In this episode of the Future Proof HR podcast, Thomas Kunjappu, CEO of Cleary, sits down with Amy Wang, Head of HR and Payroll Shared Services at Mercedes-Benz North America, to discuss how HR is changing as AI, shared services, and human leadership increasingly overlap.

With experience across IT, procurement, operations, and HR, Amy brings a cross-functional perspective on what it takes to build systems that are both scalable and people-centered. She explains why the future of HR depends on connecting people, processes, and technology in more intentional ways.

Together, they explore where AI can support HR workflows, where human judgment still matters most, and why better design and governance are essential for making these tools useful in practice. They also discuss how shared services is evolving beyond transactional work into a more strategic function focused on capability, data fluency, and cross-functional value.

Amy also shares why curiosity, continuous learning, and adaptability will be critical for HR leaders who want to stay relevant as work continues to change.

Topics Discussed:

1. How Amy’s transition from IT leadership to HR shaped her approach to organizational change
2. Why the convergence of HR, IT, and shared services is accelerating
3. Where AI can support HR workflows and where human judgment must remain central
4. The “human-AI-human” model for responsible AI use in HR processes
5. Why poorly designed AI systems create frustration and how better governance can help
6. How shared services is evolving from transactional processing to capability building
7. The role of curiosity and continuous learning in staying relevant as AI reshapes work
8. Why organizations must create safe environments for experimentation and innovation
9. How HR can act as a translator between strategy, systems, and the employee experience
10. Future opportunities for AI in areas like employee relations analysis and pattern detection

If you’re an HR leader thinking about how AI will affect HR operations, shared services, and the skills required to lead in the future, this episode offers practical insights and a thoughtful perspective on what the next shape of HR could look like.

Additional Resources:

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

It's taken me from managing change to really designing change.

2

So like now, HR really can

operate as like a translator.

3

It helps connect people processing

technologies so that strategies

4

that are being revealed to employees

really become real to them.

5

It's become something

that's makes more sense.

6

Thomas Kunjappu: They keep

telling us that it's all over.

7

For HR, the age of AI is upon

us, and that means HR should

8

be prepared to be decimated.

9

We reject that message.

10

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

11

Instead, it'll be defined by those

ready to experiment, adopt, and adapt.

12

Future Proof HR invites these builders to

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

13

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

14

We are committed to arming HR

with the AI insights to not

15

just survive, but to tHRive.

16

Thomas: Hello and welcome to the Future

Proof HR podcast where we explore how

17

forward thinking leaders are preparing for

disruption and redefining what it means to

18

live and lead people in a changing world.

19

Today's guest is Amy Wang, head

of HR and Payrolls shared services

20

with Mercedes-Benz North America

with roots spanning IT leadership,

21

procurement, healthcare, higher

education, and enterprise HR.

22

Amy blends data technology and

human insight to build stable

23

systems that enable growth.

24

She serves as well on the advisory

board for Cornerstone University's

25

strategic AI program and contributes

to SSNs HR Shared Services blog series.

26

So a lot of hyphens here.

27

I'm so excited to bring Amy onto the show.

28

Welcome to the podcast.

29

Amy: Thank you, Thomas.

30

I'm happy to be here.

31

Thomas: So there's so many things

that we could talk about, but

32

I'd love to get started on.

33

Talking about your CIO to HR

kind of bridge experience, so

34

you don't see that very often.

35

People working in IT, procurement

operations, and then also like in HR.

36

So tell me how that happened.

37

Amy: I started off in, it just, it

was the thing to do when I started

38

it and it naturally progressed

into all the different areas of

39

it from being a programmer to

working in the network data center.

40

And then finally project management.

41

And when I found project management,

I found that was really what really is

42

the connection and the bridge between

all the different areas that I had

43

been in, whether it's IT operations,

procurement, and now HR, because there's

44

the people element that you really have

to focus on when you're in connecting.

45

Those has really been something

that I've truly enjoyed.

46

And finally being able to use.

47

My degree in HR.

48

It's been something that has been

really exciting for me and especially

49

how I think industry has evolved.

50

It's really allowed me to take all

those different aspects of my career and

51

really apply it together in using it now.

52

Thomas: So you're saying how

the industry has evolved.

53

How has it evolved and do you see

combinations and intersections

54

between these functions more now

than when you first got started?

55

Amy: Oh, absolutely.

