In this episode of the Future Proof HR podcast, Thomas Kunjappu sits down with Amy Goldfinger, Chief People Officer at Slice, to talk about what HR can and cannot hand over to AI.

Drawing from her experience across Walmart, Heidrick & Struggles, and Slice, Amy shares how the people function changes across scale, why startup HR requires sharper prioritization and speed, and why the fundamentals of talent, operational rigor, and leadership development remain constant.

They discuss practical uses of AI in learning and development, board preparation, performance management, and manager coaching. Amy explains why AI can accelerate the work, but cannot replace the judgment, creativity, empathy, and influence that HR leaders bring into the room.

From the risk of weakening early-career development to the opportunity to help managers have better conversations, this episode offers a grounded look at how HR can use AI as a capacity-builder without hollowing out the human capabilities that make people teams effective.

Topics Discussed:

• How HR priorities change between a global enterprise and a late-stage startup
• Why speed, prioritization, and “just enough structure” matter in high-growth environments
• How AI helped Slice build a leadership academy and where human judgment still had to take over
• Why AI output can feel repetitive, mechanical, or incomplete without human creativity
• How early-career roles may change as AI removes some of the traditional training ground
• Why struggle, discomfort, and hands-on work still matter for developing analytical judgment
• How HR leaders can decide when AI is advantageous and when a human should lead
• What board meeting preparation reveals about the value of wrestling with hard decisions
• How AI can support performance management, review writing, and manager coaching
• Why AI should strengthen manager capability instead of replacing difficult conversations
• How people teams can use AI to do more with less without hollowing out HR
• Why future-proof HR may become even more human-centric in an AI-driven workplace

Additional Resources

• Cleary’s AI-powered HR Chatbot
• Future Proof HR Community
• Connect with Amy Goldfinger on LinkedIn

We're not seeding the judgment, but we shouldn't

2

think AI has the judgment.

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I, so that's one aspect.

4

And then the judgment that it takes

to make decisions is born of learning

5

which is painful and uncomfortable

and you wrestle with things.

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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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Hello and welcome to Future-Proof

HR, where we explore how forward

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thinking leaders in HR..,

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are 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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Today's guest is Amy Goldfinger,

the Chief People Officer at Slice.

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Amy is a senior HR leader who has worked

closely with C-Suites and boards across

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public and private companies to unlock

competitive advantage through people

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strategy.

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Before Slice, Amy ran a global HR

function within Walmart, led the

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global CHRO practice at Heidrick and

Struggles, and earlier in her career,

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Thomas Kunjappu: worked in

a product management and

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management consulting capacity.

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Across those roles, she's developed

a pragmatic view of AI, where it

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accelerates work, where it falls short,

and why judgment, creativity, and human

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development matter more than ever.

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Welcome to the podcast, Amy.

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Amy Goldfinger: Thanks, Thomas.

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Appreciate it.

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Glad to be here.

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Thomas Kunjappu: So I'm excited to

talk to you about so many things

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because you've worked in massively

different types of scale and in

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different types of roles in relation

to what the people function can do.

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Maybe we can just start there,

just talk about scale a bit.

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So if you were to compare HR and

an organization like Walmart versus

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a much smaller team but at a very

exciting startup called Slice.

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How does that change priorities

and even the leverage that you

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have in the people function?

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Amy Goldfinger: I love this question

because I've loved the experience of

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going from a large, really complex,

mature organization to late stage

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private, and it was very intentional

as I was seeking my next opportunity.

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But working in large companies is all

about leverage from systems and process

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and scale, and you get the advantages

of getting the operational model

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because when you get it right, thousands

of people can execute consistently.

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You spend a lot more time aligning,

reducing variance actually, because those

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small improvements compound at scale.

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Thomas Kunjappu: Right.

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Amy Goldfinger: I used to say every turn

of the dial, every degree mattered because

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the ripple effects for, at that time, 2.3

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million people really mattered.

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versus my experience now at a late

stage startup where leverage is

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just so much more concentrated.

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We are a handful of decisions, a

handful of hires, any trade off we

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make materially changes our outcomes.

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And so we have to be really

sharp on our priorities.

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We have to be tight with our

resources and speed matters more

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than things being really elegant.

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my focus a lot now at Slice is on

ensuring that I have just enough

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structure, but to not get in the

way of slowing down the business.

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Thomas Kunjappu: Right.

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Amy Goldfinger: I, have to be

careful not to over-engineer.

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I made that mistake very early.

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I was a month in and brought forward a

proposal about something we were working

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on, and it was like, oh, wait a second.

