In this episode of the Future Proof HR podcast, Thomas Kunjappu sits down with Lorena Scott, Chief People Officer and Head of Customer Experience at Relay, to explore how AI can be used to accelerate people and CX roadmaps without losing the human moments that matter most.

Drawing on her dual mandate across People and Customer Experience, Lorena shares how Relay thinks about AI not as a replacement for people, but as a way to expand capacity, unlock time, and bring forward initiatives that would otherwise live years out on the roadmap. She explains how lessons from CX such as coaching, enablement, and quality assurance have directly informed people practices, and why unifying these functions has created a more consistent and human-centered experience across the business.

Lorena breaks down practical examples of AI in action, including AI-powered coaching to support managers and individual contributors, using AI to accelerate insights from people data, rethinking headcount planning across human and non-human capacity, and creating space for internal mobility through stretch projects. Throughout the conversation, she emphasizes the importance of showing impact through action, not promises, as the most effective way to build trust and reduce fear around AI adoption.

Topics Discussed:

1. Using AI to accelerate people and CX roadmaps
2. Unifying People and Customer Experience under one operating philosophy
3. AI coaching for managers and individual contributors
4. Expanding human impact by removing low-value work
5. Rethinking headcount planning with human and non-human capacity
6. Applying CX learnings to HR enablement and support
7. Internal mobility and stretch opportunities in a scaled organization
8. Building trust through action, not reassurance
9. Preparing people teams for an AI-enabled future

If you are an HR or People leader looking to use AI to scale impact, improve enablement, and move critical initiatives forward faster without sacrificing humanity, this episode offers a thoughtful, operator-level perspective on what future-proofing really looks like.

Additional Resources:

1. Cleary’s AI-powered HR Chatbot
2. Future Proof HR Community
3. Connect with Lorena Scott on LinkedIn

I do strongly believe that if we leverage AI in the right ways,

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we can accelerate the impact that as

members of a people team we can give.

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So it's like learn from

engineers, learn from anyone who

4

is an expert in building GPTs.

5

Understanding how it works.

6

I think there is power in becoming

an expert there to be more

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impactful on the people side.

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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

people leaders are reimagining work

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and leadership in the age of AI.

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I'm your host, Thomas

Kunjapu, CEO of Cleary.

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Today's guest is Lorena Scott, Chief

People Officer and Head of Customer

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Experience at Relay, a leader who's

redefined what it means to connect

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employees and customers alike.

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Lorena's background spans

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venture investing, founding an

e-commerce business and scaling

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people in CX teams at companies like

500px, Algolia, CaseWare and Ritual.

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At Relay, she's leading both people

and culture and customer experience

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at uniting two disciplines around one

philosophy, creating environments where

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people do the best work of their lives.

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Lorena, welcome to the show.

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Lorena: Thank you very much Thomas.

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Thomas: Right off the bat, I have

to ask you about this dual mandate.

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Tell me about this combo, these

two hats that you wear between

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people and customer experience.

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Lorena: I know for most people, it feels

like it's an awkward combination or

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unique, but it is very on brand for Relay

in that we've always prided ourselves in

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providing a very human centric experience.

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And that because it is so important

to us, it really meant that having a

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unified experience, really showing up

consistently in moments that matter.

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Whether it be our external customers,

our small business owners or our

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internal customers, our relays.

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We needed one leader to really ensure

that the values and the way we did

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that and executed against that was

consistent and unique and meaningful.

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And as I look at kind of what's

the equation for success in really

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delivering incredible experiences.

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It's like how you onboard, it's how

you support and it's how you enable.

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And we leverage maybe a different.

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pieces to that formula, whether

it's people or customer experience,

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but it is very Relay-esque and

that's very special for us.

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Thomas: I know you've had

experience on different sides of

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the table and investing, founding,

obviously on the people team.

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I'm curious, what draws you to

continue to be on the people side?

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Lorena: The honest answer is I stumbled

into people about 10 years ago.

