Building an AI-First Culture: Embedding AI in the Rhythm of Work

Lauren Tropeano: 00:00:00

How can you ask people to come on this journey unless you

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enable them to be successful on it?

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That would be like me saying to you,

like, hey, I want you to sail across an

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ocean, but you've never sailed before.

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Oh, my gosh.

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But yeah, but we're giving you a sailboat.

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We're giving you like the tool, but you

don't necessarily know how to navigate it.

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You don't know what you're expecting.

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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 Kunjappu: Welcome to the Future

Proof HR Podcast, where we explore

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how forward-thinking HR leaders are

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preparing for disruption and

redefining what it means to

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lead people in a changing world.

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I'm your host, Thomas

Kunjappu, CEO of Cleary.

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Now, today's guest is Lauren

Tropiano, the Chief people Officer

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at Docebo, a global AI-first learning

platform supporting HR and L&D teams

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around the world.

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With a thousand employees

across North America

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and EMEA, Lauren is helping lead Docebo's

transformation from the inside out.

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Translating product ambition

into internal people strategy.

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Through a company-wide AI academy,

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intentional mindset work, and L&D

experimentation, she's helping

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the org to unlock innovation,

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one team at a time.

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Lauren, welcome to the podcast.

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Lauren Tropeano: Thank

you so much, Thomas.

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So excited to be here and

talk all things AI with you.

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Thomas Kunjappu: Absolutely.

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Give us some context about

Docebo, the product, the

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company, because I think that's

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going to be very relevant to

our conversation today, right?

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Lauren Tropeano: Yeah, absolutely.

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So Docebo is a global company,

like you just mentioned.

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We have about a thousand employees.

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We are a leader in AI first

learning, and we provide a

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multi-use platform to companies

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of all sizes, enterprise businesses,

as well as more mid-market

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businesses that help organizations

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unlock learning and endless

potential in their employee bases.

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And yeah, we've been

around for about 20 years.

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And we are just so excited about what

we've got going this AI horizon right now.

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We're really leading the charge

in the industry on modernizing

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learning and making sure that we're

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a leader in this space right now

as companies are really trying to

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meet the mandate of how to bring AI

and uplevel all of their employees

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to grow and learn in this new way.

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So yeah, that's a little bit about Docebo.

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Thomas Kunjappu: That's exciting.

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So I want to talk a lot about what you're

doing and leading by example internally.

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But before we get into that, I'd like

to just ask you to opine or share

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your thoughts on what

is the transformation.

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What is happening with learning in

the workplace more broadly, and how

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should companies be looking to respond?

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Lauren Tropeano: Learning's

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changing a lot.

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The concept is still there, such as

we need humans, we need our people

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to grow skill sets and evolve,

but the modalities with which

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people are learning are changing.

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And that's very similar to how

people consume content, right?

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Like they don't really

read a newspaper anymore.

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Some people do, but they consume

content on TikTok, on LinkedIn, on

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all different types of platforms.

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The days of going to a physical training

or a classroom setting, those again,

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those forums do still exist, but

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there are many more modalities and much

more of a focus on personalization and

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micro learning and things like that.

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So we are building tools and evolving

our product every single day with all of

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our new product releases to really make

sure that we're meeting the needs of the

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modern learner and that we are both also

able to deliver content and technology

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tools that unlock that learning in an

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expedient way, as well as also

making sure that we're supporting

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L&D professionals as they evolve

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the function and how content gets created

and authored and all of that as well.

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So I think

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personalization's king right

now in this conversation and

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AI is helping us unlock a lot

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of that, which is really exciting.

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Thomas Kunjappu: So let's

zoom out even further.

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What would you say makes this AI

transformation or this kind of industry

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shift feel different from others

you've been involved with in the past?

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Lauren Tropeano: As an HR person, as

a people person, we've been managing

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changes, major transformations

and changes for a long time.

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You think about the journey to the

private cloud or even like COVID, right?

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That was like a massive transformation

in how companies worked, right?

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It's like overnight,

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organizations were in offices

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and then everybody had to

be in a distributed format.

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That's like wild, right?

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But the interesting thing

about this transformation

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is I think it's so exciting

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because we have no idea

what's around the next corner

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because the technology is changing so much

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and it is so fluid.

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And I think that's both a little, it's

both exciting, but a little bit scary.

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I also think companies have

the opportunity to author

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what this next step means

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for them and how they actually ingest

this period of change and all of that.

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So I think a more exciting time to be in

a transformation because it's not specific

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to a business strategy, but it

is actually the next horizon

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of how work itself is changing.

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And it is pervasive across all

industries and all environments.

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was just reading an article where it was

like, interior designers are using this.

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Electricians are using it.

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Chefs are using it for recipes.

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It's not just recipes.

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It's not just a corporate thing.

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AI is really changing the

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way that people like do their work.

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And I think that's so exciting.

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Thomas Kunjappu: Yeah,

it sounds like it's like

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more foundational, right?

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Yeah.

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So it's there's promise and peril.

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It's unsettling, but also

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there's opportunity.

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Lauren Tropeano: Yeah.

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Thomas Kunjappu: You're swimming in it.

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So if you're thinking about

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Docebo, would you say that I think

when we're talking previously, there's

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this concept of an AI first org and

orienting the organization in that way.

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Would you say that's you guys?

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And if so, what does that mean?

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Lauren Tropeano: Yeah, absolutely.

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For sure.

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We've really adopted

that moniker internally.

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And I think you need to name

that for your organization

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because it really, I think, sets

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a tone of we really want to be embedding

this into our operating system and

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our mindsets and just how we work.

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We want to be AI first, meaning

that we are not only obviously

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building products in this space,

but we ourselves are operating in

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such a way that's our orientation.

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It is not just like, oh, an afterthought

or just some type of a tool that we use.

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It is like in the rhythm of our business.

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So yeah, I think it's important

to really be explicit with that

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as you're trying to influence

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organizational change.

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And we have, yeah.

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Thomas Kunjappu: So let's go

more in depth and internally.

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What does that mean at Docebo

from a people process, systems,

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reinforcement, maybe L&D

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perspective to have that posture.

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And if you were talking to

your peers about maybe creating

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a shift like that for their

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organization, or maybe there's

the demand for that from executive

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team or the CEO or board,

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and you're trying to figure out a

strategy to shift in that direction.

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What are the kind of the levers that you

have and the activities that you might

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put in place to move in that direction?

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Lauren Tropeano: Yeah.

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It first starts with your vision, which

our vision is very embedded in being

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an AI first technology and AI first

learning company that unlocks that value.

