In this episode of the Future Proof HR podcast, Thomas Kunjappu, CEO of Cleary, sits down with Fernando Garcia, Vice President of Corporate Services at Cargojet, to unpack what HR leaders are getting wrong about AI, and what they should be doing instead.

Fernando brings a rare blend of experience across HR, legal, compliance, and business strategy, and he makes a clear case for why AI will not replace HR, but it will reshape the job. The work that remains, he argues, is the work that matters most: human judgment, context, experience, and the ability to make value-based decisions when the answer is not obvious.

Together, they explore the practical reality of “shadow AI” already happening inside organizations, why guardrails matter more than hype, and how HR can work with legal as an early strategic partner rather than an emergency hotline once something has already escalated. The conversation also goes deep on the ethical tension of AI-driven hiring and fairness, including how bias can show up on both sides, whether decisions are made by people or machines, and why the “trolley problem” isn’t just a thought experiment anymore.

This episode is for HR leaders who want to adopt AI responsibly, without parking their judgment at the door, and who want to future-proof their work by leaning harder into the human side of leadership.

Topics Discussed:

1. AI will change HR jobs, not eliminate them
2. Why HR’s value is judgment, context, and the human element
3. The “three-legged stool” of business, legal, and people leadership
4. How HR and legal can partner early to prevent risk, not just react to it
5. The reality of “shadow AI” and why assuming no one uses AI is the biggest risk
6. Practical guardrails: data privacy, PII, sensitive employee info, and due diligence
7. Where AI helps today: drafting, surveys, training design, and early recruiting support
8. The ethics of AI in recruiting, fairness, and bias on both sides of the argument
9. Why culture, training, and peer learning matter more than expensive enablement programs
10. Skills that will matter most for future-proof HR: curiosity, EQ, relationship-building, and broad capability

If you’re an HR leader trying to balance innovation with compliance, curious about AI’s real use cases beyond automation, or navigating how to adopt these tools without losing the human element, this episode offers a grounded and thoughtful framework.

Additional Resources:

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

Are you nervous about AI taking away work?

2

I think no, I think it's going

to change our jobs and it's

3

going to change what we do.

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But the value that we truly

add is that value judgment.

5

That knowledge base.

6

That experience that you're

bringing into your role.

7

And I think that human touch,

that human element of it is

8

really what adds our value.

9

And I think that's no matter what,

that's never gonna be taken away.

10

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 the Future Proof

HR podcast, where we explore how

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forward-thinking HR leaders are preparing

for disruption and redefining what it

22

means to 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 Fernando Garcia,

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Vice President Corporate

Services at Cargojet.

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With 15-plus years of experience across

general counsel, HR and labor relations

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compliance and corporate secretary

roles, plus a BA in labor studies and a

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master's in industrial relations and HR.

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Dual civil and common law degrees,

and an MBA in strategic management.

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I think it's fair to say, Fernando

brings a rare T-shaped blend of legal

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depth and business people breadth.

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So he leads at the intersection

of law, business, and innovation.

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And advocates for pragmatic adoption of

legal and HR tech to unlock efficiency

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while at the same time managing risk.

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Fernando, welcome to the podcast.

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Fernando Garcia: Thank you very much.

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It's a pleasure to be here and,

looking forward to our conversation.

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Thomas Kunjappu: Absolutely.

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So, I'd love to set up our

conversation with this concept of

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the three-legged stool I think we

were talking about a bit earlier.

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We've got business, legal,

risk management, and people.

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Now you've pursued degrees and have

worked in a combination of all three.

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How do you see that all coming together?

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Fernando Garcia: When I look at

what makes a business successful,

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I think, and looking back at it

when I first started my career, I

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thought there were three elements.

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One is obviously the people.

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The HR part is critical.

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It is what distinguishes

one company from another.

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That is what makes a place attractive

for someone to go work at and stay there.

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The other part is legal.

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We're all involved in an environment

of laws and regulations and compliance,

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and that affects how we do our job.

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That affects how companies go to business

and which companies are successful.

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And then obviously the business

component of it, the business strategy,

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the planning, and, making sure your

products are meeting the needs of

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society and they're adapting as

necessary to be able to be successful

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in your environment or your market.

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So when I was looking and thinking, how

do I wanna shape my career moving forward?

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I thought those are three elements

that I really wanted to touch on,

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become experienced in and really

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gather experience.