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I had a business that I started

on the e-commerce side, which

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she mentioned in the intro.

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It was an epic failure.

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It did not scale as an org.

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So I was a founder that had to

basically shut down my business.

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But I knew that I didn't want to

go back into finance and investing.

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That's not where my heart was taking me.

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And so I was fortunate enough

to have befriended a former

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investor who turned into a CEO.

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He needed someone to help very

broadly across a startup named 500px.

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And so he said, hey, can you

help me run finance and customer

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support and operations and people?

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And candidly across all of those

disciplines, I really only knew how

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to run a model or knew that well

with confidence, but he took a bet

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on me and he said, go figure it out.

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think you'll care enough.

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And we've had enough failures that you

should have learned a thing or two.

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And I found myself very much

gravitating to the people work.

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And so the short answer is I

find it really interesting.

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It's never the same.

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It's a constant journey in terms of

learning about people, about what

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matters to them, about their living

programs and experiences that are, that

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show up with a lot of heart and care.

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And I find that really rewarding

more so than living in the

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financial model these days.

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Thomas: Got it.

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So then do you think that there are any,

I mean, there are lots of differences

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between being a Chief People Officer

and a founder, but is there anything

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in mindset or any, are there any

similarities that you carried through?

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Lorena: Yeah, there are probably,

I think there are a few.

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One is just resilience, right?

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Being a founder and I was a,

I didn't have a co-founder.

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I think in that context also requires

just a lot of rolling up your sleeves,

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doing the work, having an appreciation

for what it takes to do the work and a

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lot of creativity and problem solving.

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And today there is no shortage of

work to be done as we're scaling a

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company and my kind of role of leading

people and culture in that context.

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And so it's being ruthless

about prioritizing, knowing that

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resources aren't unlimited and not

applying the same playbook that

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other organizations have used.

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So that really feels differentiated

from an employee experience.

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And so there's a lot of creativity,

a lot of problem solving, and

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you're always on and working on it.

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I think, and I love that fuels me.

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It's not for everyone, but for me, I

take a lot of joy in doing the work

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and the amount of work, I know that

sounds like little crazy, but yeah.

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Thomas: There's no shortage of that,

of the amount of work, just on the

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people side, but also obviously

on the customer experience side.

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And I think in this moment, especially

when there is a proliferation of

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AI, I'm curious, are you seeing more

adoption or possibilities in one of your

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orgs versus the other, or just in general.

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Could you talk us through a little bit

about how you're seeing at this moment,

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AI is getting into or impacting the way

that you and your team is doing work?

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Lorena: I would say we are

leveraging or thinking about AI

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equally between the two teams.

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I mentioned earlier a little bit about

the equation for success being really

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how do you onboard successfully?

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How do you support and enable?

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And so both teams have really strong

onboarding practices and rituals,

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both do a lot around enablement,

whether it's CX enablement or we call

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talent enablement on the people team.

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And we're doing a lot of support and kind

of firefighting internally or externally.

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We're trying to find

opportunities where AI can drive

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efficiencies or speed up our opportunities

to do enablement, either at scale

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or refine or improve the enablement.

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And it is balanced.

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And sometimes I'll find myself something

that has worked really well in CX

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and thinking about whether or not we

could translate that to accelerating

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some of the work we're doing on

the people side and vice versa.

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And also inspiring the sides of how

we leverage AI besides of the teams.

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Thomas: Oh, that's really interesting.

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Do any examples like come to mind?

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Because most listeners are in

the people discipline itself.

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And of course you're inspired by just

what other folks you're seeing within

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your own discipline, but also your

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being exposed a little bit to what's

going on, not at your level in terms

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of just like in-depth ownership.

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Anything come to mind, especially

in terms of inspiration that

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people leaders can take from things

that are working on the CX side.

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And by the way, also counter examples

are great too, if there's anything that

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didn't work or it's actually different.

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Lorena: I had a prep conversation.

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We talked about AI coaching.

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We've actually been using AI

to coach and QA our CX agents.