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So it starts with your vision

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and then everything I

think stems from that.

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What that practically means is

really have to be overt with, again,

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talking about this all the time.

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You have to understand also by

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doing discovery, which is something

that we've done, where are you

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on the spectrum of AI awareness

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or adoption or innovation so that you can

understand your starting point, right?

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So one

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thing that we did was we

actually embedded in our mid-year

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performance reviews, we embedded

a question, which is not meant

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to be like a rating or anything,

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but it was more a calibration

exercise for us to understand

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where we are as a company.

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We just created a very simple four-point

scale from AI aware to AI innovator.

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And we asked managers and employees

to rate themselves on where do you

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think you are on this spectrum?

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And that was really meant to

inform where are we today?

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Where do we hope to be?

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Obviously

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we hope to be more on the innovator

side, but it's really important

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for us to understand the current

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place of the company so that

we can help bring people along.

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And so it starts with just again, like

just doing a diagnosis of where are you?

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Where do you want to be?

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And then helping people come

along the journey and also

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thinking about that journey as

something that is really exciting

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and an invitation to learn

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and experiment and do all those

things as opposed to it being

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for otherwise otherwise like for

a lot of people might be like,

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oh, this is scary, this

is new, this is temporary,

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those types of things.

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And we really wanted to be explicit

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around how we're inviting people

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to come on this journey

with us and experiment.

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One of the other things that I would say

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is really important to

the enablement of this

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sort sort of posture within

a company is that you

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have to have a really great set

of tools that are available to

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people and you have to give them

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almost like a marketplace

to choose from, right?

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So most companies have ChatGPT or

they have Gemini, depending upon

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what tools and technologies are

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available, but we have a phenomenal

internal IT department and

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they have done a great job in

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partnering with all areas of the

business to really understand like,

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what are the business practices

that you're constantly working on?

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Like, how are your business operations,

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how can they be made more

efficient through AI tools?

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Or what are the things

that you're spending

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a lot of time on so that they can help

to recommend for us some different tools

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or technologies that can help make the

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adoption of AI really easy because it

adds a lot of value for our people.

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And that partnership with IT

has been huge for us as we

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bring in like a myriad of really

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exciting apps for people to just

experiment and play around with.

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Thomas Kunjappu: I think that's an

interesting point because I know

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you're not calling it a mandate,

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but by having a vision and

kind of really pushing this new

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way of working for everyone,

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for it to relate for anyone in their

day-to-day, if there's friction

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between what they're hearing

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at that messaging level and what

they actually need to do, which

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is a bunch of whatever it is,

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a bunch of manual tasks or a bunch of

collaboration that needs to happen.

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Yeah.

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If you're able to connect a specific work

task that will help move the ball forward.

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But a key piece of that is having

a technology forward partners

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maybe your IT org who can

actually help you those dots.

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But IT can't help you unless

the folks on the ground know

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what are the potential pain

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points that can be solved better with AI.

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Lauren Tropeano: Yeah, for sure.

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For sure.

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And that partnership is so

important because we're able

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to articulate the rhythm of our

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work and our business.

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And then they're able to really provide

us with, oh, hey, there's this tool.

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How would that potentially help us?

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So they're almost like an

internal consultancy for us that

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brings us some interesting new

opportunities to experiment with.

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And in most functions as well,

we have an AI champion or a

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small team of people who are like

AI champions who are those early

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adopters or those first movers

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within the organization that are really

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closely partnering with their IT

partner to provide that guidance

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or be the one to be in a pilot or

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something like that.

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And so those people are really helping

to lead the charge, provide those

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technical requirements and things

like that, and then ultimately

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be the voice within the function

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that can help bring people along.

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And I think that's an important piece too,

because you do need those champions in any

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type of a change that are

going to have that credibility

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within the function versus to

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your point, like feeling like

something was imposed upon

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you because people don't like

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that.

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Thomas Kunjappu: And just

because get very practical.

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So these champions, are they official?

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Is there, do they have badges or badges?

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Do they have dinner parties?

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Or is it completely organic and

natural and it happens or doesn't

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in different parts of the org?

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Because I'm really

trying to get practical.

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Because if you're really trying to

make this change happen, how much

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is it bottom up versus top down?

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Lauren Tropeano: I would say it's

pretty, we've been very lucky in

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that it feels quite grassroots.

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Like we didn't have to actually

impose all of this structure

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around it just because there

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was a lot of excitement about it.

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And I think that partly comes

from the products that we're

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building and the tremendous value

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that we see like our customers being

able to unlock like through this.

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So people are like just also excited

to utilize these things themselves.

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But yeah, I would say it's

not a super formalized effort

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and different organizations.

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I'm sure that

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there are a lot more like formally

committees and things like that.

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We do have a group like a

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consortium type group that's

coming together to share best

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practices and things like that.

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But for the most part, it feels

grassroots and it's mostly voluntary

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in the sense of if someone's really

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excited about it, then

they can get involved.

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And that I think is the best

way to do it because it really,

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again, it's like a self-led thing.

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And that energy, it's

like, it's contagious.

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You can't really

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create that unless someone is

passionate about this topic themselves.

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So those are the people

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that I think are the best fit

for these types of things.

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Thomas Kunjappu: So tell me

more about something that I

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think is more explicit, which you've

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invested in, which is

the internal AI Academy.

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Yeah.

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In some ways, like the baseline, or you

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want to have everyone to get

to this level of learning.

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Tell me more about how that came about,

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what it is, outcomes.

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Lauren Tropeano: Absolutely.

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So my peer on our executive

team, we have a Chief Learning

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Officer because we are a learning company.

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And so that's a unique role that not every

company has, but we do have the benefit of

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having one here at Docebo.

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So he is my peer and he and I

were talking about, okay, we

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really want to lead this company

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through this transformation.

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How can we make sure that what

we're asking of people is really

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practical and approachable

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and also that everyone is

starting from a common foundation.

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We put our heads together and we

came up with this idea of this AI

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Academy, which is a homegrown academy.

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And what we did was we took

someone who was previously in a

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product kind of marketing role

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and brought him over to

the learning function.

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And he was then tasked with,

let's create this essentially

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like this internal product that we

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can give to all of our employees

to start them on this journey.

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And that would give us the peace of

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mind that everybody in our company

is essentially like de facto,

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like certified in understanding

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these like AI foundations.

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And to be honest, we're still building it.

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We launched the first, I would say like

the first module or the first iteration of

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it this summer, and it's been going great.

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We had very high completion

rates and people really loved it.

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Essentially what it is, we went out to the

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organization, we asked them, like,

what would you like to know about AI?