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This is actually just too complex

relative to where we are as a company.

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That would've worked in my previous life.

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So I quickly needed to pivot

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and mentally readjust.

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To, Make sure that I was working in the

context of a high growth, private company.

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So the one, there are some consistent,

there are some themes that carry

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over between large and small.

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And I would say quality of talent is you

can't compromise in either environment.

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And what we look for is very different.

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But, and context really matters.

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Experience the contextual factors of

people's experience really matters

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it doesn't take away from the

quality of talent that we were in any

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context that we've been looking for.

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Thomas Kunjappu: Would you say the what

is demanded of the people function?

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Is there it's, dramatically different?

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Or would you say it's just,

it's really, it's the same.

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Yes.

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It's obviously, it's the same profession.

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People who have been trained in this

field who are then being asked to

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apply that in different contexts,

or does it feel like there's

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one extreme example is obviously

there are specializations within HR.

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that a global HR function like at

Walmart would have, and even like in

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an early stage startup, but for sure

where they have two HR people, like

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100% will, would not have, right?

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That's specialization by just

subfunction, like within HR.

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But then if you were to sum

it up, would you say that.

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Overall, there's even differences in

what, is demanded of the function, right?

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Across the employee lifecycle, talent

acquisition or just how, you're coming

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across to the board or leadership,

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Amy Goldfinger: No.

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Thomas Kunjappu: Across the board.

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Amy Goldfinger: In my experience

so far, I would say there

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aren't material differences.

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Functionally speaking.

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I think the way we go

about things is different.

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The level of focus.

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So different functions take on different

levels of urgency in small versus large.

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Right now, for example, I'm spending a

lot of time on the fundamental operational

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rigor, like the fundamentals operationally

of our organization because as we.

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increasingly complex.

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We need to be prepared for that.

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We need to make sure our

processes are in place.

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And the reality is that as a, maturing

organization, a lot of those need to

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be refreshed as we've scaled and grown.

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So it's, more in my mind, the emphasis

of where we're spending our time and

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prioritization across the function

than to say that any one piece of the

116

function isn't important because they,

remain equally important in my mind.

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Irrespective of the size

of the organization.

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Thomas Kunjappu: It's about the emphasis.

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I'd like to talk about

something in, in preparing.

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I'd love to hear about.

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Any stories, right?

122

Like that of operators have around

their experiences with AI and.

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you shared an interesting one about when

your head of talent was on mat leave.

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Could you share a little

bit more about that?

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Amy Goldfinger: Yeah, I joined

and very quickly after our head

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of talent and learning went off

on leave for an extended period of

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time and I thought, oh my goodness.

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We have a lot to build very quickly and.

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Just on the topic of

AI, I use AI every day.

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There isn't really a day that goes

by that I can think of where I'm

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not tapping into the power of AI.

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Our learning is, and development is

one example of where we've, leaned

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in, particular, for example, in very

short order, we built a, and designed

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a six month leadership program for

our mid and top, mid-level leaders.

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So still very much forming

their leadership capabilities.

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And it was a leadership academy program.

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The first that we had done as a company,

and we delivered a first session.

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We've now delivered many

modules of the program.

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We've had everyone go through assessments,

they've been going through coaching.

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We have just a number of

aspects of this program.

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And in designing the second and final

part of a, the six month program, I

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said, you know what, let's put all

of this into and AI and see what it

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says about how we should design our

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final time together in person.

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And this is a global program.

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We're bringing people in from all over

the world to we want, we need this

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to be a very effective use of time.

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And I, thought it got me exactly

60 to 70% of the way there.

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I would say 60%.

150

It was wildly helpful.

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It didn't do the work for

us, but it certainly pointed

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it gave us a point of view.

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I think it accelerated the

development of the content.

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And then we needed to overlay our

knowledge and to make it ours really.

155

But it was very valuable.

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Thomas Kunjappu: That's interesting

because it's also the tail end because

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you've already know your what you've

already delivered some modules.

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You have content already, and this

is like a part two or part three.

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which is even more context, right?

160

To use the LLM language.

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You're giving sharper in info

input to get sharper output.

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And yet you say, okay, what we got to

was about 60% of the way there, right?

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Because that would be one of the

theoretically home run use cases,

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which is, it's writing, right?

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So you, need to maybe and take a

final look and edit a little bit.

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But it's writing with a lot of

detailed context given in beforehand.

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And I think L&D tends to be one

of these experimental zones for

168

like HR leaders for that reason.

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And yet you said it's

60%, not 80, 90, like 99%.

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What's the.