56

In one of my former roles, I feel

like being in IT, it really taught

57

me about things like governance

and scalability and data integrity.

58

And then now being in HR, I feel

like I have a lot more mindset into

59

like empathy and communications.

60

And when those come together, I feel like

with how technology's changing so much.

61

It's taken me from managing

change to really designing change.

62

So like now, HR really can

operate as like a translator.

63

It helps connect people processing

technologies so that strategies

64

that are being revealed to employees

really become real to them.

65

It's become something

that's makes more sense.

66

Thomas: I've heard there's some

companies experimenting with this

67

stuff, like having the CIO and

the CHRO's office merge together.

68

Does that make sense to you or is that

like a trend for some reason you can

69

see more or less of in the future?

70

Amy: I think it makes perfect sense.

71

I actually cited an article I read

and Moderna is actually doing that.

72

They're merging both IT

and HR into one leader.

73

And I think it makes

a lot of sense, right?

74

Because there's so much in technology

that really touches the end user, right?

75

And so being able to connect, agAIn,

people process the technology together

76

for strategy, I think it makes tremendous

sense to help accelerate organizations.

77

Thomas: Let's talk a little bit

about AI and how it's come in

78

different ways as you have seen it.

79

And maybe we can talk a little bit about

the different ways you're attacking it.

80

I imagine leveraging AI in your

work, maybe in your personal life.

81

You're also involved in teaching

as well as in creating content

82

and blogging about the topic.

83

So just tell me overall, like your

relationship with AI and how it's

84

evolved over the last couple years.

85

Amy: On a personal level, I think

I am experimenting more than

86

probably more from my actual role.

87

But in having a lot of conversations with

industry in volunteering with different

88

organizations, I'm seeing it more and I

feel this is where it's super exciting.

89

But I feel like also we just have to make

sure that we understand what is it that's

90

specific for AI and what is it that there

should still be a human element to it.

91

And that's always my primary concern,

is ensuring that we're blending the

92

human element in everything we do.

93

Thomas: I hear that a lot, but I would

love to get more concrete about that.

94

What does that even mean?

95

Why do you need a human element?

96

And in what

97

Amy: For example, when it comes to

professional like environments, right?

98

There's things that you

don't wanna delegate to AI.

99

I feel like there's still a discernment

that should be left for humans.

100

For example, like when you're doing

audits or exceptions or anything that's

101

involving like human context or ethics, I

think those are important things that you

102

would leave specifically for humans versus

what you would go in the direction of AI.

103

If you're doing audits, you don't want

to completely turn that over to a system.

104

When we're talking about

audit, we're doing actually

105

the human side first, right?

106

Versus doing something that's specific to

107

instead of using AI.

108

So I feel like there's opportunities

where the human can enter the

109

information and understand the

process, but then using AI to assist

110

in like a second tier verifier, right?

111

So maybe flag anomalies, maybe looking

at patterns or inconsistencies before

112

things have to escalate, right?

113

So that way I think that there's

the human-centric piece of it

114

before you take it to the system.

115

Thomas: Okay.

116

And then to be very specific, what

kind of audit are you imagine?

117

Or can we talk about a

specific audit like process?

118

Amy: Maybe for example, in some

organizations I would say like payroll.

119

There's a lot of pieces where an

employee maybe is badging in making

120

changes, but then you want audit.

121

And then you want your payroll person

to do whatever they're supposed to do.

122

But then maybe the system to audit

because for example, maybe tax regulations

123

change, maybe pay codes have changed,

maybe other things are changing and

124

you just wanna make sure that from an

audit perspective there's compliance.

125

And that would be what I would use it for.

126

Thomas: Okay.

127

So in this case you're talking

about like specifically for payroll?

128

And like a and non-exempt employee,

when you're talk clocking in and out

129

with time cards, you wanna make sure

that you are looking systematically

130

at the process to ensure that

131

the inputs are accurate.

132

Amy: And

133

Thomas: so how and how is that being done?

134

Like without AI, is that just

not being done enough or is it...

135

I

136

Amy: think it's done by two people.

137

So it's, you have

multiple people doing it.

138

So if one person's doing it, you

have a second person who will verify

139

with a second pair of eyes, right?

140

Yeah.

141

And so I actually, here's an example.

142

I actually had a conversation with

an industry colleague and they were

143

talking about how AI flagged what

they thought was payroll fraud.

