00:29:46,464 --> 00:29:49,439
Thomas: You mean pre AI revolution,
are you talking about COVID pandemic?
562
00:29:49,484 --> 00:29:51,544
Tell me about that first, then
we can talk about this next one.
563
00:29:52,004 --> 00:29:52,364
Stefani: Yeah.
564
00:29:52,834 --> 00:29:57,414
And I think I mentioned this when
I first met with you around HR is
565
00:29:57,434 --> 00:30:02,044
not a checklist admin function,
I have not seen it that way.
566
00:30:02,414 --> 00:30:08,644
And I think AI is just adding fuel to
this fire that has been within me of guys,
567
00:30:08,664 --> 00:30:10,484
we are not this is what we actually are.
568
00:30:10,744 --> 00:30:11,874
I've always felt HR
569
00:30:15,004 --> 00:30:18,334
is way more than what it's
given credit for a lot of times.
570
00:30:18,334 --> 00:30:21,754
And I'm fortunate at Propio that
I've been supported and been able
571
00:30:21,824 --> 00:30:23,274
to carry out that vision around.
572
00:30:23,334 --> 00:30:26,374
Propio HR is really
embedded in the business.
573
00:30:26,624 --> 00:30:27,974
We understand the business goals.
574
00:30:28,184 --> 00:30:29,644
We can anticipate their needs.
575
00:30:29,684 --> 00:30:33,014
We can help them drive impact
through their growth and performance.
576
00:30:33,084 --> 00:30:38,464
And so it's not just about ensuring simply
their compliance or processing forms.
577
00:30:38,824 --> 00:30:40,494
It's building on capabilities.
578
00:30:40,514 --> 00:30:42,444
It's strengthening our leadership team.
579
00:30:42,734 --> 00:30:44,564
And really it's helping to create
580
00:30:46,664 --> 00:30:50,334
programs or processes or
whatever it is that help the
581
00:30:50,344 --> 00:30:53,954
people perform at their best.
582
00:30:54,584 --> 00:30:57,194
And AI is just adding a fuel to that.
583
00:30:57,524 --> 00:31:03,224
And in a way it's catching up to where my
mind's at I've spent over the last five
584
00:31:03,224 --> 00:31:09,224
years, but AI is fundamentally shifting
HR from administrative to strategic.
585
00:31:09,804 --> 00:31:11,284
There is no way around that.
586
00:31:11,624 --> 00:31:14,644
And the real opportunity
is about replacing people.
587
00:31:14,844 --> 00:31:17,294
It's about amplifying the human community.
588
00:31:17,694 --> 00:31:20,294
I have always said it's not
employees, they're human capital.
589
00:31:20,344 --> 00:31:22,474
It is the most important
thing to a business.
590
00:31:23,144 --> 00:31:28,564
So AI is really just amplifying
the human capital's capabilities.
591
00:31:29,024 --> 00:31:33,944
And we are seeing, especially
Propio, we are seeing AI as a tool to
592
00:31:34,004 --> 00:31:35,884
streamline some of that routine work.
593
00:31:36,364 --> 00:31:39,434
The teams can focus on
higher value initiatives.
594
00:31:39,854 --> 00:31:43,784
And that's where I think
a lot of HR leaders and HR
595
00:31:43,854 --> 00:31:45,531
professionals are scared of AI.
596
00:31:45,531 --> 00:31:46,944
It's replacing my job.
597
00:31:46,944 --> 00:31:47,654
It's not.
598
00:31:47,784 --> 00:31:49,694
It's bringing you up to be more strategic.
599
00:31:49,704 --> 00:31:51,344
It's bringing you up to be a partner.
600
00:31:51,629 --> 00:31:55,564
It's allowing you to provide talent
strategy to an organization and
601
00:31:55,574 --> 00:31:59,324
driving culture and being in a
leadership development opportunity.