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Like, where are you?

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Like, what things are you afraid of?

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: 00:16:00

What do you feel like you need to

know in order to talk to customers,

335

: 00:16:02

in order to talk to customers, in order to

336

: 00:16:04

talk to your peers, in order to adopt

this in a really thoughtful way?

337

: 00:16:08

And so we got all that

338

: 00:16:09

information.

339

: 00:16:09

And then that team was able to pull

together this academy, which covers

340

: 00:16:15

things like AI language, right?

341

: 00:16:17

Like, what are some of

these technical terms?

342

: 00:16:19

that are being used.

343

: 00:16:20

What do we practically mean about that?

344

: 00:16:23

What are some best practices in terms

345

: 00:16:25

of using AI responsibly?

346

: 00:16:28

Like, what information

should we share with LLMs?

347

: 00:16:30

What shouldn't we share?

348

: 00:16:31

And how do we actually use it?

349

: 00:16:33

Meaning that we have like internal

licenses here at Docebo that can help

350

: 00:16:37

us protect our proprietary information.

351

: 00:16:39

You shouldn't just go out on your

352

: 00:16:40

personal account, like

governance, things like that.

353

: 00:16:42

And then also just just really good

prompting, how to interact with it.

354

: 00:16:47

And then also how to sort of apply

your human logic to make sure that

355

: 00:16:51

whatever you're getting out of the AI

is actually makes good sense, right?

356

: 00:16:55

Because we know sometimes

357

: 00:16:57

AI gives us answers to things,

but sometimes they don't

358

: 00:17:00

always make the most sense.

359

: 00:17:01

So we still do

360

: 00:17:02

have to apply our common logic.

361

: 00:17:03

So those are just like some of the things.

362

: 00:17:05

But yeah, it's a journey.

363

: 00:17:06

And we thought, hey, we can't expect

people to come on this journey,

364

: 00:17:09

but not enable them, especially

as a learning company.

365

: 00:17:12

This was something that was developed

366

: 00:17:13

just this year and just rolled out

and people have loved it so far.

367

: 00:17:17

So continuing to build it

368

: 00:17:18

upon that.

369

: 00:17:43

Thomas Kunjappu: So one of the points

I think you've subtly made is that

370

: 00:17:47

because Docebo is learning company

371

: 00:17:50

and an AI-first company

and the product does that.

372

: 00:17:53

Obviously you have a lot of talent who

373

: 00:17:55

is naturally excited and working

in the world of AI like every day.

374

: 00:18:01

And yet it might vary by department

and in context and experience.

375

: 00:18:06

So you're doing this AI academy to bring

people at least to some baseline together

376

: 00:18:10

and share in that learning journey

as you point the direction forward

377

: 00:18:15

and be aligned in the path forward.

378

: 00:18:17

Has that impacted your point of

view on onboarding or recruiting

379

: 00:18:22

for the organization as well?

380

: 00:18:24

Lauren Tropeano: Yeah.

381

: 00:18:24

On the point of recruiting, and I'll

cover onboarding in a moment, to

382

: 00:18:28

the point of recruiting, we actually

built in specific questions into

383

: 00:18:33

our initial screens to screen for

384

: 00:18:38

AI competency.

385

: 00:18:39

Now, we're not looking for AI

expertise in all roles, but we

386

: 00:18:42

want curiosity and some competency

387

: 00:18:46

or awareness for every single

person that we hire at Docebo.

388

: 00:18:50

So it could be like a simple question

like, tell me about how you use AI

389

: 00:18:57

in your everyday work, or how have

you used AI to improve your efficiency

390

: 00:19:03

or the outcomes or impact of a

391

: 00:19:06

specific deliverable or

project or something like that.

392

: 00:19:09

So for us, it's just testing

393

: 00:19:11

for curiosity around the topic,

experimentation around the topic,

394

: 00:19:15

some of those characteristics

395

: 00:19:18

that we are really looking

to really build upon here.

396

: 00:19:21

So that's how we've just, again, started

to very simply and very tactically

397

: 00:19:26

just infuse that into the screen.

398

: 00:19:28

Now, if someone is like a deer

399

: 00:19:29

in the headlights, it's okay.

400

: 00:19:30

Maybe they're not, maybe they're

not the most competent in this area.

401

: 00:19:35

And we should just step back and

reflect, is this a good fit for the

402

: 00:19:39

very strong culture we're trying

to build around AI literacy and

403

: 00:19:42

competency and all of that, and really

like a curiosity for this topic.

404

: 00:19:45

So it's not, again, like a binary

405

: 00:19:47

yes or no, but it is something

that helps to give us some signals,

406

: 00:19:51

hopefully positive signals that

407

: 00:19:52

they'll be able to adapt to the

strong like AI learning culture

408

: 00:19:56

that we're building right now.

409

: 00:19:58

Thomas Kunjappu: I love that as a

babysit before we go on to onboarding,

410

: 00:20:00

I just want to reflect on that

411

: 00:20:01

because you're, I think in some

ways having an admission that

412

: 00:20:05

where we don't know where this is

413

: 00:20:06

going to go, what kind of

specific skillset tools

414

: 00:20:09

process you're going to need.

415

: 00:20:10

But given the prevalence of this

technology globally for a few years

416

: 00:20:16

now, we want you to at least be curious

about it and showcase that you're

417

: 00:20:20

using it personally in some kind of way.

418

: 00:20:22

And that's where you're started.

419

: 00:20:23

I wonder if the way this

420

: 00:20:24

evolves is that for each function,

if you're in customer support

421

: 00:20:29

or in sales or in marketing,

422

: 00:20:30

there's going to be much more

specific expectations over

423

: 00:20:35

time that start to become like

industry-wide, if not credentials,

424

: 00:20:38

but at least signs of competence.

425

: 00:20:40

Because it would be like if you're

asking someone in finance, like,

426

: 00:20:44

do you know QuickBooks or some other

kind of tool versus doing pen and paper

427

: 00:20:49

for doing all of your corporate finance?

428

: 00:20:52

It's not something you

even ask after a while.

429

: 00:20:53

It's just a very baseline expectation.

430

: 00:20:56

But I think this is a sign that we're at

the nascent stage of the technology that

431

: 00:21:01

on the recruiting front, we're really

just trying to filter for curiosity.

432

: 00:21:04

Lauren Tropeano: And also maybe even take

that a step further, like a point of view.

433

: 00:21:07

Like, oh, I do use this and I

also use it in my personal life.

434

: 00:21:11

And I'm excited for these

435

: 00:21:12

use cases.