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So one was the educational background,

which you've read already, quite exciting.

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My wife always complains that if I

could, I would be a lifetime student.

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And I think in many ways,

we are all lifetime students

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because we never stop learning.

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We never stop developing.

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We never stop growing.

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And if we do, that's

when things get boring.

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So we're always looking at that.

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But those are three areas that

are of interest to me in terms of

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education, but also in terms of

what I do on a day-to-day basis.

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I don't want to be just a lawyer, and

I don't want to be just an HR person.

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I want to be a business person

with an HR and legal background.

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Thomas Kunjappu: I love that

concept of combining these two,

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so it's like one C two functions.

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but tell me where you see the

strongest synergies between

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specifically HR and legal.

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I mean, my mind and probably everyone's

mind goes to like employee relations

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and like, just making sure that

you're, you know, firing and doing

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things in a compliant way, right.

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And on the people side.

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But yeah, tell me about how you see the

two coming together in your day to day.

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Fernando Garcia: I think a lot

of it is also risk management.

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Some of those elements that you mentioned

are very important on a day-to-day.

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Making sure you avoid litigation,

making sure you're following proper

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processes and hiring, firing, and

all those day-to-day things of HR.

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But there's an element of HR that

looks longer-term, more strategic, more

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longer term value-based, and the legal

environment and the legal background also

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helps you mitigate risk in the long run.

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So helping strengthen your brand

and making your brand stronger, both

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locally and internationally, and

understanding what are the things that

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are gonna impact it so that you can.

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Be successful in that environment.

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And part of that is a huge part of

it is having the right people in the

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right jobs and feeling like they wanna

stay and be developed, have their

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skill set acknowledged really fully

developed within the corporation.

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So it's in the short term and in the long

run that I think there's a ton, tons of

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synergies between HR and legal itself.

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Thomas Kunjappu: When you say 'short

term and long run,' what do you mean?

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Like in day-to-day

tactical things, but also.

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Fernando Garcia: If something happens

and I need support or I need your

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advice regarding this particular

issue that we're dealing with today.

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But also thinking about longer-term

in terms of where businesses are

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going and what are some of the

unique needs of risk mitigation,

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development and all the fun stuff.

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And AI walks right into that.

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Thomas Kunjappu: So okay, let

me ask for some advice because a

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lot of HR leaders don't have your

background in and training in law.

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But of course are very much in the weeds

or their teams are in compliance, right?

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Fernando Garcia: Yes.

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Thomas Kunjappu: So what have you seen

or what would be your advice for HR

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leaders in terms of like how they can

best work with the legal department?

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Fernando Garcia: Yeah, I think

it's also a function of the

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mindset of your legal department.

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There's legal departments that

are like I always say that the

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people who are in charge of forms

347C, and all they do is 347C.

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And if you have a legal question

about that form, you go to them.

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But then there's also the

legal departments And I've been

120

advocating for a long time.

121

you mentioned that the T-shaped

lawyer or I called it the plus-shaped

122

lawyer in one of my articles

that I wrote many years ago now.

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Not just being a legal department

that handles legal questions, but

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that it's part of the business

integrated into the business.

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And that's the case.

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I think HR and legal working together

really help to fill the void to

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mitigate risk, which is the things

that are very important for us.

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And for anyone really operating

in an environment, right?

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Because you don't want to create

any kind of a situation or in the

130

environment or to the company.

131

Thomas Kunjappu: If you're talking to

like your friends, colleagues in HR

132

who are not obviously lawyers as well.

133

Like what are the kinds of things

that were you or situations,

134

did any situations come to mind

where you feel like this was I

135

wish in this case the HR

department had like checked in or

136

worked more closely with legal.

137

And are there any kinds of situations

that keep coming up in your mind where

138

you know, the HR function could work

more tightly with the legal department?

139

Fernando Garcia: I think if you look

at your legal team as a business

140

strategic advisor and really

part of the business itself, then

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you get them involved early on.

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The biggest issue or what I look at one

of the greatest limitations is when you

143

get involved with legal but too late.

144

Once something has already blown up,

once something's already a conflict or

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there's a potential litigation issue.

146

At that point, it's much harder

because your tools or the available

147

outcomes are already much more limited.

148

But if you get them involved early

on, if the relationship is one of

149

constant communication, interaction

and working together on things, you

150

can be proactive and address the

issues before they even become issues.