602
00:31:59,539 --> 00:32:03,974
It allows us to move much
faster, analyze data a lot more
603
00:32:04,314 --> 00:32:06,284
and a lot more intelligently.
604
00:32:06,444 --> 00:32:10,064
I just had somebody the other day
that said, I never trusted HR with
605
00:32:10,364 --> 00:32:14,064
numbers before you and before your
leadership here at Propio I didn't
606
00:32:14,064 --> 00:32:16,094
trust HR as far as their numbers go.
607
00:32:17,864 --> 00:32:20,484
That is going to get better because of AI.
608
00:32:20,844 --> 00:32:26,814
If HR leaders allow it to happen,
they are able to become a different
609
00:32:26,864 --> 00:32:28,852
version of themselves to the business.
610
00:32:28,852 --> 00:32:31,944
They're able to be that
person that has their numbers.
611
00:32:31,974 --> 00:32:34,734
Be able to provide insights
that we never were able to
612
00:32:34,734 --> 00:32:35,984
provide or would have provided.
613
00:32:36,034 --> 00:32:39,404
Would have taken us hours and days
to provide any sort of insights
614
00:32:39,404 --> 00:32:40,624
that may or may not be wrong.
615
00:32:40,634 --> 00:32:41,894
Now we don't have to do that.
616
00:32:43,644 --> 00:32:47,974
Thomas: I think your talent acquisition
implementation is an example of that.
617
00:32:48,009 --> 00:32:51,044
First of all, you're getting data and
you can say, no, really this is brought
618
00:32:51,044 --> 00:32:55,964
up in 80 % of the time in this market
when we're hiring for this role, they
619
00:32:55,964 --> 00:32:58,684
keep mentioning PTO and here is the data.
620
00:32:59,054 --> 00:33:03,424
It's hard to question that versus the
same conversation would have been, like
621
00:33:03,434 --> 00:33:07,714
the recruiters keep, we keep hearing this
and a couple of our key managers agree.
622
00:33:07,714 --> 00:33:10,624
So let's put this big investment
in to change the policy
623
00:33:10,674 --> 00:33:12,254
that would help us close.
624
00:33:12,544 --> 00:33:13,844
Or it's a very different conversation.
625
00:33:15,194 --> 00:33:18,994
Stefani: And I told my team, said,
HR will really in the future be
626
00:33:18,994 --> 00:33:22,814
defined as how can we effectively
blend technology and empathy?
627
00:33:23,014 --> 00:33:25,734
We can never lose the empathy
component of our world.
628
00:33:25,894 --> 00:33:30,914
How can we blend that technology and
the empathy and really use AI for
629
00:33:30,914 --> 00:33:33,434
efficiency versus human connection?
630
00:33:34,894 --> 00:33:39,124
Thomas: So you mentioned then it's going
to be less administrative as a function.
631
00:33:39,594 --> 00:33:43,294
But the way I see it is
that's not going away.
632
00:33:43,454 --> 00:33:46,714
The administration needs to happen, right?
633
00:33:46,714 --> 00:33:50,694
People need to be the hiring and firing
and like the benefits and all that.
634
00:33:51,024 --> 00:33:54,144
Do we agree that it's we're stacking on
top of that, but that's actually possible.
635
00:33:54,144 --> 00:33:57,864
So we're going up higher up the hierarchy
of needs for the organization, but
636
00:33:57,864 --> 00:34:00,834
we've never been able to get there, but
this stuff doesn't really disappear.
637
00:34:00,834 --> 00:34:00,864
it?
638
00:34:02,254 --> 00:34:03,144
Stefani: It doesn't disappear.
639
00:34:03,154 --> 00:34:09,444
But I think it's because of these tools,
we're able to do it quicker and we're
640
00:34:09,454 --> 00:34:13,373
able to add and in some ways we're
able to set up the systems to do it.
641
00:34:13,414 --> 00:34:17,744
And so instead of me going in and changing
this system, this and this, or my team
642
00:34:17,793 --> 00:34:22,784
going in and having a five step process,
this system is able to do that for them.