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What do you, think, what do

you think this that Delta is?

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And let's just start there.

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What were the actions that you

and your team were doing to

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get it to a hundred percent?

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Yeah.

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Amy Goldfinger: You know what,

what was put out felt AI.

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So we all know what it feels like to

read something that AI produced that

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hasn't been otherwise interfered with.

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It's a little repetitive.

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A little.

181

In some ways a little boring

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And feels very familiar.

183

There's a rhythm to AI produce content.

184

There's like I said, repetitive.

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So we've, it's required

actually a lot of work.

186

But that work has been really fun because

we say, okay, do we want this exercise?

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How would we frame it differently?

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If this is feels repetitive, what's

it actually going to feel as a human

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being, as a participant in the room,

and how's the day going to flow

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Thomas Kunjappu: Right.

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Amy Goldfinger: From a multimedia

perspective, how do we want the experience

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to feel on day one versus day two?

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Do we want more videos?

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Do we wanna stand up?

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Do, how do we think about our breaks?

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How do we there's so much more

texture to it that you didn't,

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that we didn't get from the AI.

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And like I said, we did

find it very repetitive.

199

So for example, we said, oh, this feels

like we just did this that morning.

200

And then we're going to do a very

similar thing in the afternoon and.

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Thomas Kunjappu: Right.

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Amy Goldfinger: That kind of judgment

and creativity to overlay it is essential

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because otherwise it would feel robotic.

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It would feel like a machine led

experience, and we want it to feel.

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Like a slice specific.

206

We've defined our objectives.

207

We've been very clear about the behaviors

we're going to drive and so forth, the AI

208

got some of that, but it felt mechanical,

so we needed to start with the meat on

209

the bones, and it saved us a lot of time.

210

And then we needed to make

it real and make it ours.

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Thomas Kunjappu: Yeah.

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That judgment piece, right?

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I hear that often.

214

There's, that's missing a little bit

or put it, or I would inverse it.

215

It's the, that's a key piece of what we

as humans need to bring constantly and

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always on top of AI whenever we're working

on on different different projects.

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I guess is that, would you say that

as like a, is a concern for you

218

or it's more just like a, is it a

concern that we're seeding too much

219

judgment to AIs in practice across

across the economy, across, across,

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Amy Goldfinger: Yeah.

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Yeah.

222

I would phrase it differently.

223

We're not seeding the judgment, but we

shouldn't think AI has the judgment.

224

I, so that's one aspect.

225

And then the judgment that it takes

to make decisions is born of learning

226

which is painful and uncomfortable

and you wrestle with things.

227

And I think about this in this call, like

the second chapter of my career this sort

228

of stage of my career where it's, can call

upon my experiences require learning me,

229

that developed my analytical thinking.

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In order to inform my decisions, it

helps me make much faster decisions

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as a result of the wrestling that I

did earlier on in my career, whether

232

it was as a consultant, whether as

operator, in any of those capacities.

233

So, I often feel like AI

has repeatable recognizable

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output and lacks originality..

235

And so where

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Thomas Kunjappu: Yeah.

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Amy Goldfinger: judgment come in?

238

So I do have a question about how

AI will how the AI generation will

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build its analytical judgment?

240

Maybe prompt development is

that, maybe that's to be part

241

of what develops people skills.

242

But this is a question

that I've had on my mind.

243

since AI has really taken off.

244

And the other piece is I sit in a number

of forums of other chief people officers.

245

We talk a lot about disrupting

those early career positions.

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Thomas Kunjappu: Yeah.

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Amy Goldfinger: Those

roles prepare people.

248

Very much for more senior level, more

complex decision making the ability.

249

So maybe they don't need to be up

till 2:00 AM wrestling with a model,

250

but if you haven't wrestled with

a model, it's a question of what

251

other ways are we ensuring that next

generation has these skills and that

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the current generation doesn't atrophy.

253

I'm less worried about that.

254

But the next generation and I think

about all the mistakes I've made,

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all the mistakes that I've made,

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Thomas Kunjappu: Yeah.

257

Amy Goldfinger: that haven't been right,

also helped me, helped inform my ability

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my judgment, my analysis of a situation.

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I think it's also about the use cases.

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There's, a lot to that, but

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Thomas Kunjappu: Yeah.

262

Amy Goldfinger: such a concern.

263

It's just, it's very early and we have

to see how that, how do we make sure

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that we're preparing those upcoming

individuals with those analytical skills.

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Thomas Kunjappu: Yeah it's interesting

you say the words like grunt work and

266

associated with wrestling with the work.