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For most, maybe the back half

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And we've seen improvements in confidence

levels and CSAT scores, what we call

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acceleration of one touch resolution.

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So being able to answer a ticket or a

question from a customer in one setting

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versus kind of multiple interactions.

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And so we've, we learned from that to say,

how do we accelerate just enablement or

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coaching within our own team internally,

different tools, different partnerships

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potentially, but nonetheless, just saw

the impact in ultimately like the customer

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experience by way of a CSAT score.

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And so how do we do that more quickly

on, people side, whether it's general,

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like support questions that we get

with like inquiries, like how's my

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payroll or what's the next payroll

cycle or how do my benefits work to

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things like, Hey, I'm really struggling

in this moment and giving feedback.

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How do I do it better?

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How do I do it differently?

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Thomas: Let's talk about that second

element, because that could be not

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just for the HR team, but actually more

broadly for peer to peer feedback, or

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I think crucially manager feedback.

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The AI powered coaching sounds like

it started with helping customer

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support agents in doing their work.

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Have you thought about

that for managers as well?

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Lorena: Yeah.

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So right now we're exploring.

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So the thing about Relay is that we

do have a talent enablement practice

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that focuses on kind of three points.

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And the journey one is

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our onboarding, the other

is what we call growing.

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So growing in your career.

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And the third is leadership development

path and how we support developing

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leaders and accelerating leaders at relay.

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a big part, you know, a tool that

we have in our toolkit across

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those three areas is coaching.

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But for hiring coaches that kind

of fit in the relay context and

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also in our budget, because we are

a scale up, has been challenging.

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And so coaching has really been

limited up until recently to our

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people leaders, our managers.

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And we are working with a partner

right now on AI coaching for everyone.

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So that in people leaders who have not yet

had one-to-one coaching opportunities, but

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are struggling to structure a conversation

that is both candid and caring, right?

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They are first time managers,

they've never done this before.

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They want some, like a micro moment of

coaching that an AI coach can do that for

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them to an individual contributor who is

structuring how to present or communicate

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effectively the point that they want

to make because they see an opportunity

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that needs to be addressed, but they

haven't quite been able to crystallize

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the comment in a way that is being heard.

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There's many different use cases, but

we've loaded this to have our values,

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our roadmap, our priorities, our all of

the relay intel to really refine how it

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speaks and the type of feedback it gives.

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Thomas: So it is personalized

to the organization and further,

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you're building in capacity.

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So I love these examples of AI

unlocking just new surface area that

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just would never have happened before.

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And I think before when we're talking

mentioned you're less interested in

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AI replacing roles and just, okay, let

me have AI do this instead of a person

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and more about accelerating what you

can't do otherwise or what can't today.

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How do you think about that as

a lens for investment in just

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AI projects across the board?

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Lorena: Yeah, I know when you

and I talked earlier, I like, I

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believe in the power of people.

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Part of the, why I have

the two roles that I have.

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And, but I also work in a

resource constrained environment.

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And so we can't do everything.

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And one of the really wonderful

exercises that we did in September of

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this year was to dream a little bit.

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What would it take to make

Relay a generational company?

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And we want to be known for for both on

the people and customer experience side?

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And so there were all these wonderful

and vicious dreams that we put on the

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table and then given where we're at and

the pace that we're moving, I like, we

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won't be able to do that even next year.

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It's going to be like a 2027, 2028 dream.

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And then I thought, what if we leverage

technology to accelerate or bring forward

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those plans into the 2026 roadmap?

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And so that's been really powerful

in that we've now moved forward

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things that we wanted to do because

we can leverage AI or leverage

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other technology and do it sooner.

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Do it better.

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Be continuously learning.

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That to me is we wouldn't have

been able to have coaching

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for all until I think 2027.

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And that had to mean a lot of

other things went right for us.

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And now we're going to do

it by the end of this year.

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Thomas: Wow, that's like

a two year head start.