643
00:34:23,543 --> 00:34:24,464
They still need to check in.
644
00:34:25,373 --> 00:34:29,134
We're not going to get away from
I-9s or W-4s or whatever it is.
645
00:34:29,384 --> 00:34:30,514
Those are always going to be there.
646
00:34:30,514 --> 00:34:33,384
But the systems are making
them move much more quickly.
647
00:34:33,384 --> 00:34:37,094
And so the team, I think, are
still doing those, but the time
648
00:34:37,094 --> 00:34:38,543
it takes them is so much less.
649
00:34:38,543 --> 00:34:39,284
And so they're.
650
00:34:39,844 --> 00:34:44,184
They have so much extra capacity now
to where they can be those strategic
651
00:34:44,184 --> 00:34:45,277
partners to the business and understand
the business at a deeper level
652
00:34:45,277 --> 00:34:46,184
than we've been able to understand
653
00:34:48,494 --> 00:34:49,014
it before.
654
00:34:50,164 --> 00:34:50,474
Thomas: I love that.
655
00:34:50,704 --> 00:34:54,034
So can I ask also about just
the future of work a little bit?
656
00:34:54,603 --> 00:34:56,684
I think earlier when we
were talking about how
657
00:34:58,954 --> 00:35:02,594
the employer-employee relationship,
it might be shifting and it
658
00:35:02,609 --> 00:35:07,234
changes over the life cycle of an
employee of an employment period.
659
00:35:07,794 --> 00:35:12,234
And sometimes employees grow with
the company as a company shifting,
660
00:35:12,234 --> 00:35:14,084
or sometimes you grow apart.
661
00:35:15,239 --> 00:35:20,354
This is all, guess, age old, like people
leadership stuff, but how do you handle
662
00:35:20,354 --> 00:35:26,584
these kinds of conversations around
ensuring that as a company's pace is
663
00:35:26,584 --> 00:35:29,384
so in terms of changes so fast, right?
664
00:35:29,384 --> 00:35:32,474
What you're describing, which in
terms of employee growth, tooling
665
00:35:32,494 --> 00:35:36,704
mindset shifts, like process changes,
it's a lot that's like happening.
666
00:35:37,114 --> 00:35:37,909
You're throwing at people.
667
00:35:37,919 --> 00:35:40,869
How do you balance that with just ensuring
that you're bringing people along and
668
00:35:40,879 --> 00:35:45,919
having the right conversations to help
people grow into or out of appropriately?
669
00:35:47,359 --> 00:35:51,899
Stefani: Yeah, that conversation
is one I have, I shouldn't say
670
00:35:51,909 --> 00:35:53,159
I never shied away from it.
671
00:35:53,159 --> 00:35:57,159
I think early on in my career, I was
in the, my gosh, we lost a person.
672
00:35:57,159 --> 00:35:58,649
What are we going to do mindset?
673
00:35:58,679 --> 00:36:00,759
And I really shifted away from that.
674
00:36:00,799 --> 00:36:03,759
And now anybody that has gone
through an interview with me at
675
00:36:03,759 --> 00:36:05,409
Perprio, I have said the same line.
676
00:36:05,659 --> 00:36:08,619
This place, it's not
the place for everybody.
677
00:36:08,689 --> 00:36:09,949
And I'm okay with that.
678
00:36:10,259 --> 00:36:14,539
I tell people if you want a manual
that I can pull off of a shelf and
679
00:36:14,539 --> 00:36:15,939
say, this is how we've always done it.
680
00:36:15,939 --> 00:36:17,239
This is how you're going to do it.
681
00:36:17,239 --> 00:36:19,869
This is exactly the key to success.
682
00:36:20,399 --> 00:36:21,869
Harbor is not the right place for you.
683
00:36:21,869 --> 00:36:26,199
And I know that there's talent out there
that are phenomenal at what they do,
684
00:36:26,199 --> 00:36:27,889
but it's not the right place for them.