267

Really you need a way for people are

getting into their careers or and that's

268

really what school is also, right?

269

It's just to

270

Amy Goldfinger: Yes.

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Thomas Kunjappu: practice getting

those neurons firing and making those

272

connections in some kind of format.

273

The counter argument to this is

that when we had the internet and

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information search was at our fingertips.

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We had a whole generation that

was now not learning how to use.

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Oh man.

277

The name fails me Dewey

Decimal system and how to find.

278

how to find information, in a library

279

And so you're using Wikipedia and

Googling things and figuring it out.

280

And this is yet another evolution of that.

281

And

282

people will figure it out.

283

And another even more nuanced pushback

I think is, to this idea is that

284

one way to look at it's

fraternities, right?

285

Or sororities.

286

It's I went through this terrible

rush my freshman year and so now

287

everyone else needs to do, and now

look at me and I'm a great senior

288

and now I need the next class.

289

We're gonna make it just as hard for

them and do all these crazy things, but

290

which eventually lead to subcultures.

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Amy Goldfinger: For the record,

I don't subscribe to that model.

292

Thomas Kunjappu: The initial, the early

work, because that is gonna be changing

293

and even in preparation in college

and high school, how would you push

294

back on, or does this feel distinct?

295

The risk here for early

jobs and preparations?

296

Amy Goldfinger: I don't know yet.

297

If I only had that crystal ball, I

think there's something about grit that

298

is important and you and I have met

people along the way in life who have

299

faced, everyone's faced challenges.

300

And it does, it makes you.

301

can make you stronger.

302

I really believe in learning.

303

I say this all the time, which is

if it's not painful, you're probably

304

not learning that much, right?

305

Thomas Kunjappu: Yeah.

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Amy Goldfinger: if it

doesn't feel uncomfortable,

307

then how much are you really growing?

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Thomas Kunjappu: yeah,

309

Amy Goldfinger: like I said,

in life, and of course we're

310

talking in a professional context,

311

Thomas Kunjappu: yeah.

312

Amy Goldfinger: The struggle

does teach critical thinking.

313

My question is, what is the AI what is the

generation struggle that builds that grit

314

and that builds the critical thinking.

315

And AI can't substitute for

engagement or alignment and influence.

316

Can't substitute for it.

317

It maybe can give you a prompt to

say, here's how I would structure

318

that conversation, but the actual

ability to go into a room and take

319

the output and drive consensus.

320

a whole other set of skills

that's really important.

321

So maybe you could skip the

early analysis and get there.

322

And that's where we focus our

attention, because that's the

323

humanity that overlays it.

324

That's the, I actually

have to collaborate across

325

Thomas Kunjappu: Sure.

326

Amy Goldfinger: actually have to drive.

327

Influence across an alignment.

328

So maybe I think we just don't know

yet, but it's, I'm constantly thinking

329

about this as we engage, increasingly

engage with AI and think about it as

330

part of our everyday work sitting next

to us which I absolutely anticipate it

331

will, and it is already in some context.

332

So

333

Thomas Kunjappu: Yeah.

334

Amy Goldfinger: just, it'll

be interesting to see.

335

And to your point, the large accounting

firms, the banks, the consulting firms

336

they have to wrestle with some of that.

337

So we can and learn around it.

338

Really.

339

Thomas Kunjappu: Yeah, maybe

you got me thinking if that's

340

let's just use that 60% marker.

341

So any kind of grunt work

activity that you used to do,

342

like you get a 60% head start on.

343

When you get going, when you're

like that in that early career

344

mode, doing that, do that work.

345

So it just takes many more of those

operations to go from 60 to a hundred

346

percent that you need to wrestle with.

347

That's where you're firing

the neurons and, learning.

348

But it takes more of those, right?

349

Because more of those projects

to get to the same level of

350

learning and wrestling with the work,

but it's also different learning, right?

351

You're just starting with.

352

The internet or starting with

the AI and then going from there.

353

But I appreciate the humility in

the, I don't know, response there.

354

But

355

Amy Goldfinger: It's true.

356

Thomas Kunjappu: it's an important,

it's an important conversation.

357

I think about it within within the

HR function itself and some of the

358

applications that my company is deploying

it is partnering with the junior HR

359

operations folks, but also you get, their

roles are gonna be a little bit different

360

when you're engaging with tools like ours.

361

And that's happening with every

function and all across the economy.

362

But

363

Amy Goldfinger: Yeah.

364

On this,

365

Thomas Kunjappu: go ahead.

366

Amy Goldfinger: think this is

important because we have the option

367

to decide what use cases are best,

highest for AI versus human being.