144

The data was correct, but like the

numbers didn't line up and so the human

145

reviewer noticed it after actually.

146

So they just use the AI,

the human reviewer noticed

147

it and said, wait a second.

148

I know that person returned

actually from a medical leave.

149

And so that context changes the story

because the system saw a mismatch.

150

But then if you have a person involved,

there's more design where you need

151

to keep the human in the loop, right?

152

So I think it's like you have a

human who does one part, you'll

153

have AI do another part, and then

there's another part for the human.

154

And there's handoffs that

need to be part of it.

155

So I think it's more like having AI

work as a partner versus a replacement.

156

Thomas: So in this specific

example though, you're saying

157

did AI add value or not?

158

What do you think?

159

Amy: I think in that particular example.

160

If everything worked to

normal, AI would add value.

161

But this is where it's like

almost a sandwich, right?

162

You have the human piece, you

have the AI piece, and then

163

you have the human piece again.

164

And I think that's part of the evolution

and maybe as people's processes are

165

designed differently, how technology's

used differently, it'll eventually

166

evolve where you don't need to have that.

167

But I think in this example that I

talked about, it really has been human

168

AI and then human and other examples

where you may not need a separate

169

human verification again, but as things

170

are being inputted to create

the validations that you're

171

trying to set up for AI.

172

I feel like there's still another

piece of right now that people

173

still have to verify, right?

174

So making sure that if someone's

entering their first piece of work and

175

then AI is doing the validation or the

compliance, I think there should be spot

176

checks or if things come up, I think

there still needs to be validation.

177

Thomas: With a human expert, right?

178

Yes.

179

On top.

180

On top of it.

181

Amy: Yeah.

182

And maybe that's a human putting

in the information to kind.

183

The context, right?

184

Or the prompts.

185

Maybe that's who's doing the verification?

186

Thomas: Yeah.

187

Workflow where you have, without

AI, you have just two people

188

checking something, right?

189

Someone's inputting data, maybe

an employee in this case, and then

190

you have one person looking it over

like a manager, and then you have HR

191

looking it over, and typically you

have decreasing levels of fidelity

192

and increasing surface area that each

193

stakeholder then needs to like handle.

194

So what happens naturally is that

the manager looks at things at some.

195

There's a spot check of every 10

records or every month you just do it.

196

And then HR is checking every a hundred

or every quarter or something like that.

197

And I guess if I think about your

sandwich metaphor, it's like you

198

could have an AI layer in there for

e either one of those checks, right?

199

Where either for the manager, in

this case, you're helping them point

200

their attention, like their mind

or their eyes or their time towards

201

particular entries and or HR as well.

202

But I think the risk you

rightfully point out is that

203

like the inputs or the context

could be missing and in this

204

case, there was no fraud, but

arguably no harm, no foul because

205

it was something that was flagged

to HR and a human judgment was

206

used to say this is not fraud.

207

But the AI just didn't have

the context, but it's still

208

arguably a little bit helpful.

209

But on the other hand, you might

miss things if you don't have

210

that human verification step.

211

But then overall though, I wonder, is

this actually even helping in practice?

212

Are you seeing that like

in these audit processes?

213

It just, yeah, just randomly you get

like some flags, but there's so much

214

shift and change that actually you're

not getting enough value from having this

215

thing in the middle in the first place.

216

And maybe folks who have hair unlike

me want to pull it out because they're

217

just like, wait, this thing is useless.

218

Or just like getting in the way.

219

I know sometimes there's

frustration, right?

220

Sometimes.

221

With AI tools, what do

you think about that?

222

Is it making enough of an advancement

in some of these use cases or?

223

Does it actually end up

creating frustration?

224

Amy: I think there's a lot of

frustration created, right?

225

But I think the AI is as

good as the people who are

226

building the context, right?

227

So it's going to be as

smart as how you design it.

228

So if you're buying tools and

just throwing 'em in place, right?

229

And assuming it's going to close

the gap, it's not going to.

230

It's really gonna be how well you

design the process, how well you

231

put in all the context and all the

different flow that it could be.

232

So I think in their case, now that

they know that maternity leave could be

233

something that gets flagged, how will they

now maybe restructure that system to have

234

it as maybe a different validation point?

235

So maybe those are things

that need to happen.

236

So I think it's

237

something that's gonna be more of

a continuous improvement situation.

238

Versus a one and done.