685
00:36:28,339 --> 00:36:30,369
I've had people on my
team since I've been here.
686
00:36:30,369 --> 00:36:31,649
I'm like, you're a great person.
687
00:36:31,949 --> 00:36:35,249
I think you're great for a
business, just not this business.
688
00:36:35,649 --> 00:36:40,119
And so I think that can be scary
because sometimes turnover is
689
00:36:40,169 --> 00:36:42,409
looked poorly upon as a leader.
690
00:36:42,649 --> 00:36:46,469
It's not always now, obviously I could
go down a rabbit hole of when it is.
691
00:36:46,679 --> 00:36:47,939
But it's not always.
692
00:36:48,089 --> 00:36:53,019
So I think the way that I handled it,
and especially at Propio is just with
693
00:36:53,039 --> 00:36:54,849
honesty and transparency and respect.
694
00:36:55,299 --> 00:36:57,819
I've brought people
along said, here's why.
695
00:36:58,899 --> 00:37:01,659
My team knows all the changes we're
making, why we're making them.
696
00:37:02,229 --> 00:37:03,469
Pros and cons to it.
697
00:37:03,509 --> 00:37:05,534
I try to approach them very self-aware.
698
00:37:05,854 --> 00:37:08,104
I know this isn't going to
be a perfect change for us.
699
00:37:08,104 --> 00:37:10,914
I know this might give you a headache
or a little bit of heartburn here.
700
00:37:12,294 --> 00:37:14,274
I'm through this with you guys.
701
00:37:14,574 --> 00:37:17,564
And so I've been very
transparent with them on the
702
00:37:17,564 --> 00:37:19,034
changes that we've had to make.
703
00:37:19,304 --> 00:37:22,584
But also when team members have come
to me or I've had to have conversations
704
00:37:22,594 --> 00:37:26,224
with team members, I don't feel
like you're loving this anymore.
705
00:37:26,644 --> 00:37:30,024
Let's talk about that because
I want them to succeed.
706
00:37:30,024 --> 00:37:33,214
I think unhappy people do unhappy work.
707
00:37:33,614 --> 00:37:34,744
And that's not good for them.
708
00:37:34,764 --> 00:37:36,614
And it's not good for Propio.
709
00:37:36,954 --> 00:37:39,954
And I just want to have
that conversation with them.
710
00:37:39,984 --> 00:37:42,684
If one of my team members says,
you know what, I don't, I can't
711
00:37:42,684 --> 00:37:43,664
handle the change anymore.
712
00:37:44,534 --> 00:37:46,604
Okay, the acquisitions are getting to me.
713
00:37:46,774 --> 00:37:47,804
Okay, I get that.
714
00:37:49,234 --> 00:37:49,984
I understand it.
715
00:37:50,004 --> 00:37:53,924
And let's figure out a way that we
can support you on your way out.
716
00:37:53,954 --> 00:37:55,624
You can support us on your way out.
717
00:37:55,624 --> 00:37:56,604
Let's do this together.
718
00:37:56,604 --> 00:38:02,894
And so I think being able to
listen to this is hard on me.
719
00:38:03,114 --> 00:38:03,884
It is hard.
720
00:38:04,074 --> 00:38:07,614
You never want to hear an employee say,
of this change is driving me crazy.
721
00:38:07,744 --> 00:38:10,514
That's hard to hear because
the leaders were excited about
722
00:38:10,514 --> 00:38:11,364
it and were ready to do it.
723
00:38:11,364 --> 00:38:13,224
But I think if you can say, I did it.
724
00:38:13,424 --> 00:38:17,234
Look, it's a lot and it's not a good
fit for you, then you're putting
725
00:38:17,234 --> 00:38:20,154
yourself, the business and that
employee in a better position.
726
00:38:22,134 --> 00:38:25,544
Thomas: Yeah, that's
tough, but transparent.