368

Thomas Kunjappu: Yeah.

369

Amy Goldfinger: And we should

always be asking ourselves, is

370

this the best, use of AI or is this

really a problem to solve with the.

371

Creativity, curiosity, judge, empathy,

humanity that, an actual person brings.

372

So I we I don't, think it's a

peanut butter spread approach on AI.

373

I don't think most people are

thinking about that way, but I'll just

374

emphasize that's very much my thought,

which is, this isn't, not every.

375

Nail needs a we don't need to go around

to every single instance and say, this

376

is this how can we disrupt this with AI?

377

It's no.

378

Let's think about is AI the first

question is is AI advantageous here?

379

How is it an

380

advantage?

381

And where do we need the

human to come into play?

382

Thomas Kunjappu: This has been

a fantastic conversation so far.

383

If you haven't already done so,

make sure to join our community.

384

We are building a network of the

most forward-thinking, HR and

385

people, operational professionals

who are defining the future.

386

I will personally be sharing

news and ideas around how we

387

can all thrive in the age of AI.

388

You can find it at go cleary.com/cleary

389

community.

390

Now back to the show.

391

Actually, speaking of that, you

had a an example we talked about

392

and there's both sides of that.

393

For that example board meeting prep.

394

Something that you know many

folks in you need to do that it

395

needs to happen in some form.

396

What did you discover about where

AI could or could not be used there?

397

Amy Goldfinger: We had an upcoming

board meeting and as anyone

398

board facing knows, it's just a

tremendous amount of preparation

399

and it was no different for us.

400

Many iterations, many scenarios.

401

We're at scenario 15, scenario 16 of in

a specific instance, and it was painful.

402

Do we all just agree, are we aligned?

403

Does this make sense?

404

Is this the way we're gonna go?

405

If we tweak this dimension, what

does that mean for the output?

406

And I would say the board meeting was

very successful as a result of having

407

gone through all those scenarios.

408

Now, my question is, I wouldn't say we

used AI in particular for that example.

409

So it goes back to is this, an

instance in which it would help, but.

410

How prepared would we be if we

had used AI or said differently?

411

How would we prepare differently

if AI was used as part of that

412

preparation as, the primary tool or

of the getting us off the ground?

413

So those are the things that we

should be asking ourselves and

414

then changing our way of operating.

415

But in that instance, it was so

valuable we all came away saying.

416

It was, hard.

417

It was like a struggle to get through

the preparation, but we had a very Si

418

we came outta that board meeting feeling

like we had, we were just so prepared,

419

That any holes that were poked, we all

felt very comfortable we could answer

420

Thomas Kunjappu: Yeah.

421

And theoretically you could have a prompt

that says, Hey, AI create 17 scenarios.

422

And, but the work was, and the synthesis.

423

Wasn't the group coming together

debating, thinking through

424

arguing from all these dimensions?

425

It goes back to what

you said about the the.

426

Model work till 2:00 AM at post college.

427

It's it's the

428

what's that called?

429

The reward is in the work right.

430

In, some ways.

431

Amy Goldfinger: Yeah, but

432

I, it's not the only way.

433

I think you're also saying

it's not the only way.

434

But what is the new way and I, and

435

Thomas Kunjappu: yeah.

436

Amy Goldfinger: remains

to be seen, I think

437

Thomas Kunjappu: Yeah.

438

I would say, okay, you're not

necessarily anti AI, but I feel like

439

there's very, you're very clear about

limits that you want for it, right?

440

Amy Goldfinger: Definitely not anti AI.

441

Thomas Kunjappu: Maybe it's, I dunno,

maybe it's pro-human, but not that

442

there's like a like a, fight there.

443

Exactly.

444

But how do you think about holding these,

both, both these truths together at once?

445

Amy Goldfinger: Yeah.

446

As I said, I use it every day.

447

I'm always thinking about how

Slice can to use AI for those

448

opportunities across the company.

449

How do we unlock value for our customers?

450

Where can AI play a role?

451

How do we improve our

employee experience with AI?

452

We just had this conversation yesterday.

453

We've got a.

454

A great tool we're testing

around performance management.

455

That could be really exciting and

just lift our managers meaningfully.

456

So it's a tool and we

can't undermine, right?

457

The empathy, the curiosity, all

the things we've been talking

458

about that come into play.

459

And it goes back to that use cases.

460

A computational genius

can only get used so far.

461

You still need.

462

The person needs to show up and deliver

that message to someone that's difficult.