239

You can't just code it or like

in traditional systems, you may

240

be able to do some customizations

in your code or do maybe some

241

configurations and you walk away.

242

But I think this is more where we talk

about trAIning the AI to understand

243

and recognize the different types

of situations that can come in.

244

And that's only gonna be

as good as the humans.

245

Who are involved in programming

it or not in traditional sense,

246

but putting in the different.

247

Either prompts or the different

questions in there so that

248

it's getting better guidance.

249

Thomas: Guardrails

250

Amy: Yeah.

251

All that will need to be done.

252

And I think all needs to be done

a little bit differently than how

253

things were done traditionally.

254

And I think that's the big learning curve.

255

And it really depends on how

engaged your workforce is too.

256

Because I think some of these

systems could be better designed,

257

but then I think there's also

fear for people that maybe then.

258

There's not a place for them.

259

And I don't know the full context and

how that particular example was when

260

I was talking to a friend of mine,

but those are all I think things

261

that we need to consider as we're

rapidly deploying new technology.

262

There's so many different factors in

which can affect the success of that.

263

Thomas: Absolutely.

264

So let's get to that, like fear or just

like the mindset thing in one second.

265

I'd love to come back to that.

266

It's a huge point.

267

But even before that, you're talking about

just all the edge cases and programming.

268

It's almost, if the tools

doesn't work, it's your fault.

269

You have to work harder on it.

270

That's like what every vendor

including myself would say.

271

But who ultimately is

responsible for this.

272

Specifically in the HR realm.

273

There's a lot of just people

going Through their day-to-day.

274

Do you have time to get into this whole

world of prompting and guidance and

275

guardrails and seeing this an edge case?

276

And so I'm gonna try to like

work on it directly myself.

277

Or is it just the vendor capabilities

are gonna increase or are we gonna

278

see a whole, I dunno, crop of

consultants cropping up who are

279

gonna be specializing in this stuff.

280

Is there a specialized skillset

here or is it's gonna have to be a

281

part of what everyone needs to be

upskilled towards to be future proof?

282

Amy: I think both.

283

I think there is going to be a certain

amount of upskilling that needs to happen.

284

I think that people will need to evolve.

285

And I think in general, like

workforce has to be evolve.

286

Anytime there's new

technology that and new waves.

287

I think that will require

the workforce to evolve.

288

And I think those who are the most curious

at first will have the most insurance of

289

job security because they really want to

learn and adapt and apply this knowledge

290

and then bring other people along.

291

And I think that's where the humans will

have longevity in how to partner with AI.

292

Thomas: So you're already getting

at the some of the answer, I think.

293

To that second concept, which is

about like roles changing within

294

HR and like what you're foreseeing

and sometimes that's met with

295

fear or the fear of the unknown.

296

I guess a two part question.

297

What's the temperature out there?

298

What do people from your gauge.

299

Like folks in your network.

300

How do people feel about...

301

is there fear or is people

sensing opportunity?

302

What are your thoughts on how an HR

professional can stay future proof?

303

Amy: I think it's both.

304

I think there's definitely fear, right?

305

Because things are happening

so fast and people are not

306

always comfortable with change.

307

But I think that the best way is

for organizations to create a safe

308

place for employees to feel that

they can be part of the change.

309

They create good governance so

that people aren't just not rapidly

310

buying technology and throwing it in.

311

Because I think if there's

good governance, will actually

312

help accelerate innovation.

313

Because it's better than buying

something, making mistakes, cleaning

314

it up and starting over again.

315

But if you actually create the

environment for people to be

316

part of and to also create.

317

Provide the right guardrails

and the right infrastructure

318

for people to be successful in.

319

I think you'll see a lot

more people adapt faster.

320

And I also feel, this goes back

to working with your employees and

321

understanding like what other skills

they have beyond their job titles.

322

It's important to understand

323

your employee base and

understand their skills, their

324

capabilities, and their interests.

325

And have those regular conversations,

not just once a year at the

326

performance review, but ongoing.

327

And I think understanding your employee

base, their interests and skills

328

and what they wanna develop in will

actually help align with some of the

329

changes we're seeing in industry and

will bring organizations along faster.

330

Speaker 4: This has been a

fantastic conversation so far.

331

If you haven't already done so,

make sure to join our community.

332

We are building a network of the

most forward-thinking, HR and

333

people, operational professionals

who are defining the future.