727
00:38:25,594 --> 00:38:25,614
The
728
00:38:27,674 --> 00:38:30,544
thing I'm thinking about is
if that's like the posture.
729
00:38:30,544 --> 00:38:32,544
How do you stay people first, right?
730
00:38:32,684 --> 00:38:36,344
Which is a big part of the ethos where
really what we're talking about is
731
00:38:36,399 --> 00:38:41,109
a rapid acceleration of change that
everyone is experiencing throughout the
732
00:38:41,109 --> 00:38:42,509
world, but certainly in the workplace.
733
00:38:42,839 --> 00:38:47,989
But really a lot of that is being
driven by the AI enablement of
734
00:38:48,079 --> 00:38:49,869
so many things like shifting.
735
00:38:50,274 --> 00:38:53,022
Is there like a universal skillset
that is going to come into the fore
736
00:38:53,022 --> 00:38:54,422
for everyone across every company?
737
00:38:54,422 --> 00:38:57,122
I know you're commenting of
course about your organization and
738
00:38:57,362 --> 00:38:58,292
what you're like seeing through.
739
00:38:58,292 --> 00:39:01,627
But if you're stepping back out and
reflecting a little bit, generally
740
00:39:01,627 --> 00:39:05,677
speaking, what is it going to be
meaning for any HR leader where
741
00:39:05,727 --> 00:39:08,867
many of us are committed to being
people first and investing in the
742
00:39:08,867 --> 00:39:11,777
people in an AI enabled world?
743
00:39:13,967 --> 00:39:15,997
Stefani: Yeah, it's a great question.
744
00:39:15,997 --> 00:39:23,197
And I think when I look at it, I
do not see AI as replacing people.
745
00:39:23,477 --> 00:39:27,242
And everything that we are doing
with AI, we're asking what is
746
00:39:27,247 --> 00:39:29,017
the impact on the employees?
747
00:39:29,047 --> 00:39:30,497
What is the impact on the client?
748
00:39:30,557 --> 00:39:32,307
What is the impact on the end user?
749
00:39:32,747 --> 00:39:36,157
And so I think as long as you don't
lose sight of the people first,
750
00:39:36,197 --> 00:39:37,947
you're able to successfully do it.
751
00:39:38,327 --> 00:39:39,779
And I say people operate AI.
752
00:39:39,779 --> 00:39:41,457
And that's what I tell
my team all the time.
753
00:39:41,457 --> 00:39:44,977
I said, we've got to have a team
that can operate the machines
754
00:39:45,277 --> 00:39:46,597
that are doing all of these tasks.
755
00:39:47,177 --> 00:39:49,507
And people are the ones that
are coming up with the ideas.
756
00:39:50,012 --> 00:39:52,457
A machine didn't tell our executive
team, here's what you guys should
757
00:39:52,457 --> 00:39:53,537
do over the next 12 months.
758
00:39:53,657 --> 00:39:55,527
We had to come up with those ideas.
759
00:39:55,732 --> 00:39:58,817
And so what I really spent my time on
is what I mentioned earlier with my
760
00:39:58,817 --> 00:40:00,567
team is how is a person receiving this?
761
00:40:01,297 --> 00:40:04,657
It might've been done
in a third of the time.
762
00:40:04,747 --> 00:40:05,767
Great for you.
763
00:40:06,287 --> 00:40:09,497
But if it makes a person not
feel good, you've lost them.
764
00:40:09,587 --> 00:40:13,227
And my team hears these two
words more than anything.
765
00:40:14,127 --> 00:40:14,957
What is the experience?
766
00:40:16,527 --> 00:40:17,587
It's people experience.
767
00:40:19,347 --> 00:40:21,337
And that is what I will always do.
768
00:40:21,367 --> 00:40:24,647
So when we're sitting, going through
and we're building the responses,
769
00:40:24,667 --> 00:40:27,877
we're building the automations,
we're building out all these things.
770
00:40:28,397 --> 00:40:30,177
How would you feel if you got that?