463

It's not enough to have the words, and so

464

Thomas Kunjappu: Actually I'm, curious,

465

Amy Goldfinger: yeah.

466

Thomas Kunjappu: ask about the

perform 'cause performance management?

467

That's that is a, place where,

468

Amy Goldfinger: Yeah.

469

Thomas Kunjappu: Really you need to

have feedback delivered gracefully and

470

with intention words chosen carefully.

471

And yet you're seeing there's some value.

472

What, do you think about the divide there?

473

What are the, use cases or parts

of that AI and a tool can help with

474

versus the ones that you're, I dunno,

you want double down on let's say,

475

management training and make sure

that people are delivering it well.

476

Amy Goldfinger: So the conversation

in full between me and my

477

team was, we really want to.

478

Disrupt our own sort of

performance management cycle.

479

Condense the time it takes.

480

And we're talking about one of the

things it takes the most time in that

481

process is for people to write reviews.

482

I'm testing out that we might employ

that would help people write reviews.

483

Pretty straightforward.

484

It's interesting.

485

When AI first came out, everyone

said, especially as someone who grew

486

up in the talent acquisition world.

487

Oh, that's where it's going to disrupt.

488

And I think,

489

Thomas Kunjappu: Yeah.

490

Amy Goldfinger: has a place there, but

actually what's more exciting to me

491

is helping managers be better managers

492

With a tool that might give you

help you synthesize your performance

493

data, sit with you as a co-pilot.

494

In, your conversations with your team

members and then be able to help you

495

think about what the, summation of that

is at the after, for a performance season.

496

In any case, I think those are

some of the examples where it

497

can get you really far, then.

498

Like I, really am enjoying thinking

about how it can help with performance

499

management, because we all are

wrestling with how best to do that.

500

Ratings, no ratings.

501

But the reality is it's the quality

of the conversation that matters.

502

You can give someone a rating, and I

always coming up when I had ratings

503

or I'd get a rating or I'd get my

compensation what does this mean?

504

That's what you wanna know.

505

What does it mean?

506

What does it mean for what I did?

507

Thank you.

508

And what does it mean for

what I need to develop?

509

does it mean for me continuing

to advance and grow?

510

That's the richness of it.

511

Thomas Kunjappu: It is.

512

Amy Goldfinger: whether or not

you have ratings, who cares?

513

Great.

514

Use a rating.

515

It helps distribute create a

distribution that's all valuable.

516

I'm just saying that's where AI can

be interesting if we use it to further

517

the richness of the conversation.

518

Thomas Kunjappu: This debate or

this, challenge across organizations,

519

it's always everyone complains about

performance management at their company

520

because now all of a sudden I have to look

up and do all this stuff and I have to

521

re really think about what happened and.

522

Managers have to write pages for each

employee, and it takes so much time.

523

It's always like a big complaint.

524

And the ratings is another

piece on top of it, right?

525

But now your voice is in my head, Amy.

526

So isn't the magic in the work isn't,

the act of the complaint or the, outcome

527

is the complaint, but the output that

led to that complaint is, dozens and

528

hundreds of managers and employees doing

peer reviews and feedback and having to

529

think about it and thinking about was

this good or was it, should I say this?

530

Should I not say that?

531

Why is that?

532

Does that map to a value answering

hundreds of these questions?

533

Which, yes, it's annoying 'cause it

takes time, but that's why it's valuable.

534

And the doing that then produces

something that is, produces complaints,

535

but hopefully something useful as well.

536

Amy Goldfinger: Yeah.

537

Thomas Kunjappu: if.

538

That part which is part of the

work is now outsourced to AI.

539

Is there a risk now that's, like a muscle

that you start to start to lose or Yeah.

540

How do you set especially at

scale, I would think, right?

541

You have, you — thousands of managers,

how do you like make sure at, the,

542

I mean at the most basic level,

a manager doesn't just click send

543

A, on an AI generated like slop or

even if it's right or nine times

544

outta 10 people just send it along.

545

There's a bit of that risk, right?

546

Amy Goldfinger: Yeah.

547

What I'm seeing that I like is.

548

If you put that in the context

of an ongoing conversation,

549

so the AI starts to hear, has

pattern recognition, for example.

550

By the way, AIs can also give the

manager feedback on how they're managing.

551

So one that I'm looking at, it says,

you handle that meeting well and when

552

you finish, discussing this topic.

553

You weren't concrete enough

in your expectations of what

554

that person should deliver.

555

Wow.

556

Can you imagine how powerful

that, let me go back.

557

Great.

558

Thomas Kunjappu: Yeah.