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To enable all of this, you're

having these internal discussions

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with teams who themselves and CX

and people time people teams, they

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also have this, like many knowledge

workers, this background fear, right?

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Around what's coming with AI.

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It's coming for my jobs.

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Have you faced that?

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Maybe you haven't faced that and

different teams are different, but, and

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how do you come back and kind of shift

from this kind of fear to excitement

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for bringing in your roadmap and

being able to do more things faster.

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Lorena: I honestly have not seen

the fear and, maybe folks haven't

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expressed it to me as transparently.

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I think in general to combat that it's

not what you say, it's what you do.

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And so if the hypothesis is, or if

we're leading with, it's going to

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accelerate investment in roadmaps or

in initiatives by 12 to 18 months or

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as much as 22 or 24 months, then we

just have to show that's happening.

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it's, we're going to remove some of the

tedious tasks that were on your plate

237

so that you can do more impactful work.

238

We have to demonstrate that.

239

And then on the CXI, for example, we want

to make you more confident in your work so

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you can show it better for our customers.

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We have to unlock that and

demonstrate that and show the

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data and how that's happening.

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And so long as you can prove

out what you're saying in action

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and that translates into the

business impact, I think that's

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where you build the credibility.

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Maybe folks are by nature a little,

should be a little nervous, but

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ultimately if you do what you say in

terms of what, how AI can be powerful

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in an org that speaks volumes.

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And I feel like that's being seen

today, at least in the Relay context.

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Thomas: It's really about showing, right?

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And that's what I'm hearing.

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That's your

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Lorena: Doing, showing it.

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Yeah.

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Thomas: So speaking of doing, I know

you're all types of internal innovations.

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One of the things that we're

talking about is this like listing

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this internal marketplace, right?

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Because let's talk a little bit about

like internal mobility, because we've

259

been talking about how AI projects have

been coming into the fore at Relay.

260

But on top of that, there's new skillsets

that will be, need to be developed and

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there's new potential like projects.

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Let's talk a little bit about how

you're enabling all of that, like

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creating these internal marketplaces.

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I think you call it right between

to pair talent or learning projects

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with or learning goals with potential

projects within the organization.

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Lorena: First of all, I really can't

take credit for this initiative.

267

This was the creative like brainchild

of a member of the people team.

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So hopefully she'll listen to this

and know that shout out to Jenna.

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One

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of the things that we're saying is if

AI unlocks more efficiency and therefore

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gives our team members more space to

do projects or special projects and say

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that's 20 % of their time, what is the

mechanism that we're going to build to

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create a platform for people to figure

out what those stretch opportunities or

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the special projects are as we scale?

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Because informally that has happened

at Relay for the last six years.

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People, somebody in marketing will be

like, I have this problem around this

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data that I'm trying to better understand.

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And somebody from the data team will

be like, I will help you with that.

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And it's a beautiful exchange.

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It's a great partnership.

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But as our teams have gotten

larger, as Relay has gotten

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bigger and more distributed,

that doesn't happen as naturally.

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And so what can we put formally in place?

284

And so this is the

marketplace idea that we have.

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It's not yet launched or built out

is how do we create a destination

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within Relay for folks to talk about

their skills, things they want to

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learn, places where they want to grow

in their career and match that with

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projects or skills needs on other teams.

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Because ultimately the way people

do progress at Relay is delivering

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on impact and taking on stretch

opportunities that allow for that impact.

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And so now we're just creating

something more formal to allow that.

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But the only way that would be possible

is that if we afforded people more

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time to take on those opportunities,

and that's where AI has been like,

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it's a partnership between like, we've

created more efficiency in the system,

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therefore there's incremental more time

to take on these stretch opportunities.

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How do we find and like, match

people to these opportunities?

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Thomas: So I think you're saying the

AI element of that is to take away

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some of the activities that you're

doing today to be able to have some

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open time to stretch into new areas.

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And on the other hand, I think

there's opportunities that will

301

be enabled by AI, which will be

the stretch opportunities as well.

302

And effectively in this endeavor

to create a two-sided marketplace,

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there's supply and demand.