436

: 00:21:13

And it helps to give us a little

bit of a window into how excited

437

: 00:21:19

the individual is about embracing

438

: 00:21:22

this technology in this moment

in terms of transforming

439

: 00:21:26

themselves as an individual, as

440

: 00:21:27

well as a professional.

441

: 00:21:29

And that is, again, when you think about

a characteristic of an employee or a trait

442

: 00:21:33

of an employee versus like a skill,

which is like when you use that

443

: 00:21:36

when like that QuickBooks analogy

444

: 00:21:39

it's like anyone can learn a

software per se but there's like

445

: 00:21:42

an inherent curiosity about this

446

: 00:21:45

space that's what we're looking

for more so than like a skill

447

: 00:21:48

that we could teach which would be

448

: 00:21:50

like the difference between the software

versus, again, like an inherent curiosity

449

: 00:21:54

about something that's really new.

450

: 00:21:57

Thomas Kunjappu: I was just thinking

back to maybe the 80s when personal

451

: 00:22:01

computing and software do something

452

: 00:22:03

like finance and it's like a new thing.

453

: 00:22:05

And if you're that world and

you've experienced that, it's

454

: 00:22:13

a market for that curiosity that

455

: 00:22:14

you're talking about in that

different eras, but eventually

456

: 00:22:17

it just becomes, there's no jobs

available unless you're doing that.

457

: 00:22:21

But if that's where the

458

: 00:22:22

technology evolves.

459

: 00:22:23

But let me ask you more about mindset.

460

: 00:22:24

Cause this is interesting.

461

: 00:22:25

Cause you said the server, you get

a sense of like where people are

462

: 00:22:28

at in terms of their AI adoption.

463

: 00:22:31

And then you're leveraging other surveys

and just inputs to understand what

464

: 00:22:35

you want to put in

terms of the AI Academy.

465

: 00:22:37

But if you zoom that out to

just the broader population or

466

: 00:22:40

just think about any industry.

467

: 00:22:42

Earlier you were telling me about how

the applications are endless, right?

468

: 00:22:46

Like it's in personal life.

469

: 00:22:48

It's not just corporate.

470

: 00:22:49

It's all types of industries.

471

: 00:22:50

across the board.

472

: 00:22:51

And yet the things that you mentioned,

like people feel like it's scary,

473

: 00:22:54

it's unsettling.

474

: 00:22:55

I don't know if this is

just the flavor of the day.

475

: 00:22:58

There's been other trends that

476

: 00:22:59

have come up and down that this

too shall pass my industry or my

477

: 00:23:02

job is safe slash it's the same.

478

: 00:23:04

Or there's like a not quite that

mindset of it doesn't apply here, maybe.

479

: 00:23:09

I just want to stress

test this with you, right?

480

: 00:23:11

Is this mindset do you

think, globally applicable?

481

: 00:23:14

I know what we've been talking about

is Docebo and what you're seeing there.

482

: 00:23:17

But if we're going to look at any industry

and any employee and or CHROs who are

483

: 00:23:24

in vastly different kinds of industries

484

: 00:23:27

and company sizes and locations,

485

: 00:23:29

what are some of the boundaries

or are there any, right?

486

: 00:23:32

Or is this, generally speaking,

globally useful thinking, do you think?

487

: 00:23:36

Lauren Tropeano: I do

think it's globally useful.

488

: 00:23:38

And again, there's

489

: 00:23:39

a lot of layers and nuance to that,

depending upon what line of work you do.

490

: 00:23:44

Certainly if you're a

491

: 00:23:45

technologist or you're developing these

types of products, your purview for this

492

: 00:23:52

type of work or the level of depth that

you'll need to go into is way different

493

: 00:23:55

than someone who may be experimenting

with this in their personal life

494

: 00:24:00

and doesn't yet have any opportunity even

to utilize this in their professional

495

: 00:24:05

capacity because it's still nascent.

496

: 00:24:07

But I think that this is, again, as I

mentioned, I think it's like fundamental

497

: 00:24:12

shift in how we are working as people.

498

: 00:24:17

It's not, It's like a new

tech, it's like the internet.

499

: 00:24:20

Like it's just like everything's

just done online now.

500

: 00:24:22

It's like the new way of doing things.

501

: 00:24:24

How that gets espoused in

different roles or different

502

: 00:24:27

industries, I think we will see

503

: 00:24:30

over the next coming years.

504

: 00:24:31

And I think it's going to

rapidly iterate and be adopted.

505

: 00:24:35

But I do think that this is one of

those moments where it's pretty sticky.

506

: 00:24:39

I think this is a new way of working.

507

: 00:24:41

And I don't necessarily think that

this is going to go analog anytime

508

: 00:24:47

soon or that we're going to move

509

: 00:24:48

away from this.

510

: 00:24:49

But I do think there will be, again,

degrees of adoption and degrees of

511

: 00:24:52

relevance based on the type of work that

512

: 00:24:55

you do.

513

: 00:24:56

Even the most human-centered

jobs, physicians and doctors and

514

: 00:25:02

therapists and people who are

515

: 00:25:04

doing deeply humanly connected

work are using AI in different

516

: 00:25:09

capacities, not maybe necessarily

517

: 00:25:11

for all dimensions of their work, but

certainly as a sidekick to help unlock

518

: 00:25:17

research and productivity and writing

and like those types of things too.

519

: 00:25:22

So I think there's

520

: 00:25:23

like universal application.

521

: 00:25:26

Thomas Kunjappu: I think that's right.

522

: 00:25:27

Yeah.

523

: 00:25:28

For doctors, even like all

524

: 00:25:30

these examples that you're

saying, like you're, it's just

525

: 00:25:32

going to be you're just going to,

526

: 00:25:33

it's got to be your psyche if you

want to be both efficient, but also

527

: 00:25:38

accurate or better at your job.

528

: 00:25:41

So does that mean if I was translating

that specifically, does it make sense

529

: 00:25:46

for every academy to have some

version or every company to have

530

: 00:25:49

some version of an AI academy?

531

: 00:25:51

Lauren Tropeano: I think so.

532

: 00:25:51

Thomas Kunjappu: Or

like, when would it not?

533

: 00:25:53

Lauren Tropeano: I think so,

because how can you ask people to

534

: 00:25:55

come on this journey unless you

enable them to be successful on it?

535

: 00:25:59

That would be like me saying to you,

like, hey, I want you to sail across an

536

: 00:26:07

ocean, but you've never sailed before.

537

: 00:26:09

Oh, my gosh.

538

: 00:26:10

But yeah, but we're giving you a sailboat.