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And that's where when you

add the most value, because

152

you're working hand in hand.

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And again, I've seen many

situations of people who are

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lawyers who go and in terms of HR.

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And I've seen the other way

around too, HR people who are very

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specialized, especially in areas like

labor relations, and then they go

157

Thomas Kunjappu: Oh.

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Fernando Garcia: they take

on a quasi-legal function,

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Thomas Kunjappu: Sure.

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Fernando Garcia: their organization.

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So it goes both ways.

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But I,

163

Thomas Kunjappu: Yeah.

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Fernando Garcia: find that there's a

lot of synergies there in terms of the

165

functions and the roles that we play.

166

Thomas Kunjappu: So, you talked a

little bit about that mindset then.

167

The T-shaped mindset, but

also the ability to be like a

168

focus on the business outcome.

169

Like regardless of kind of function.

170

So sounds like that might apply equally

to HR and legal on both sides, right?

171

But you also mentioned how that

mindset may be actually even like

172

a perfectly fit for the age of AI.

173

So tell me about that.

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From both perspectives.

175

And especially from a risk mitigation

and compliance perspective, which is what

176

we've been talking about so far, right?

177

How do you think about AI,

especially with that mindset of

178

being flexible, agile, T-shaped?

179

Fernando Garcia: Yeah, I think AI brings

another element to our toolkit and it's

180

a critical tool in terms of helping take

away maybe some of the more administrative

181

functions or responsibilities and

really focusing more on the value-added.

182

Giving you another person that they, it's

a virtual person that you can run ideas by

183

come up with alternatives.

184

Now again, I wouldn't say it's a

professional partner because I think

185

there's still some development to go.

186

and you've got to be somewhat critical

and you've got to be careful about

187

what information is given to you and

how you are using that information.

188

So you've got to check in and you

still have to go do your due diligence.

189

Thomas Kunjappu: Sure.

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Fernando Garcia: I think it's a critical

tool in terms of helping take away

191

the more intensive administrative

functions and really helping you focus

192

on where you can add the greatest

value in terms of your organization

193

and even your function itself.

194

With the caveat you've got to

be careful with it as well.

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Thomas Kunjappu: And I

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Yeah, let's get very specific then.

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Like what's your safe list or

the more exciting things to talk

198

about is like, don't do this.

199

These areas are just like,

you know, you've got to be

200

really careful about with AI.

201

But how do you or maybe you

can kind of answer both.

202

Like, how do you think of it?

203

What is safe?

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What are you gonna go into, what's

okay to experiment with versus where

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do you really need to be careful?

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Fernando Garcia: Yeah, I think

like anything, I want to give you

207

lawyer answer, but it depends.

208

really the fundamental here is to make

sure that you're understanding terms and

209

conditions in terms of what you're using.

210

If you're putting in private information,

make that you understand that it stays

211

and contains and, working IT department

to make sure it's a closed system versus

212

the information putting in all of a

sudden becomes part of the public domain.

213

you're putting in sensitive employee

information in there, possible health

214

information, which is obviously, HIPAA

and some of the other concerns that

215

you have in that particular case.

216

But if you have all that covered

up that issue is not a concern.

217

It does open up the possibilities

in terms of how you can use it.

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Just mindful of whatever information

you put in there, you have to double

219

check, you have to review it's safe.

220

Not gonna have loss of privilege

issues or you're putting out

221

personal information onto the domain.

222

But in terms of that element of it, I

think there's a lot of opportunities

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too in terms of recruiting in terms of

drafting letters, in terms of just really

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sometimes even just getting you started.

225

But the key is you

still have to review it.

226

'Cause it does tend to

hallucinate at times.

227

And there's also the concept of

garbage in is garbage out, right?

228

So you have to make sure that whatever

you're, how you're prompting it or

229

what information you're feeding it

is gonna affect what the outcome is.

230

And you got too be mindful

of that part of it as well.

231

Thomas Kunjappu: So I guess

there's a lot to consider.

232

Are there, but.

233

it sounds like, I think you're saying

there there's a clear set in your

234

mind, of areas you have to like

make sure that you're bulletproof

235

on in terms of risk mitigation.

236

Right?

237

And data privacy.

238

And once that's in place, would you say

that's pretty universal is it really in

239

your view, besides cultural expectations

where some companies are more AI forward

240

versus, or innovative versus others,

241

Fernando Garcia: Yeah.