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So we talked about a little bit of think

how AI is potentially for a lot of it.

305

Producing both the

supply and demand, right?

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For new skills, proliferating

throughout the organization,

307

but for on the demand side.

308

Managers or leaders or project leaders

who are potentially looking for talent.

309

Are there things that you're

doing systematically to encourage?

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Not necessarily the internal marketplace

itself, but just encourage either

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AI use or new project initiatives to

then call out the needs which would

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then feed into the extended path.

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Because the reason I ask this is often,

I think surprisingly, in high talent

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density environments, it's the supply

of opportunity that's considered that's

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more constraining than the actual,

the supply of opportunity versus the

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demand of people wanting to do stuff.

317

So how do you ensure that there's like

a system that's generating these stretch

318

opportunities consistently for people?

319

Lorena: Candidly, that has not

been a problem at Relay, right?

320

We have no shortage of

projects and opportunities.

321

What I do worry about is people being

burnt out because they're trying to do a

322

lot of things on the side of their desk

because they're curious and because they

323

want to show up for their team members.

324

I think what I wanted to do was make

sure that we created the space, right?

325

There was a way to relieve some of the

manual tasks from folks as an example

326

so that they could spend a portion

of their time picking up projects

327

without breaking and being able to

really sustain the ride for as long

328

as they want to be a part of Relay.

329

So we haven't necessarily yet and look,

we're a 225 going to 300 person company.

330

And so maybe that's a luxury of still

being small and are on the smaller side.

331

But today projects and initiatives

where folks could learn and

332

explore is not the constraint.

333

This has been a fantastic

conversation so far.

334

If you haven't already done so,

make sure to join our community.

335

We are building a network of the

most forward-thinking, HR and

336

people, operational professionals

who are defining the future.

337

I will personally be sharing

news and ideas around how we

338

can all thrive in the age of ai.

339

You can find it at go cleary.com/cleary

340

community.

341

Now back to the show.

342

Thomas: Maybe

343

I can ask a little bit different

and maybe it is a scaling thing.

344

really at scale is when it comes in.

345

It's everyone for whatever

work they're doing.

346

There's always more to do than there's

time for, but often what is missing is the

347

connection between that and the potential

for culturally for even a manager to

348

ask the question that like someone in a

completely different org would be able to

349

help or head count or the team that I have

is that's the resource again, my time.

350

And that's often what maybe that's

like to me, that's a supply of ideas

351

problem, but really it's a cultural

issue about making sure that there's

352

this, even the idea that an HR

generalist could help with a marketing

353

data analytics project or vice versa.

354

And because as you get a little bit

more siloed, I guess that's part of

355

what you're looking to do, right?

356

Make, create these connections.

357

Lorena: Yes.

358

And that's, that has happened

as I alluded informally.

359

And when we were in just one

office, it happened naturally.

360

We are now in, doing the count

one, two, three, three primary

361

offices were much larger.

362

And so that, hey, we run into

each other in our main office

363

in Toronto, doesn't happen.

364

And I also found that like the same

people who knew each other well were

365

each other to do these projects together.

366

When there's a lot of amazing folks,

some of them much newer to the relay

367

journey, who had the appetite, the skills,

and just didn't have the connections.

368

And building this marketplace means

that there's an equalizing of, if I

369

have the skill, I have the bandwidth,

and there's this opportunity presented,

370

I can raise my hand and do it and

learn and really drive impact.

371

Thomas: Yeah.

372

So the multi-location problem

starts to create it and then the

373

hierarchical organization at scale

starts to reinforce it and you're

374

already fighting against that early.

375

But then let's talk about,

okay, the constraint then.

376

besides the skillset, it's time.

377

There's lots of opportunities

to bring back time for the team,

378

specifically on the HR side.

379

I know you're doing some interesting

stuff also with CX agents as innovators

380

creating their own GPTs and stuff, but on

the HR side or on the people team side.

381

Speaker: what are the big

opportunities that you see that would.