539

: 00:26:12

We're giving you like the tool, but you

don't necessarily know how to navigate it.

540

: 00:26:15

You don't know what you're expecting.

541

: 00:26:17

Like the waters, that's a

little bit of an interesting

542

: 00:26:20

analogy, but it's quite similar.

543

: 00:26:21

It's like you can give people the

technology, but you have to help

544

: 00:26:25

them learn it and get educated

545

: 00:26:26

and comfortable in that

new dimension as well.

546

: 00:26:30

So I think it's incumbent

upon organizations

547

: 00:26:34

to actually set their people up

for success and not just throw

548

: 00:26:36

them into the deep end of, oh,

just figure it out type thing.

549

: 00:26:40

And I do know organizations

are doing that.

550

: 00:26:42

And it's like

551

: 00:26:43

a sink or swim.

552

: 00:26:43

Well, if people can't get on board,

then they maybe don't belong here.

553

: 00:26:46

And

554

: 00:26:47

I feel that's a bit, that's a bit

harsh for people because this is

555

: 00:26:51

a new, you just made that analogy.

556

: 00:26:53

It's like, this is a new way

of working for many people.

557

: 00:26:56

And I think it's incumbent upon us

to enable that and enable it in a

558

: 00:27:00

way that feels safe and fun and like

exploratory as opposed to punitive or

559

: 00:27:06

forced or those types of things

that really makes an impression on

560

: 00:27:09

people favorably or unfavorably.

561

: 00:27:13

Thomas Kunjappu: That's interesting

because that you mentioned that because

562

: 00:27:15

I'm connecting the dot between that and

the concept of return to office being

563

: 00:27:20

for many companies being like an implicit

way to do round of layoffs when you're

564

: 00:27:26

not actually trying to announce that,

but you're just trying to come up with

565

: 00:27:30

some policies that make it effectively

sink or swim or just change things up

566

: 00:27:34

on people pretty quickly and then expect

attrition and call it good attrition.

567

: 00:27:40

But there's a similar

568

: 00:27:41

thing here, right?

569

: 00:27:41

So we're an AI first company.

570

: 00:27:43

All right, here's all the

tools, go nuts, right?

571

: 00:27:46

And then you're going to have

different levels of success with

572

: 00:27:48

that as from a learning development

573

: 00:27:49

background.

574

: 00:27:49

So let's talk about the HR

department a bit itself.

575

: 00:27:55

So actually, first of all, just

576

: 00:27:56

within Docebo, as you enabled the AI

Academy, as well as just everything

577

: 00:28:00

that you're seeing in terms of

578

: 00:28:02

demand shift from your organization,

from the employees to your

579

: 00:28:05

organization in HR, what is

580

: 00:28:07

different, if anything?

581

: 00:28:08

Does your function

start to feel different?

582

: 00:28:13

Are people's day-to-days starting

583

: 00:28:14

to feel different?

584

: 00:28:16

How is that changing?

585

: 00:28:17

Lauren Tropeano: We're on our own

transformation journey, right?

586

: 00:28:20

So there's the company.

587

: 00:28:21

So actually, let me

step back even further.

588

: 00:28:24

There's the industry that's transforming.

589

: 00:28:26

There's the company that's

590

: 00:28:27

transforming to support the industry

or to even lead the industry.

591

: 00:28:31

And then there's the different

592

: 00:28:32

functions within a company that

need to evolve and grow to support

593

: 00:28:35

the company's transformations.

594

: 00:28:37

So we, as a people team, are

also going through this journey.

595

: 00:28:41

And I would be remiss if I said,

596

: 00:28:41

as a people team are also going through

this journey and I would be remiss if

597

: 00:28:42

I said oh yeah we've got it

all figured out because we

598

: 00:28:44

absolutely don't and that is

both I think like very real and

599

: 00:28:50

also it's still exciting because

600

: 00:28:52

we're still writing

this story because again

601

: 00:28:55

a lot of this is evolving

602

: 00:28:56

what I can say that we are doing is we

use an OKR kind of methodology for goals

603

: 00:29:01

and things like that here at Docebo.

604

: 00:29:03

One of the OKRs that we have

each quarter is to have everybody

605

: 00:29:09

on the HR team, like adopting

606

: 00:29:11

some type of AI rhythm

into their work, right?

607

: 00:29:14

To either unlock efficiency or unlock,

again, some form of impact in their role.

608

: 00:29:20

And so, again, that goes back to just...

609

: 00:29:23

Thomas Kunjappu: Sorry,

this is global, right?

610

: 00:29:24

You're not

611

: 00:29:24

talking about the HR team,

this concept of unlocking some

612

: 00:29:27

kind of efficiency with an OKR?

613

: 00:29:29

Lauren Tropeano: Yes.

614

: 00:29:29

Yeah.

615

: 00:29:30

So that is like a global ask, but specific

to the people team, I have asked each

616

: 00:29:36

person on my team.

617

: 00:29:37

And I think it's important

to just highlight that this

618

: 00:29:39

isn't like an ask of the

619

: 00:29:40

HR team, because often it

is assumed that these types

620

: 00:29:44

of things are happening in technology

teams only, that GNA doesn't

621

: 00:29:48

do this stuff or people teams

622

: 00:29:50

don't do this stuff.

623

: 00:29:52

But we need to be explicit users of

this technology like adopters so that

624

: 00:29:58

we can lead the charge again,

within this change for the company.

625

: 00:30:02

So yeah, we are trying

to find all different

626

: 00:30:05

types of opportunities.

627

: 00:30:06

Like it could be something

as simple as like my TA team.

628

: 00:30:09

Like we, we had a problem with not

problem, but like a challenge, I would

629

: 00:30:13

say with people taking comprehensive notes

630

: 00:30:16

in interviews.

631

: 00:30:16

So it's okay.

632

: 00:30:17

Let's just get them a sidekick

so that we can get higher quality

633

: 00:30:21

notes that then can give us insights

634

: 00:30:23

into the interview outcomes, right?

635

: 00:30:26

That's a very sort of common use

case, but it's just something

636

: 00:30:30

that we were adopting.

637

: 00:30:31

Or how can we make sure that our

people ops team that answers employee

638

: 00:30:38

inquiries and things, they're

not answering the same

639

: 00:30:41

question over and over again.

640

: 00:30:42

We're actually using

an enterprise-wide tool

641

: 00:30:45

that we use Glean that can

help serve up information

642

: 00:30:48

for people through a simple just question.

643

: 00:30:51

And we actually don't even

need a human interacting

644

: 00:30:53

in that environment, right?