559

Amy Goldfinger: me go back to that

team member and say, I wanna be really

560

clear on what my expectations are for

X and maybe the AI would even spit out.

561

I think it, I'm still learning

here's how you might go back and,

562

you know, clarify.

563

So it's.

564

Rather than it being the be all, end

all, it becomes more of that copilot,

565

which I like that and you're right.

566

Does it strengthen the manager

or does it weaken the manager?

567

But I think if my goal is strengthen the,

quality of those conversations, then maybe

568

it, maybe we get there as a result of it.

569

Like maybe it actually is a teacher

for when you're a new manager,

570

you don't have the words unless.

571

Thomas Kunjappu: Yeah.

572

Amy Goldfinger: As long, if

you've had great managers, you

573

probably have more of the words.

574

But if and if you're a high

performer, you don't know.

575

It's very hard to manage low

performers when you've been a

576

high performer your whole career.

577

Like I remember someone talking to someone

about, I thought, How would they know

578

how to have that one-on-one conversation

with someone who's performing,

579

Unless simply because they've never

been in the room when that happened.

580

this is where I think it can be

581

Thomas Kunjappu: So like pattern

matching and background awareness and

582

pointing out blind spots to the manager.

583

Clearly adds value.

584

It's almost like having a coach like that

for the manager that you can't really

585

in practice have for every manager.

586

So that's like unlocking

new value clearly.

587

So let me ask about one other area, which

I think is bedeviling, a lot of HR teams.

588

I would say since post COVID and since

we've been at the peak before in, after

589

say, 21' 22' with the end of ZIRP a common

thing you keep hearing and I feel like

590

to some degree it's accelerated with AI

591

every HR team is under

pressure to do more with less.

592

Amy Goldfinger: Yep.

593

Thomas Kunjappu: Got it.

594

Deliver more results and,

595

Amy Goldfinger: Yep.

596

Thomas Kunjappu: here's

like less budget somehow.

597

How so how do you balance that in

the age of AI and do that without

598

hollowing out the capability and

what the team is looking to drive.

599

Amy Goldfinger: Yeah, I

think in the short term

600

AI's adding a lot of capacity simply put

601

On a daily basis.

602

I, like I said, I feel it personally.

603

I see it and we're, gonna be

testing out something at Slice.

604

I won't go into the details, but just

to say it'd be really interesting to

605

see how it, not hollows out, but just

really lifts as we grow especially in

606

a high growth environment where it's

it's not like we do or don't need.

607

We need the people we

have and we're growing.

608

And so like

609

Thomas Kunjappu: In more capacity.

610

Yeah.

611

Amy Goldfinger: Exactly like

huge opport amazing opportunity.

612

so yeah, I think it's like how is the

capability built alongside or even to

613

enhance people's skills and capabilities.

614

A lot of what we've discussed

and, that's where my head is,

615

in HR, thisis another example,

616

like in performance management

617

We're doing more, we're doing

more, we're doing better.

618

It's higher quality.

619

Thomas Kunjappu: Right.

620

Amy Goldfinger: it doesn't hollow out.

621

It just, actually helps us

all strengthen our muscles.

622

So I think it's the other side of

AI, which I'm, very optimistic about.

623

Thomas Kunjappu: So then if you're

zooming out and looking at the industry

624

more broadly, what do you think that

625

a future proof HR

department looks like then?

626

Amy Goldfinger: Yeah look,

the people function, our

627

role, it is very interesting.

628

There are so many conversations about AI

and, i'm not anti but I'm pro at all the

629

other thingsr things the other things

that the people function need to continue

630

to do to take into account demographic

shifts, where the business is going.

631

The full picture of the full

system and AI merely a tool I'm pro

632

progress and taking, a systems view.

633

I think it's really exciting to

think about the people function being

634

at the tip, the tippy point of the

spear on a lot of these changes.

635

Thomas Kunjappu: Oh, how do you mean?

636

Amy Goldfinger: Our aging workforce

are how do we manage intergenerational,

637

cultural dynamics how do we put the

business in the context of macro

638

and more local economic shifts.

639

I, just think those are the

aspects that I think a lot about.

640

Thomas Kunjappu: Yeah.

641

Amy Goldfinger: and how does that

influence slice how we attract the

642

right people, develop our people and

just essentially grow the business.

643

And then the other piece is always

644

it's, about humanity.

645

It's human-centric.

646

Like how do we continue to, like

our leadership program starts with

647

leading yourself and how do we help

people continue to lead themselves to

648

cultivate empathy and compassion, to

learn how to work with other people too.