382

Thomas: looking forward or even

to your point, maybe it's this

383

quarter, not two years from now.

384

What are the big opportunities that are

unlocked that can get people out of let's

385

say some of the proverbial muck, right?

386

The work muck.

387

Lorena: Yeah.

388

I think getting people out of

the proverbial, like, let me

389

pull your vacation balances.

390

Let me share more on the

benefits, which takes time.

391

And it's important to people is

like the easy, low hanging fruit.

392

What I'm also seeing now is

that we're able to create

393

dashboards at the company level.

394

And then at the team level that give

us a signal on this moment happened.

395

Here's where it could learn, turn into

a good career trajectory versus an exit.

396

We're basically downloading reports

and feeding it into ChatGPT and

397

helping us better understand the

signal and then translating that

398

back to managers and leaders.

399

We could do that and we have

been able to do that, but this

400

just accelerates time to deliver.

401

These dashboards to deliver the

insights and the opportunity to go

402

deeper because it's less about report

pulling and data amalgamation and

403

more around what does this mean?

404

How do I unpack this?

405

So I think the insights are better

and we're able to action more quickly

406

and then learn as a result faster.

407

Thomas: I love that.

408

there's, okay.

409

So guess you've mentioned like

two specific opportunities, one

410

around just, I guess the reactive

HR support work and then just.

411

I would say this is really

about analysis, right?

412

Cause I think you're talking about

particular analysis around employee

413

engagement data, but there's probably

different pockets of that type of work in

414

like your HR professionals world, right?

415

Compensation or one-off requests for

analysis for a particular organization

416

or VP, but that intermediate

step of data analysis to get to

417

insights can be made more efficient.

418

Lorena: And right now

we're resource constrained.

419

So we only have one person on the

people operations team as an example.

420

And the level of analysis and the

kind of depth of thinking would

421

normally be limited by that one human.

422

Thomas: So let's talk about yet another

process, which I think is interesting.

423

Headcount planning.

424

Yeah.

425

So you said your capacity model now

includes both humans and non-humans.

426

Tell me more.

427

Lorena: That is primarily on

the CX side today as we are

428

building out our 2026 plan.

429

For example, normally past models,

capacity models, like what we went

430

to finance to request for additional

headcount was based on the channels

431

that we supported our customers and like

the growth of those channels based on

432

ticket volume and kind of information

that we had in the current year.

433

We have totally changed our model to

think about what are the human actions

434

and what are the non-human touches that

will still deliver a great experience.

435

And so I have a headcount

needs for both human agents as

436

well as our non-human agents.

437

And then I'm able to, as our assumptions,

for example, on efficiency and quality

438

shift over the course of the year,

better understand what is the mix

439

between our human and our AI agents.

440

Thomas: Okay.

441

So I have to ask here because this

is the kind of language that is great

442

for like vendors who are trying to

like, or if you're trying to get

443

clicks in the media landscape to talk

about like workforce planning with

444

agents and robots replacing humans.

445

But here Lauren and operator working

with your finance team and you found

446

this to be like practically useful.

447

How is this from your perspective?

448

Any different than software,

you know, like you might ask for

449

head count and software budget to

work on stuff like in the past.

450

Versus now AI agents and human agents.

451

Does it feel a little bit different in

the conversation that you're putting

452

forward with finance than those times?

453

Lorena: Yes, it

454

does feel different in that I think

with software requests in terms of

455

budget for tooling in the past, it's

been more about the cost savings and

456

what leverage does it give us from a

financial perspective for the work?

457

So reduced cost per interaction or

for using this tool is one example

458

on the customer experience side.

459

Rightfully or wrongfully, I know about

60 to 70 % of our CSAT score is just

460

driven by timeliness of response.

461

Not even the quality of the response

is if we can get to a customer in less

462

than 10 minutes that they will be way

more engaged as a result, be higher C

463

Score, higher NPS and higher revenue

for Relay because they'll stay with us.