645

: 00:30:55

So there's very, again, nascent

business cases that are coming up.

646

: 00:30:59

But I think the biggest

thing is just inviting people

647

: 00:31:02

to think about this as how do

we build this into our workflow?

648

: 00:31:06

So that's one thing that we're

649

: 00:31:08

doing that has, I think, like

really signaled a shift in how we

650

: 00:31:12

work as an HR team, as a people

651

: 00:31:13

team.

652

: 00:31:14

And then beyond that, it's like, how do

we really, again, think about enabling the

653

: 00:31:20

organization on this journey?

654

: 00:31:22

And that's not,

655

: 00:31:24

it's not just like in the

traditional sense of like, how

656

: 00:31:26

do we use AI, but like, how do we

657

: 00:31:28

lead an AI first organization, right?

658

: 00:31:32

What is our posture or like

our point of view on employees

659

: 00:31:37

using AI to write white papers

or things like that, right?

660

: 00:31:41

Because I don't know, back even just a

661

: 00:31:44

few years ago, it was taboo somewhat

to use AI to author pieces of

662

: 00:31:50

work and then call it your own

663

: 00:31:52

or things like that.

664

: 00:31:52

But it's how do we actually think about

developing a point of view around this?

665

: 00:31:57

And then also, what are those...

666

: 00:31:58

skills and competencies that

we believe are really important

667

: 00:32:01

for this like modern leader

668

: 00:32:03

in this type of environment to have.

669

: 00:32:06

So there's a lot of different

ways that we are thinking about

670

: 00:32:09

this and trying to adjust and

evolve our HR team, but it's still

671

: 00:32:12

definitely a work in progress for sure.

672

: 00:32:15

Thomas Kunjappu: I love that concept of

embedding the projects into the rhythm of

673

: 00:32:21

your planning process or existing process.

674

: 00:32:23

In this case,

675

: 00:32:25

there's like a quarterly OKR rhythm

and you're just forcing everyone

676

: 00:32:28

to stop and reflect and say,

677

: 00:32:29

okay, what am I going to be doing

in this next quarter that's aligned

678

: 00:32:32

with this particular pillar?

679

: 00:32:34

It's a very practical way

of translating the vision

680

: 00:32:39

into action throughout the organization.

681

: 00:32:41

And great example on governance issues

that just keep cropping up across the

682

: 00:32:44

board, which is, I think one of those

things, I think these subtle items

683

: 00:32:49

where the people team might

be asked to do, I think I hear

684

: 00:32:53

constantly to do more with less.

685

: 00:32:55

And that's one of those, another

one of those subtle things of,

686

: 00:32:57

oh, here's another more that

687

: 00:32:59

like maybe you weren't handling before.

688

: 00:33:01

Sticking with the people team, the HR

function, how do you think budgets are

689

: 00:33:06

evolving in response to the AI era?

690

: 00:33:10

As a naive CFO might

say, everything that is

691

: 00:33:16

not revenue generating, we want

to be as efficient as possible.

692

: 00:33:20

Let's cut, cut, cut.

693

: 00:33:22

And really,

694

: 00:33:22

look, now we have AI tools, tooling for

everything to just enable everything

695

: 00:33:27

from just invoices to payroll to

just all the administrative work to

696

: 00:33:32

just everything that we need to do

697

: 00:33:33

there.

698

: 00:33:33

And so we can be ever leaner

than ever before, because this

699

: 00:33:38

goes into the fundamental thrust

700

: 00:33:39

of what we like to talk about here

is what is the opposing view to that?

701

: 00:33:43

How do we future-proof HR as a

function in response to that kind

702

: 00:33:47

of thinking, which I think is going

to be more and more pervasive.

703

: 00:33:51

Lauren Tropeano: I have a

couple of thoughts on this.

704

: 00:33:53

The first is with any transformation,

705

: 00:33:55

you're typically trying to build something

that's a bit more future-proof while still

706

: 00:34:01

running a highly functioning business.

707

: 00:34:04

So it's that analogy of changing

the tires on a bus while

708

: 00:34:06

you're driving on the highway.

709

: 00:34:07

It's hard to do.

710

: 00:34:08

So I think the, maybe the naive,

711

: 00:34:11

dare I call it like point of view

that, oh, okay, we now have AI.

712

: 00:34:15

So that can just like

713

: 00:34:17

cut tons of money out of our budget.

714

: 00:34:19

I feel like that's a bit

dangerous of a point of view,

715

: 00:34:22

because I still think AI

is a great enabler, but you

716

: 00:34:27

still need human beings and

717

: 00:34:30

employees to guide that AI or

to inform that AI or even build

718

: 00:34:35

process around things that are being

719

: 00:34:37

automated and to transfer

knowledge and things like that.

720

: 00:34:41

So I think it would be naive to think

721

: 00:34:44

that it could be like a light switch

that you turn off and then you

722

: 00:34:47

turn something else on right away.

723

: 00:34:49

It's like any sort of

technology implementation.

724

: 00:34:52

It takes time,

725

: 00:34:53

right?

726

: 00:34:53

So that's the first thought I had on that.

727

: 00:34:54

The second thought is, I have

a point of view where work

728

: 00:34:58

for humans isn't going away.

729

: 00:35:00

AI is actually

730

: 00:35:04

a commodity for all businesses,

meaning that all businesses could

731

: 00:35:09

potentially have access to ChatGPT or

Glean or whatever these things are.

732

: 00:35:13

The thing that makes the AI really

unique and useful and powerful in

733

: 00:35:17

organizations is actually the coupling

of the AI with the human beings that

734

: 00:35:21

you have in your business.

735

: 00:35:22

Because the humans are like the unique

flavor, the thing that differentiates

736

: 00:35:29

how AI gets utilized, adopted, integrated,

built, whatever, into your organization.

737

: 00:35:36

And that is, and humans

are not commodities

738

: 00:35:39

in any way, shape, or form,

739

: 00:35:40

which is why we're so beautiful,

740

: 00:35:42

because everybody is unique and messy

741

: 00:35:44

and all the things that come with it.

742

: 00:35:47

But there is, so I don't necessarily

743

: 00:35:49

think, again, they're like a one

for one, like certainly certain

744

: 00:35:52

roles will be massively changed

745

: 00:35:55

and disrupted in some ways.

746

: 00:35:57

But going into the idea of how do

we future proof the HR organization,

747

: 00:36:02

I see AI as like a massive enabler

to a function that has always been

748

: 00:36:07

traditionally resource constrained.