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Thomas Kunjappu: like there's like

a kind of a generic sense of, you

243

know set of guardrails across all

industries, across all companies?

244

Like, hey, no training with this

data for the core LLM models, there's

245

some kind of like onboarding and

training for every employee who's

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gonna have access to these things.

247

PII or customer data should not be on

this or this is the specific guardrails.

248

And there's trainings on that.

249

You know, there's a set of

things you could come up with.

250

And do you feel like that's like pretty

universal and really in the only gap

251

is cultural or in your view like from

what you can tell, it's just like, it

252

just, every industry is like different

and you really have like nuances about

253

Fernando Garcia: Yeah.

254

Thomas Kunjappu: is

what the guardrails are.

255

Fernando Garcia: I think it's

beyond just every industry.

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I think every company, every

location is at a sort of a

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different stage in their journey.

258

And some people are still

very much experimental.

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Some people are all in and they

want all their employees to have

260

access, all their employees to be

properly trained and other employees.

261

The reality though is that most

people, whether it's on a personal

262

basis or at work, are using something.

263

you've got to make sure that you train

them up in terms of saying, look, if

264

you don't have the proper guardrails

in place, still use it, but be mindful.

265

Don't put employee information in there.

266

Don't put names, don't put

personal information, don't put

267

stuff about products I haven't

released to the public yet.

268

Don't put market share data sensitive

pricing information unless you are at

269

that stage where you've now checked

the box and everything's okay,

270

and there isn't that risk element.

271

So every company, every location

will be at a different stage of that

272

journey, but I think the biggest risk

of them all is assuming that nobody in

273

your company or no employees using AI.

274

because I think more and more, whether

it's just to write a greeting card or

275

to start an email, or really to check

a report or review something, or even

276

draft, initial stages of reports.

277

People are using it.

278

So you have to be mindful of that

and you've got to be mindful of

279

how knowledgeable are they of

it and how can they protect the

280

information as much as possible.

281

Thomas Kunjappu: Yeah.

282

Fernando Garcia: So some minor

training I think is critical.

283

Regardless of where you

are in that journey.

284

Thomas Kunjappu: Yeah.

285

So regardless of whether you've

adopted wall to wall some kind of

286

like LLM enterprise solution or not.

287

In all likelihood, someone

out there is using it.

288

In previous years, we'd had this

concept called like shadow IT and that

289

when SaaS was first coming into the

fore and now there's like Shadow AI.

290

That there's usage happening and

it's similar things, like your

291

data could be leaking without

the right kind of guardrails.

292

I'm very curious, given your two

halves here, where do you think there's

293

more, there's been more adoption of

AI tools within the legal kind of

294

community for all types of contract

law, employee law, there's all types

295

of paralegal type of work or the HR

world which, you know, our audience

296

obviously like, knows a lot about.

297

But do you think there's a

I don't know, an emergent

298

any differences in terms of adoption

or like, if you see like the different

299

communities that you're traveling in and

the general stance towards these tools?

300

Fernando Garcia: Yeah, For example, we

were talking about the legal industry.

301

I think you can break

it up into two parts.

302

Because you have the in-house counsel

and then you have the external

303

lawyers who work at law firms.

304

Big law firms tend to have more resources,

tend to have more training and tend to

305

have more of that giving them the tools

and having the parameters properly set.

306

In-house counsel, depending on the

size of the companies they work at they

307

can have that available to employees

and training and everything else.

308

Or you could be in a smaller

organization where there's less

309

of that, less of that training.

310

But I think in HR, same concept.

311

I hear from people who are very much just

drafting emails with it or doing some

312

preliminary to people who are getting

resumes for a particular role and they

313

run a preliminary search through the a

hundred resumes, say, pick me the top 10

314

based on the following job description.

315

But again, you've got to be

very mindful of that as well.

316

That you've got to be careful

that you're still doing that.

317

Your proper check and your proper

due diligence because I hate to

318

be in a situation where people are

using AI to create their resumes.

319

Then they're using AI to check amongst

the resumes to see which is the best

320

one to then check it against the job

description that was developed by AI.

321

And at the end of the day, AI's just

doing your recruiting and it takes

322

away that human element, which is I

think, at the end of the day, critical.