334

I will personally be sharing

news and ideas around how we

335

can all tHRive in the age of AI.

336

You can find it at go cleary.com/cleary

337

community.

338

Now back to the show.

339

Thomas: So that's to me at least

an exciting kind of future.

340

And that's full of

opportunities for everyone.

341

But the practically, there's

a very human emotion, right?

342

To fight when you have the unknown

that you're looking up against.

343

So maybe speaking of the unknown, let's

talk a little bit about HR shared services

344

and maybe even shared services in general.

345

You've had a lot of experience

in this kind of world.

346

What do you think good looks like in

HR and like payroll shared services as

347

we are routing out 2025 and into 2026?

348

Amy: So I think that good shared

services used to mean specifically more

349

accurate on time and very transactional.

350

Because lot of traditional shared

services are where you bring

351

in things that you could do

repeatedly on over and over, right?

352

But I think over time, I think

that automation will take away

353

a lot of repetitive tasks so

that teams can actually focus

354

on what employees would value.

355

Clarity, consistency, care.

356

So what I'm seeing is like a shift

from transactions to more capabilities.

357

So shared services shouldn't

just be processing, right?

358

It should be where talent learns how

to think more, cross-functionally

359

manage systems, build data fluency.

360

Maybe it's probably the best

training ground, honestly to develop

361

future leaders, future roles.

362

Because right now when you go into

a shared services, the traditional

363

ones anyways, you're really learning

the basic parts of the organization.

364

You're able to see across the

organization and maybe use that as a

365

training ground to see where you can

accelerate those employees into other

366

aspects of the company and other roles.

367

And I think that's really where shared

services could really add value.

368

Thomas: So you don't see that shared

services, like In terms of jobs

369

just becoming a leaner function

overall because of automation and AI?

370

Amy: I think it will be leaner in

some se extent where things that were

371

truly the transactions, those types

of tasks will I think eventually, if

372

not already be replaced by AI, right?

373

I think you're going to see more

is where it's actually focused on

374

providing creative the value, right?

375

So what are things that you can bring

together more cross-functionally,

376

how do you actually integrate

the systems and maybe use those

377

capabilities to structure more broadly?

378

So for organizations that use the

shared services model where they're

379

having multiple companies or entities or

departments or teams being centralized,

380

that's where you're gonna see value.

381

Is the people that understand

how to centralize things.

382

And then they can continually

involve those things that are

383

needed for the people side.

384

So I think it is a different

version of what we originally

385

have noted it to be, right?

386

It's more focused on what

are the capabilities that

387

share services can provide.

388

And maybe take away some

of the more task level.

389

But take a look at what the data

pieces are and maybe use that to

390

build some of the human interactions.

391

Because once the technology can

clear things away, what other

392

human-centered pieces are still left?

393

Thomas: Interesting.

394

As you're talking about, this brings my

mind back to like where we started, about

395

a little bit about the overlaps between IT

and HR, but also I'm thinking about just

396

processes in process management general.

397

Anything back office,

including the CFO's office.

398

When you put it that way, it feels like

there's a lot of convergence, right?

399

And when you're just talking

about like collaboration or a

400

cross-functional processes, and think

about how data flows so that you can

401

just get the organization running.

402

When you put it that way, it feels like

403

all those functions, at least

at the shared service level,

404

should be merging even more.

405

Amy: Yeah.

406

It feels really natural.

407

And so having worked in IT for so

many years, but as an IT leader, a CIO

408

for a former organization, I worked

a lot with the human aspect, right?

409

Building my teams, cross training people

and making sure that from a IT shared

410

services perspective, delivering value.

411

Applying that now as a leader in HR, I

also have HR systems and taking that IT

412

mindset and operations and those pieces.

413

I think if they work really hand in hand.

414

And especially with so much AI now.

415

AI is not your traditional IT,

you're not really programming, right?

416

So it's a different way

of looking at technology.

417

But I think the concepts of working and

supporting the broader organization,

418

whatever the business is having these

skills combined makes a huge difference

419

and I think it makes a lot of sense.

420

I feel like it's taking in the past

you have the left hand and right

421

hand not talking to each other.

422

Now they're working in partnership and

I think that's really kinda exciting.

423

Thomas: Yeah, it is.

424

How should we think about reskilling the

the workforce, not just in HR and IT?

425

But just overall everyone right?

426

To re-skill the workforce.