749

: 00:36:09

So it's, oh, wait, we still have to

do this foundational body of work,

750

: 00:36:13

which is keep the lights on work,

751

: 00:36:15

but how can we have AI do that

stuff so that the human beings

752

: 00:36:19

that are in our department

753

: 00:36:20

and our function are actually

able to do the strategic, highly

754

: 00:36:24

valuable work that can actually

755

: 00:36:26

propel a business forward

much more strategically?

756

: 00:36:29

I think it's like a massive

opportunity, but I don't

757

: 00:36:31

necessarily think it's like a zero

758

: 00:36:33

sum game, like in the sense of we embed

all this AI and then we just have like

759

: 00:36:38

budgets getting decimated.

760

: 00:36:40

I think that's a pretty dangerous,

honestly, uninformed point of view.

761

: 00:36:44

It's not to say that we won't

have cost savings because we will

762

: 00:36:46

for sure in terms of maybe you

763

: 00:36:48

don't like add as many roles in the

future because of efficiencies or

764

: 00:36:52

whatnot but i still think you're

765

: 00:36:54

there's always going to be a space

for like how humans will interact

766

: 00:36:58

with technology that's been

767

: 00:37:00

the motion for the past like

since we've had technology.

768

: 00:37:02

Thomas Kunjappu: Yeah and

arguably that's been the

769

: 00:37:04

evolution of the function

right because it used to be the

770

: 00:37:06

benefits function where it's by

771

: 00:37:09

definition administrative, like the

things that you just put in that layer

772

: 00:37:12

of just saying that we just can, it's

not the human side at all and evolved

773

: 00:37:16

to HR and people like slowly and

774

: 00:37:19

subtly over time.

775

: 00:37:21

So it's not a zero-sum game maybe, but

then there are definitely some skill

776

: 00:37:25

sets, right?

777

: 00:37:25

And activities that'll be

more expressed in the future.

778

: 00:37:28

Sure.

779

: 00:37:29

So what do you think those are

for folks in HR who are looking

780

: 00:37:32

to future-proof their careers

781

: 00:37:34

as they're thinking about

experiences or skill sets they

782

: 00:37:37

should really try to gather?

783

: 00:37:39

I assume one of them would just be trying

to be AI curious and seeing how we can

784

: 00:37:43

do something in whatever role they're in.

785

: 00:37:45

But anything beyond that, if you

think about the actual roles that

786

: 00:37:48

are going to be expressed more

often than not in the future?

787

: 00:37:51

Lauren Tropeano: Yeah, for sure.

788

: 00:37:51

Obviously, the ability

to interact with and know

789

: 00:37:55

how to be really strategic with AI as

again, like a tool is going to be huge.

790

: 00:38:02

But I really think that juxtaposing that.

791

: 00:38:05

technology with the deeply human

skill sets is where people are

792

: 00:38:09

going to, you'll never be able

793

: 00:38:11

to replace that.

794

: 00:38:11

So things like coaching

as an example, right?

795

: 00:38:13

Yes, there are AI coaches

and Docebo has one, right?

796

: 00:38:17

However, there is so much

nuance in a conversation.

797

: 00:38:22

The ability to read facial expressions.

798

: 00:38:24

The ability to like understand body

language, the emotional complexity

799

: 00:38:29

of a conversation is something that

800

: 00:38:31

humans have been wired through

millions of years of evolution to

801

: 00:38:36

really understand in a way that

802

: 00:38:37

I just don't think

machines understand yet.

803

: 00:38:40

So it's like those

deeply human things, also

804

: 00:38:43

communications, right?

805

: 00:38:44

We're going to have a lot of work that

gets automated, but we need to still

806

: 00:38:49

bring people along, inspire them, create a

807

: 00:38:52

vision, create excitement, like

all of those things that, again,

808

: 00:38:56

evoke these emotions in people.

809

: 00:38:58

Those are deeply human things

that are, that human beings are

810

: 00:39:01

uniquely like designed to do,

811

: 00:39:03

right?

812

: 00:39:03

So like those types of skill sets.

813

: 00:39:05

Also just the ability to

really understand a business

814

: 00:39:09

and what we're trying

to accomplish and then

815

: 00:39:11

be able to filter that

through the lens of people.

816

: 00:39:13

And that's just the strategic

mandate of an HRBP or someone

817

: 00:39:18

in the people organization.

818

: 00:39:20

That is always going to be a skill set

that I think helps you interpret and

819

: 00:39:24

contextualize what is important to the

business through then the people lens.

820

: 00:39:29

So those are just skill sets

that I would say are very

821

: 00:39:32

future proof for any HR person.

822

: 00:39:36

Thomas Kunjappu: Got it.

823

: 00:39:36

So then if you were going to take

that point of view and imagine

824

: 00:39:41

you're talking to someone who's

just coming out of college and is

825

: 00:39:43

looking to get into the function,

what advice would you have for them?

826

: 00:39:48

Lauren Tropeano: I would say get

off of your phone and meet people in

827

: 00:39:51

person and have human conversations.

828

: 00:39:55

And the reason I say that is because so

much of what emerging generations are

829

: 00:40:00

doing is like digital, which is great.

830

: 00:40:02

That's just the way that they interact.

831

: 00:40:04

But we cannot lose our skills

for interacting as human beings.

832

: 00:40:10

We can't lose that way of connecting, the

way of knowing people deeply on a very

833

: 00:40:17

personal level outside of technology.

834

: 00:40:20

Again, it's so rudimentary,

835

: 00:40:22

but I do worry about people's

ability to navigate social

836

: 00:40:27

situations, situational context,

837

: 00:40:29

things like that.

838

: 00:40:30

Because of the influx of the use

of technology and how some of the

839

: 00:40:34

earlier generations are interacting.

840

: 00:40:36

Yeah.

841

: 00:40:37

So that would actually be, I would say,

like really make it, make an effort

842

: 00:40:41

to get to know people and

to connect in real life.

843

: 00:40:46

Thomas Kunjappu: Yeah.

844

: 00:40:46

I think there's a real challenge there

845

: 00:40:47

because we were talking about

L&D and transforming an existing

846

: 00:40:50

organization and employees.

847

: 00:40:52

And we're like, in my

mind, I'm thinking about

848

: 00:40:55

like mid-career folks, 'cause

there's a lot of context

849

: 00:40:57

that you're bringing in value to the

organization, just knowing how work

850

: 00:41:00

works and also how this company works.

851

: 00:41:03

And then you're investing

in transforming them.

852

: 00:41:05

But then the pipeline from high school

or college the first jobs that's

853

: 00:41:11

really being disrupted a little bit.