323

What a resume shows or what a resume

provides doesn't necessarily mean

324

that person's gonna be a good fit

within the environment, within the

325

industry that you work in and that

they're going to be successful.

326

Thomas Kunjappu: Well, the part

that you're missing in that

327

equation is that the candidate

pool is also not standing still.

328

And that resume that these AI tools are

reviewing are half generated customized

329

in response to the AI generator job

description to give it a great likelihood

330

of advancing to the next stage.

331

Fernando Garcia: Yeah.

332

Thomas Kunjappu: Just AI

tools fighting AI tools.

333

And there's just like volume

of applications jumping up like

334

dramatically in all types of roles

335

Fernando Garcia: Oh,

336

Thomas Kunjappu: because it's,

337

Fernando Garcia: That's

338

Thomas Kunjappu: yeah.

339

Fernando Garcia: trend that

you're seeing that for any role

340

where you might have had 20 to 25

applicants, now you're getting 200.

341

Which makes it even more important

to have the tool to go through and

342

least the initial process to try to

narrow it down and to focus on it.

343

But again, you've got to be very careful

in terms of what it is doing and that

344

you're still having an element of

human judgment and discretion in it.

345

Because I think that's

where you add the value.

346

Thomas Kunjappu: I think you're

getting to a key, almost ethical

347

concept, arguably, right?

348

Which is sitting at the

intersection here about fairness.

349

And really about bias avoidance.

350

It's very obvious as a concept

in the recruiting process.

351

But you know, also in performance

management all the way to

352

performance improvement processes

and firing situations as well.

353

But it's across the board like important

as AI tools get into the workflows here.

354

So yeah, how do you think

about the ethical side of it.

355

Besides the efficiency and besides

the legal ramifications, how do you

356

even think through and we can take any

one of those like use cases and like

357

think through a little bit together the

ethical consequences of leveraging AI.

358

Whether there's bias or judgment

that you're now outsourcing

359

to Artificial Intelligence.

360

Fernando Garcia: Yeah, and it's

interesting because you get people

361

who are on both sides of the equation.

362

There are some people that say that

the more you use AI, the more you

363

take away the potential bias of

the person who's doing the review.

364

Thomas Kunjappu: Right.

365

Fernando Garcia: Other people say, hold

on a second, somebody has programmed

366

it or it's learned from something.

367

It just doesn't come

up with these concepts.

368

The training.

369

So somebody at some trained it, and

then the biases or the experiences

370

or whatever else of that training

element, wherever it's coming from,

371

will creep into the decision making.

372

So it's almost like one of those dilemmas.

373

Is it taking away the bias by using

more AI or is it just perpetuating the

374

bias by using the tool that was created

by somebody who obviously had bias?

375

What at what point do you minimize that.

376

And do you get the best result?

377

Thomas Kunjappu: Right.

378

Well, that's a great question.

379

I mean, in the world of self-driving

cars, you have a specific outcome

380

where you're trying to reduce accidents

and make sure that streets are safer.

381

And you have an outcome metric

that can be relatively objective.

382

Maybe the issue in hiring is

that the outcome metric is

383

like who judges the outcome.

384

Fernando Garcia: Yeah.

385

Thomas Kunjappu: Like fatalities is an

objective measure and there's like data

386

that you can get that you can trust.

387

In this case, it's like, well, you

can make hires, but is it a good hire?

388

Was it the right hire?

389

Do we miss other people?

390

There's so many other aspects to it

and at least this one facet, arguably.

391

You know, hiring humans is more of a to

392

really get to clarity in

393

what is like the best outcome.

394

But you mentioned these both sides

of the argument are you convinced

395

or swayed by either side or...

396

specifically with recruiting?

397

Fernando Garcia: sides.

398

I wanna remain cautious and

knowledgeable that there are risks

399

and there are limitations both ends.

400

And you mentioned the autonomous

vehicles, for example.

401

Even that has a bias.

402

And there's a great website, I'm

trying to remember the name of it.

403

It's by MIT and I think

it's called Moral Machines.

404

And it basically says this: you're

driving your autonomous vehicle.

405

And who's driving it?

406

The autonomous vehicle is.

407

And it comes to a situation where

it must decide, is it going to

408

get into an accident and kill the

occupant or is it going to kill one

409

person who's crossing the street?

410

What if it's two people crossing

the street versus one occupant?