464

And so now I'm saying an AI agent

will be on 24/7 and will give

465

responses within 60 seconds.

466

That is more about revenue and

customer experience than it is about

467

efficiency of like, How do I reduce

my cost to serve this customer?

468

And so I think that's how it has

changed, at least how we talk about.

469

What are the outcomes for the

business as a result of using

470

an AI agent versus a human agent

that can only work so many hours,

471

sometimes has to be retaught things.

472

And so that's how

473

it's shifted for us.

474

Thomas: That's interesting.

475

That reminds me of what the earlier

conversation we were having around

476

coaching and where it's increasing

the capacity to create value, right?

477

So

478

let's follow the thought

experiment on both sides.

479

On the coaching side, you could have

coaches at an hourly rate giving

480

on-demand 24 seven coverage for

everyone in the entire organization.

481

And that's one way to get at it,

but that's just like the cost like

482

doesn't add up and same thing here.

483

You could have as the organization

scales up, you could scale up your

484

human workforce so that you have

within 10 minute touch point 24

485

seven for every single interaction,

but that also doesn't scale right?

486

So in this case it's actually this

other investment that you're doing

487

versus headcount to actually get

to those outcomes directly, right?

488

So it's contributing to the outcome

versus and actually increasing the

489

capacity with software you might be or

traditional software SaaS, you might be

490

asking, given the head count we have,

how can we make them more productive?

491

And it's, think, did I

summarize that nuance?

492

I think it's very interesting.

493

Lorena: Yes.

494

And the only thing I would add is that

on the human level, whether you're

495

talking about CX or on the people side,

sometimes we require a lot of reeducation

496

or we'll fall into bad practices.

497

And so one of the benefits of the

CX AI agent is that it's constantly

498

learning and it actually doesn't,

it doesn't forget the things that

499

we have trained or taught it on.

500

And so there is, we have to see this

play out, but there is at least a

501

thinking that we have that ultimately,

the quality of the conversation could

502

be even better depending on the issue

because they're constantly learning and

503

getting better versus maybe forgetting

things as humans naturally do.

504

Thomas: Yeah.

505

This is so I have to circle back

all the way to the initial comment.

506

So then, do AI agents then ultimately

replace human jobs in this world?

507

As we keep shifting towards

them, adding more value.

508

Like expanding the scope of

value that you can add for an

509

organization and potentially in

certain vectors, doing it better.

510

Lorena: I think it depends

on the job to be done.

511

When I look at the types of

tickets or types of issues that

512

come up for our customers, they're

not all solvable by an AI agent.

513

And then when we're talking about

people's money payroll and issues,

514

there are moments that really

matter where a human is required.

515

And we just want to be able to divert

the resources that we have today to be

516

there in those moments versus being jammed

up with things that are less impactful

517

to a business, less impactful to the

relationship that we have with a customer.

518

And that's the same can be

true on the people side.

519

It's not that I don't want

to lean our people team.

520

I just want them to be there in

the moments that really matter

521

and do so in a more impactful way.

522

Thomas: That is really well put.

523

Let's talk a little bit about

the future then, Lorena.

524

So let's say you're

looking two years ahead.

525

What does a, I don't know, a people

plus CX organization look like

526

in an AI enabled organization?

527

You're already well down this path.

528

Maybe, yeah, what does it like team

look like, especially what skillsets

529

are like really like helpful?

530

Do new titles emerge and or yeah, how

does this, the day to day look like?

531

Lorena: Well, I'm not a very

good fortune teller or editor.

532

I'm laughing because two years ago,

two and half years ago when I joined

533

Relay, you would have told me how

much time I would spend in ChatGPT.

534

I would have told you were

crazy, but that's my reality now.

535

So I've embraced this world that we're

living in and find it really interesting.

536

To answer your question, I think it has

already changed how we think about hiring.

537

And from an org design perspective,

I think it is creating roles

538

where having this AI expertise.

539

is going to be more and more important.

540

And so if I even look at like my 2026

headcount plan for both CX and people.