771
00:40:30,597 --> 00:40:33,607
I think I'm probably the negative
Nellie in all of these implementation
772
00:40:33,627 --> 00:40:36,007
calls of I wouldn't love that.
773
00:40:36,337 --> 00:40:40,257
And also we've all sat on Amazon
or target or whoever's chat bot
774
00:40:40,267 --> 00:40:43,327
trying to return something and we
all have wanted to throw our phones
775
00:40:43,327 --> 00:40:45,447
out the car window while doing so.
776
00:40:46,457 --> 00:40:46,647
I just remember-
777
00:40:46,647 --> 00:40:46,907
yelling
778
00:40:47,207 --> 00:40:49,757
Thomas: like a decade ago,
yelling operator into the phone.
779
00:40:50,187 --> 00:40:50,617
Stefani: Yes.
780
00:40:50,757 --> 00:40:52,877
I just want an agent.
781
00:40:52,907 --> 00:40:53,217
Yes.
782
00:40:53,487 --> 00:40:56,647
bring those examples up to my
team all the time of I never want
783
00:40:56,647 --> 00:40:57,937
our employees to feel like that.
784
00:40:57,937 --> 00:41:00,837
At the end of the day, our team is
literally called the people team.
785
00:41:01,087 --> 00:41:01,887
We can never forget that.
786
00:41:03,457 --> 00:41:04,187
Thomas: Absolutely.
787
00:41:04,277 --> 00:41:10,347
As you look ahead and as our time is
closing out here, what are some things
788
00:41:10,357 --> 00:41:14,862
that you're like really excited about the
next stage of growth and transformation
789
00:41:14,892 --> 00:41:18,372
at Propio or for the HR team?
790
00:41:19,842 --> 00:41:20,972
Stefani: It's what I don't know.
791
00:41:21,312 --> 00:41:27,422
That's honestly what I'm so excited
about is it is I describe Propio
792
00:41:27,422 --> 00:41:30,082
as a good type of crazy and it
will always ring true to me.
793
00:41:30,082 --> 00:41:32,012
I don't know what is next.
794
00:41:33,652 --> 00:41:38,262
I don't think we had a great idea, our CEO
might tell me different, but I don't think
795
00:41:38,262 --> 00:41:42,692
that we had this thought that we would be
able to do for acquisitions in 18 months.
796
00:41:43,022 --> 00:41:44,548
I don't think any of us thought that.
797
00:41:44,562 --> 00:41:48,142
I didn't think that we would be able
to completely retool and function the
798
00:41:48,142 --> 00:41:50,682
HR team within less than two years.
799
00:41:51,112 --> 00:41:54,692
And those things were not
always on the roadmap, but they
800
00:41:54,692 --> 00:41:56,032
were opportunities that came.
801
00:41:56,032 --> 00:41:59,787
And so for me, what I'm most excited
about for my team, for Propio as
802
00:41:59,832 --> 00:42:03,362
a whole, and for the HR industry
is we don't know what's coming.
803
00:42:03,632 --> 00:42:04,772
None of us saw COVID.
804
00:42:05,422 --> 00:42:08,672
I'm sure somebody saw AI, I
did not see AI coming at the
805
00:42:08,672 --> 00:42:10,112
speed in which it came to us.
806
00:42:10,272 --> 00:42:16,992
So it's just having the mentality and
loving what I do so much of I don't
807
00:42:17,002 --> 00:42:18,222
know what's going to get thrown at us.
808
00:42:18,222 --> 00:42:19,852
Let's figure this out together.
809
00:42:20,122 --> 00:42:23,292
We might have a headache after that
day, but we're going to figure it out.
810
00:42:23,537 --> 00:42:25,052
I think is what I'm most excited for.
811
00:42:25,052 --> 00:42:28,522
Just we don't know what's coming and I
can't wait to see what's in store for us.
812
00:42:29,722 --> 00:42:30,352
Thomas: Absolutely.