427

To be able to be ready to

428

blend AI technology data along with the

human element, which I think some part of

429

that probably applies for probably broadly

every type of knowledge worker out there.

430

But from an HR perspective, if

we want to upskill, reskill and

431

ensure that people are future

proof, how can we help enable that?

432

Amy: I think there's a couple ways, right?

433

The first way is the individual really

has to take ownership of that, and I

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think Through the organization that they

work for really hoping to have continuous

435

conversations with their leadership.

436

What their goals are, maybe

the skills, learning paths.

437

And I think that's important

also from a leader perspective,

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understanding what their workforce,

their team is trying to do.

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Because as AI's evolving what

work will be, you really want

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your workforce ready to go.

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And you don't wanna wait

until something gets purchased

442

and say, oh, what do I have?

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What do I need to do?

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You wanna continuously understand

the people that are on your teams

445

and your organization so that you

can place them in the right roles and

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not just have 'em apply, but really

understand what else is coming.

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And that way, if you have these

conversations, people feel like have

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thing important.

449

I feel like people really

need to also take advantage of

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what's out there on their own.

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Really research and find opportunities

to build their own skillset right?

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And there's a lot of companies

that may have, for example, like

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a tuition assistance program.

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I would highly encourage using that.

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For example, I work with Cornerstone

University, for example, in

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their strategic AI program.

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But Cornerstone is only one of many

organizations that the Z School

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actually has partnership with.

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There's 15 different schools, and

what they do is they're partnering

460

with these different schools.

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It's online and you can take

different certifications.

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And I would highly recommend

getting certified to just

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really do dig in and learn.

464

For example, there's new ones coming

up that they have Through Loyola

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New Orleans School, Through Rockford

University and they're teaching

466

generative AI for value creation.

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And they're also teaching

other certifications.

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Like AI agents for change or how to

become irreplaceable in the age of AI

469

or even AI literacy and proficiency.

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All of those things are available to you.

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And if you don't have tuition

assistance Through your company,

472

there's so much you can learn

just Through LinkedIn or YouTube.

473

But I feel like you have to be

the CEO of your own career, right?

474

And so you have to take charge and trying

to figure out how do I stay relevant?

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And really, I feel that curiosity is

really your own career insurance, right?

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So the more curious you are about what's

happening, you don't have to work about

477

worry about being outpaced placed or out,

either replaced by AI or outpaced by AI.

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Just learn to work with it, and I

think that's really what's important.

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If you take time on your own to still

learn and to grow and ask questions, I

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think it'll make a world of difference.

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Thomas: So a lot of advice there and

a lot of like capability, like a lot

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of options out there like for folks.

483

I don't know if are you working

with in the coursework that

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you're doing and helping teach.

485

Is it new grads or college folks or just

mid-career folks or like looking to get

486

a gain AI literacy while they're working,

but maybe it doesn't quite matter.

487

But tell me a little bit from an education

standpoint, what are you focused on

488

to help close this readiness gap?

489

Amy: So personally, they

focus on two things, right?

490

Through the programs that the Z School has

to offer through Cornerstone University.

491

It's primarily professionals who

are looking to get certified in

492

strategy and how to apply new

knowledge to their existing roles.

493

So that's one piece.

494

But they also have other programs and

depending on what level you are in terms

495

of literacy of AI or career level or

maybe something you wanna do and progress.

496

I think there's so many

different options you can take.

497

And so I think that's a great option.

498

I think the other option is

joining different communities.

499

So there's a lot of different people

talking about AI and trying to learn AI.

500

I would say join those communities,

find mentorship, right?

501

To grow your data literacy

or your AI literacy.

502

So I would use all different options and

try to use it as personal development.

503

There's a lot of this is, you may be

working for a company that isn't as

504

advanced or may not have those resources,

but for you to really develop, right?

505

You have to take that in your own hands

and figure out what are the resources

506

avAIlable to me and really leverage that.

507

And that's what I would recommend.

508

I would not wait for as an

employee or employer to say, this

509

is what you need to learn next.

510

Absolutely not.

511

Go learn and ask questions.

512

And if your employer supports you

Through, like I said, tuition assistance

513

programs, or maybe they have a LinkedIn

learning program, or I would use those.

514

Also just look at your broader

community and see if you can find

515

a mentor and others to partner

with and just learn and play.

516

And I think that's the

best way to go about it.