541

I don't even know what our role that just

focused on are we using the right tools?

542

Are we embedding the practices?

543

Are we measuring if people are

using the Zenvesco pilot or the AI

544

coaching agent, just making sure

that sort of all that is happening.

545

So I think it is creating new roles where

that is a very much a core focus and

546

beyond that, I'm not going to give you a

good answer Thomas, because I don't know.

547

Thomas: But it's fair to call out

what was happening two years ago,

548

and could I have predicted where

I am at this moment back then?

549

It feels like we are

accelerating ever further.

550

Maybe that caution is warranted.

551

But that said, people are developing

new skills and need to stay relevant.

552

And we're all about future-proofing folks.

553

So if you have to give advice, and maybe

there's a simplest way to someone who is

554

just coming out of college or just new

into the workplace and is interested in

555

getting into the people function, what

thoughts would you have for them besides

556

that you don't have a crystal ball?

557

Lorena: I would say lead.

558

It does feel a little counter

to what we do to be so focused

559

on AI when we're committed to

delivering these incredible human

560

experiences and all about the people.

561

But I do strongly believe that if

we leverage AI in the right ways,

562

we can accelerate the impact that as

members of a people team, we can give.

563

like Learn from engineers, learn from

anyone who is an expert in building GPTs.

564

Understanding how it works.

565

I think there is power in becoming

an expert there to be more

566

impactful on the people side.

567

And I see that today on my team.

568

I'm probably the least sophisticated,

the least knowledgeable.

569

I'm always impressed by the GPT

that our people team are building

570

from hiring to the retention side.

571

so I'm like, don't be afraid of

it and ask a lot of questions.

572

Experiment on the side.

573

That's what I do is build and then tweak.

574

And I used it for board work

with fast board session.

575

And it's a lot of fun.

576

Yeah.

577

Thomas: Love it.

578

So thank you so much for

this conversation, Larena.

579

And looking ahead a little bit as well,

if you're, as we close out here, let me

580

just ask you, are there any particular

projects, ideas that as you look forward

581

that you're particularly passionate about

or excited about seeing how it's going

582

to turn out over the next year or so?

583

Lorena: I'm excited, even though I didn't

have good answers to what the future org

584

design and the roles that can come out of

this new world that we're operating in.

585

I'm super pumped for the AI

coaching that we talked about.

586

And then looking at our vision and

our, these projects that we hoped

587

to bring two years from now and

how we can bring them fast forward.

588

So there's, I think to having the space

and the time to dream and then say, how

589

do we leverage technology AI to bring

those forward on both the CX and people.

590

It's not very specific, but that's like

the body work I'm committed to doing

591

over the next two months is dreaming

and then figuring out how to harness

592

how far we've come in the last couple

of years to also bring all of those

593

projects forward in a scalable way.

594

I like to dream and I'm

looking forward to doing that.

595

Thomas: love that.

596

Thank you for dreaming and sharing

some of those dreams with us

597

here on the, this conversation.

598

And I particularly like this idea of

basically expanding scope, accelerating

599

and scaling up things that you otherwise

even maybe in your initial dream

600

would think of your initial formulas

of how you might get to this outcome.

601

think it's way out there, but

actually, there's opportunities

602

that you can grab much faster.

603

And thank you for going through some of

these and going back and forth between

604

the CX and HR examples, because I do feel

like there's a lot of adoption in ⁓ many

605

other functions, broadly speaking, besides

the HR and people function where there's

606

so much inspiration we can take in.

607

also it's important to understand about,

because if we're creating leverage in

608

the workplace, it's through the people.

609

And so we need to really understand

how each of these different

610

functions are shifting as well.

611

So thank you again for

the conversation, Lorena.

612

And for everyone else who's out there

and looking to future-proof your own

613

orgs and your own HR and people teams.

614

I hope you took some.

615

interesting nuggets out of this one.

616

Best of luck and we'll be seeing you.

617

Thanks for joining us on this

episode of Future Proof HR.

618

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