813
00:42:30,362 --> 00:42:34,762
I think that is a great thought as
any to end this conversation Stefani.
814
00:42:34,902 --> 00:42:39,762
Because the future is unwritten, there
is a lot we can learn from all of
815
00:42:39,762 --> 00:42:44,022
these different projects that you've
gone through, both from the executive
816
00:42:44,042 --> 00:42:47,962
alignment to change management
and how you thought about that.
817
00:42:48,792 --> 00:42:52,792
Not just top down, but also bottom up and
how you've also rolled up your sleeves
818
00:42:52,792 --> 00:42:55,302
into getting into specific projects.
819
00:42:55,682 --> 00:42:57,792
We went to some great examples
across the employee life
820
00:42:57,792 --> 00:42:59,442
cycle and HR programs, right?
821
00:43:01,562 --> 00:43:02,912
There's no dearth of
822
00:43:03,012 --> 00:43:04,362
projects or ideas, right?
823
00:43:04,362 --> 00:43:08,402
For ways that people, depending
on the journey they're on and the
824
00:43:08,402 --> 00:43:12,322
phase of the organization where they
can't find some room to experiment.
825
00:43:12,352 --> 00:43:16,142
And I love your focus on mindset,
because that came up a bunch around
826
00:43:16,492 --> 00:43:18,962
like what you're expecting from
the employee population, as well as
827
00:43:18,962 --> 00:43:24,002
the HR team to actually move things
forward and all the nuances associated
828
00:43:24,002 --> 00:43:26,322
with the communication, right?
829
00:43:26,322 --> 00:43:32,032
From the leadership position and the
HR team more broadly in interaction
830
00:43:32,042 --> 00:43:33,302
with the overall organization.
831
00:43:33,702 --> 00:43:35,212
Thank you for sharing all this.
832
00:43:35,232 --> 00:43:38,122
And you say you're a negative
Nelly, but on the other hand, you're
833
00:43:38,122 --> 00:43:39,982
also pushing to try everything.
834
00:43:39,992 --> 00:43:42,062
But I guess it's two
sides of the same coin.
835
00:43:42,062 --> 00:43:44,462
Like we got to try everything,
but that's a fail fast, right?
836
00:43:44,462 --> 00:43:48,030
But we got to be open to really evaluating
whether this is working for us or
837
00:43:48,030 --> 00:43:49,492
not, but we got to keep evaluating.
838
00:43:49,862 --> 00:43:53,157
And I suspect as you keep doing that,
the muscle just gets built and she
839
00:43:53,157 --> 00:43:56,687
just, the whole team just gets better
at it and more efficient at it.
840
00:43:56,697 --> 00:43:58,437
And it gets more fun, hopefully.
841
00:43:58,517 --> 00:44:00,637
And less of those days with
headaches, as you mentioned.
842
00:44:01,267 --> 00:44:02,617
Thank you for this conversation.
843
00:44:02,687 --> 00:44:05,967
For everyone who's listening out
there and who's looking at ways to
844
00:44:05,967 --> 00:44:08,807
future-proof their own organizations
and their own HR functions.
845
00:44:09,157 --> 00:44:10,717
I think there are several nuggets.
846
00:44:10,757 --> 00:44:14,687
Hopefully you have taken away from
this chat and to Stefani once again,
847
00:44:14,687 --> 00:44:18,727
thank you for this conversation
and see you on the next one.
848
00:44:18,827 --> 00:44:19,287
Bye now.
849
00:44:20,171 --> 00:44:23,231
Thanks for joining us on this
episode of Future Proof HR.
850
00:44:23,471 --> 00:44:26,081
If you like the discussion, make
sure you leave us a five star
851
00:44:26,081 --> 00:44:28,961
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852
00:44:29,381 --> 00:44:32,321
Or share this with a friend or colleague
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853
00:44:32,621 --> 00:44:37,571
See you next time as we keep our pulse on
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