854

: 00:41:13

And there's a little bit of a gap

here, both from what I can tell,

855

: 00:41:18

like AI tool usage leading to lower

demand for entry-level kind of

856

: 00:41:23

work in a lot of functions.

857

: 00:41:24

But also the other side is a bigger

gap in preparedness from college or

858

: 00:41:29

high school because of their social

reasons, but also just the COVID

859

: 00:41:35

is a part of it.

860

: 00:41:36

But that's a whole gap

861

: 00:41:37

that's also impacting how we're

going to be able to train the

862

: 00:41:42

get the next set of recruits.

863

: 00:41:45

We're going to be relatively like

AI native and tech native and went

864

: 00:41:49

through the COVID kind of shift.

865

: 00:41:51

But maybe that's a whole other deeper

conversation about the pipeline.

866

: 00:41:56

Lauren Tropeano: Yeah, for sure.

867

: 00:41:57

And I'll just say one quick thing

868

: 00:41:58

about that because I do have

a high school age daughter and

869

: 00:42:01

it's been so fascinating to just

870

: 00:42:04

kind of see how she interacts

like in an educational setting

871

: 00:42:07

and with friends and things

872

: 00:42:08

like that.

873

: 00:42:08

But I will say I'm very hopeful

about this next generation

874

: 00:42:12

coming in because they will be

875

: 00:42:15

the ones that are disrupting and We've

always worked this way, but there's

876

: 00:42:19

actually a better way or a different way.

877

: 00:42:21

So I think that they're going to

juxtapose a lot of the historical,

878

: 00:42:25

traditional ways of working

with this new, innovative ways.

879

: 00:42:28

And I think if we can actually

figure out a way to combine these

880

: 00:42:32

two sort of way different things,

881

: 00:42:35

we can maybe extract

the best of both worlds

882

: 00:42:38

and provide like this,

883

: 00:42:39

like mentorship and sage wisdom

with a lot of like disruptive

884

: 00:42:44

creativity for how to do things way

885

: 00:42:46

differently.

886

: 00:42:47

I think that could be like really

like explosive in a good way.

887

: 00:42:50

Like it could be a little

888

: 00:42:51

messy and stuff like that too, but I

think it could be really interesting.

889

: 00:42:54

So we'll see.

890

: 00:42:55

Jury's

891

: 00:42:55

still out, but yeah, I have a front

row seat to that here at home.

892

: 00:43:01

Thomas Kunjappu: There you go.

893

: 00:43:01

I guess mine's coming up.

894

: 00:43:02

I'm behind on that journey.

895

: 00:43:04

But I think that's a great

optimistic note as any to end on.

896

: 00:43:08

Can I ask, Lauren, if folks want

to connect with you or follow your

897

: 00:43:11

work, how can they best do that?

898

: 00:43:13

Lauren Tropeano: Yeah, they

can find me on LinkedIn.

899

: 00:43:14

So Lauren Tropiano, I'm the CPO of Docebo.

900

: 00:43:17

That's probably the best place where

I share insights and just takes and

901

: 00:43:22

things like that.

902

: 00:43:22

So feel free to connect

with me, follow me there.

903

: 00:43:25

And I'll look forward to

just continuing to share some

904

: 00:43:27

interesting nuggets of information

905

: 00:43:29

as we continue on this AI

transformation journey.

906

: 00:43:32

Thomas Kunjappu: That's wonderful.

907

: 00:43:33

So thank you so much

for this conversation.

908

: 00:43:35

The many layers that we talked

about around the industry

909

: 00:43:39

itself changing with L&D

910

: 00:43:41

and how you guys as a product, you're

thinking about that and leading that.

911

: 00:43:44

And then at a global

912

: 00:43:46

company level, you have a whole shift

to being AI enabled and AI native.

913

: 00:43:50

And we talked about the AI academy, as

well as, of course, how you're thinking

914

: 00:43:54

about that in the HR function itself.

915

: 00:43:56

And I love these practical guides

about translating the vision

916

: 00:44:00

into, for example, like OKRs.

917

: 00:44:03

That's an advertisement

918

: 00:44:04

for rhythmic planning of some kind.

919

: 00:44:07

Putting that on paper

920

: 00:44:07

to force the organization

921

: 00:44:09

at some scale to move in that direction.

922

: 00:44:11

And I think we came to

923

: 00:44:13

some really interesting

924

: 00:44:14

thoughts around where are, if

there are any boundaries around

925

: 00:44:18

the need for an organization

926

: 00:44:20

to have an AI academy or

enablement of with learning.

927

: 00:44:24

And maybe there really aren't any,

928

: 00:44:25

if we can think of so many use cases

around for personal use cases and

929

: 00:44:29

literally in any industry, maybe it pays

to have some kind of simple investment,

930

: 00:44:34

if nothing else, to try to up-level,

931

: 00:44:36

up-skill folks in this direction.

932

: 00:44:38

And it feels like a major direction

933

: 00:44:40

of what even you're doing in L&D.

934

: 00:44:43

What is the outcome that

you're trying to produce

935

: 00:44:45

no matter the industry

and the organization?

936

: 00:44:47

And of course, thank you for your thoughts

937

: 00:44:49

on the HR function itself,

938

: 00:44:50

because it's, as you said, the function,

939

: 00:44:53

change is nothing new,

940

: 00:44:55

but it continues on.

941

: 00:44:56

Something is a little bit distinct,

like you talked about this time around,

942

: 00:45:00

and we're all trying to

wrap our minds around it.

943

: 00:45:02

So thank you once again

for this conversation.

944

: 00:45:04

Lauren Tropeano: Oh, you're so welcome.

945

: 00:45:04

Thank you.

946

: 00:45:05

Thank you for having me.

947

: 00:45:07

Thomas Kunjappu: Absolutely.

948

: 00:45:07

And for everyone out

there following along,

949

: 00:45:09

this is another episode

of Future Proof HR.

950

: 00:45:12

Good luck as you future-proofed

your own organizations

951

: 00:45:14

and HR departments.

952

: 00:45:16

And I hope you found this conversation

953

: 00:45:18

as valuable as I did.

954

: 00:45:19

See you on the next one.

955

: 00:45:22

Thanks for joining us on this

episode of Future Proof HR.

956

: 00:45:25

If you like the discussion, make

sure you leave us a five star

957

: 00:45:28

review on the platform you're

listening to or watching us on.

958

: 00:45:31

Or share this with a friend or colleague

who may find value in the message.

959

: 00:45:34

See you next time as we keep our pulse on

how we can all thrive in the age on AI.

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