517

Thomas: So I have to ask, before

we run out of time here, Amy.

518

As you look ahead for the next couple

years, is there anything in particular,

519

whether it's in shared services or

in any kind of like specific domain.

520

Are there any particular types of

521

projects that you're passionate

about, you're looking forward

522

to seeing come to fruition.

523

Or even just like workflows.

524

'Cause we talked a lot about AI workflows

or AI being leveraged for all types

525

of like workflows and shared services.

526

Anything in particular you're

looking forward to getting rid of

527

off of your plates as we go into

the brave new future together.

528

Amy: I know that there's a lot

of the transactional stuff.

529

I think there's a lot of just sometimes

there's a lot of data that comes in.

530

Actually in a recent conversation I had

with a different peer in industry, one of

531

their frustrations is actually sometimes

there's a lot of information that

532

comes in, and specifically in employee

relations, under HR, meaning depending

533

on the environment, there's often

534

like a compliance line

or something like that.

535

And people will send immense amounts

of information whether audio or

536

video or documents that they write.

537

And their employees go through

this for hours and hours.

538

And so I thought it would be interesting

when we talked about it was how can you

539

take all that and put it into AI and

then maybe have AI ask more questions or

540

find patterns so you could understand why

are these employees having these issues?

541

So if you take all the information and

it can analyze it for you, it might be

542

able to find patterns to address as a

root cause versus when a person's just

543

reading it and trying to figure out

what is it that I'm trying to solve.

544

So I think there's exciting opportunities

to use it in those types of ways in the

545

future that maybe isn't being used today.

546

Thomas: That's a very

interesting use case.

547

So you're imagining not just analyzing

it one time, but actually having

548

something where you can ask questions

back and forth as the HR professional

549

to really get some insight on what's

happening here, but then level that

550

up to what's happening more broadly.

551

Maybe the organization that we

can then maybe more proactively

552

diagnosed employee relations issues.

553

There's the absolute tail

end of multiple things.

554

It's like this symptom

that you can get at.

555

But I love that thought for how

that you can take that upstream.

556

What else would you say is advice you

would have for or thoughts for your

557

fellow professionals in HR, but how

we can all stay future proof as the

558

ways that like we're working and what

we're being asked to do, as well as

559

what's being demanded of

us in some ways, right?

560

Whether it's from the C-suite

or from employees or other

561

stakeholders is shifting.

562

Amy: And I'm excited about all the

change that HRs future will be with AI.

563

But I think it's important in our

role is to continue to balance

564

information intelligence with humanity.

565

Having AI reshaped work, I think we

still want people to define the purpose.

566

And so I think AI's role is really to help

guide that shift kinda responsibly, right?

567

So we're building systems that

protect trust, to empower learning

568

and to keep culture and people

at its very center because that's

569

something we don't wanna lose.

570

Thomas: We don't wanna lose that indeed.

571

And I think sometimes

572

the whole function can use that reminder

because you might feel like beaten

573

down and feel like, you know what,

yeah, this is all gonna just come in,

574

replace everything that everyone does

and people are just not as important

575

to organizations in the future.

576

And maybe that's just not true.

577

Thank you for this conversation, Amy.

578

The concept of how shared services

is shifting and there might be some

579

consolidation and it's like maybe in

the future, less about the functional

580

lines, but just really how you go across

those lines together that really start

581

to be where the value is and where

that those organizations can shift or

582

those functions can shift and meld.

583

It's a very interesting concept.

584

And there's just so much that you're

doing in terms of both staying up to

585

date yourself and educating others

on around all the different ways.

586

And we kind talked about a couple of

different types of workflows, whether

587

it's audits or we're like talking about

just like we were just now about this

588

concept of proactively taking employee

relations information to change up how you

589

work culturally as an HR function, which

is one of those signs I think you would

590

agree of what you talked about, which is

a way to make these connections with data

591

and actually uplevel what value we're

bringing to the organization overall.

592

So there's some great both practical

and also conceptual insights here.

593

Thank you for that.

594

And for anyone who is out there

looking to future proof your own

595

organizations and your own HR functions.

596

I trust that you've taken at least a

couple of nuggets of insight here from

597

this great conversation with Amy Wang.

598

Thank you again and see

you on the next one.

599

Speaker 2: Thanks for joining us

on this episode of Future Proof HR.

600

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how we can all thrive in the age on AI.