649

Take care of themselves for

sustained leadership over time.

650

One of the conversations we're really

having with our mid-level managers

651

is if you wanna be the leader that

we're asking you to be like, you

652

need to take care of yourself.

653

What are you doing around that?

654

How, can we be intentional?

655

No tool or bot is gonna do that for you,

you have to invest the capacity, and

656

I think the people function can help.

657

Raise the level of humanity in this

context and the empathy and the

658

making sure internal equity

is a foundational principle.

659

Like these are things that

crucial for the people function.

660

And you could still putting that

in a very commercial context in

661

a, in the age of technology, but.

662

You're pulling back on those,

I think would be a disservice.

663

And I, think the HR function is, the

lever to pull and I, think that's what's

664

happening and to me that's very exciting.

665

Thomas Kunjappu: So it's almost

like the people function is

666

even more people-centric,

667

Amy Goldfinger: Yeah.

668

Thomas Kunjappu: in the,

as we go into, the future.

669

So are there just while I have you here

before we close out, do you think there

670

are any risks we're underestimating around

671

the, people function in the in the AI

driven world or to, flip that what gives

672

you optimism about how there's a big

opportunity for, the people function.

673

Amy Goldfinger: Yeah, I think

I'm so impressed by the.

674

Caliber of chief people officers

out there in these roles.

675

The quality of those conversations,

I'm challenged by 'em.

676

Um, that gives me a lot of optimism.

677

I think even from my days at Heidrick

talking to CEOs about what they

678

were looking for in their next chief

people officer, that conversation

679

in the 12 years I was at Heidrick

shifted dramatically in that period.

680

And now I think even since then,

it's come even farther, meaning.

681

Which is to say that CEOs board members

are more and more committed to ensuring

682

that their people capabilities are at

the forefront of their organization.

683

So

684

Thomas Kunjappu: Yeah.

685

Amy Goldfinger: that gives me a tremendous

amount of optimism for the function.

686

And yeah, I just think it's like

the value that human beings add.

687

And how do they use the tools

at their disposal to be the best

688

human beings that they can be?

689

And I'm optimistic we're, that's

the direction we're going in.

690

Thomas Kunjappu: That's great.

691

So it's like we're standing on

all the great work over the last

692

like decade because the reputation

right, is has been shifting.

693

Amy Goldfinger: Oh, I think it's there.

694

We keep talking about it.

695

I think we're there.

696

Move forward, it's time to just claim it.

697

And kudos to all the people before me.

698

Exactly.

699

I'm standing on some very great shoulders

of people who have really influenced that.

700

And I, think it's really exciting.

701

It's why I love being a CPO and just

tremendous influence over an organization

702

and beyond, so that's exciting.

703

Thomas Kunjappu: Absolutely.

704

So that's a great place as any

to, and we'll leave it there.

705

Thank you for the conversation, Amy.

706

So we, covered so much ground and one just

fundamentally it's useful to think about

707

scale and how distinct or not distinct

it could be for, the people function.

708

And I, felt like my takeaway was that

there's actually more similarities than.

709

Then they're not.

710

And which actually only speaks

to more of a coalescing around a

711

function with expertise that can be

expressed with different emphasis

712

in, in, in different directions.

713

We went through a lot of the nuance of

around the use of AI and arguably any new

714

technology shift and what that means for

the collective minds of humanity at that

715

moment and how it's gonna be trained.

716

And there's a, a unique problem

here I keep hearing about, which

717

is about what will be those first

training jobs for the next generation.

718

And the more I hear about that,

the more I am concerned about it.

719

I feel like it goes up funnel as well,

probably, and towards education and

720

the five paragraph essay breaking

apart because you can just build

721

that as a high school student.

722

But that's a real sort of like problem.

723

But then we extended that into all

these very practical use cases, right?

724

You have a, I think, talked about

a path to thread that needle right

725

around being optimistic about the

people side of everything going forward

726

while being very practical about what

can, how we can find leverage, right?

727

Whether it's an L&D performance

management, any kind of operational work

728

that, that we're doing in the function.

729

So thank you for the conversation and

everyone who's listening, I hope you

730

took something away as your yeah, as your

future proofing your own functions, HR

731

functions, and your own organizations.

732

Thought.

733

Hope you found this as valuable as I

did, and I'll see you on the next one.

734

Bye now.

735

Thanks for joining us on this

episode of Future Proof HR.

736

If you like the discussion, make

sure you leave us a five star

737

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738

Or share this with a friend or colleague

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739

See you next time as we keep our pulse on

how we can all thrive in the age of AI.