411

What if it's other people crossing the

street and it's two young children in

412

the car and it starts creating all these

moral dilemmas in terms of saying at

413

some point something's got to decide.

414

And depending on what your value is,

if you're a car company that comes

415

out and says, as of 2030, I'm going to

have zero occupancy deaths in my car.

416

Then that means that when it has to

make that moral decision, it's going

417

to obviously prioritize the safety and

wellbeing of the people in the car versus

418

the ones who are crossing the street

and getting to an awkward situation.

419

So I think even when you're

looking at something as autonomous

420

vehicles, there's still a value

judgment that will come into play.

421

And I can totally see it, that at some

point it'll say, whoa, I don't know.

422

I can't make that moral decision for you.

423

Here's a steering wheel back.

424

You decide, are you going to put

yourself in a ditch or are you

425

going to run over the two people

who are crossing the street.

426

Maybe jaywalking or something else.

427

Even at that level, even autonomous

vehicles, that technology still

428

will have a number of bias to it.

429

Thomas Kunjappu: Fair point.

430

I mean, you're talking about the

trolley problem, but instead of

431

like deciding between two different

external parties and a human deciding,

432

it's an AI deciding between, in this

case, like a customer who bought

433

their product and like someone else.

434

But that's a tricky dilemma to get into.

435

And the outcome or like the escape valve

let's call it is that well, okay, we don't

436

know, let's let the human needs to decide.

437

So in the recruiting world, if we come

back to what we're talking about, it's

438

like we need to let the recruiter or the

manager with all the human flaws and all.

439

We're gonna attribute it to

this person so that we can

440

move it out of the hands of a machine.

441

Fernando Garcia: You can do all

the behavioral testing you want.

442

And you can do all the

testing and the AI reviews.

443

But at the end of the day, having

that person meet, whether virtually

444

or in person with the team.

445

and seeing that interaction,

seeing how they're going to fit

446

in, seeing how well they're going

to thrive within that environment.

447

Nothing will replicate that.

448

Why people always say, are you

nervous about AI taking away work?

449

Or I think no.

450

I think it's going to change our jobs

and it's going to change what we do.

451

But the value that we truly

add is that value judgment.

452

That knowledge base.

453

That experience that you're

bringing into your role.

454

And I think that human touch,

that human element of it is

455

really what adds our value.

456

And I think that's no matter what,

that's never gonna be taken away.

457

There might be less labor intensive

elements of it and there's gonna be

458

questions about how do you get people

trained and make sure that when you're

459

using AI you're not just parking your

brain at the door that you're still being

460

critical and you're using it properly

and you're learning how to prompt.

461

But you're also learning

how to apply the knowledge.

462

But at the end of the day, I think

that is truly where we add value.

463

Is the human piece.

464

And I think that's never going to go away.

465

This has been a fantastic

conversation so far.

466

If you haven't already done so,

make sure to join our community.

467

We are building a network of the

most forward-thinking, HR and

468

people, operational professionals

who are defining the future.

469

I will personally be sharing

news and ideas around how we

470

can all thrive in the age of ai.

471

You can find it at go cleary.com/cleary

472

community.

473

Now back to the show.

474

Thomas Kunjappu: So how do you imagine

that transition happening then?

475

So that folks and let's focus on

like the HR department as as a whole.

476

You said maybe we're not gonna be spending

as much time on the administrative

477

elements of it and the repetitive tasks.

478

So how do you imagine going from

like today to like, what does

479

that future state, look like?

480

Fernando Garcia: Yeah.

481

I think, if you gain the 200

resumes for that single job,

482

if you can cut it down to 15.

483

Using AI and then understanding that

within those 15 you still have to go

484

in there and do the review, meet them,

do the screening, to see how they're

485

gonna apply in your, workplace and

how they're going to thrive within it

486

and what that we're gonna add to it.

487

I think that's part of it.

488

So it'll help you get partially

there, but you still have

489

to drive it home at the end.

490

And you still have to use

your judgment on that part.

491

Thomas Kunjappu: So are we okay with

the moral hazard of AI eliminating

492

90 out of a hundred resumes and

is is that gonna be unbiased?

493

'Cause what we're saying is like

at least for that one phase of

494

the application process, then we

are okay with the trolley problem.

495

Whatever value judgment that we're

maybe helping program into the AI.

496

But we're gonna.

497

Use that to make some judgment, right?

498

And then continue onwards.

499

Ultimately it's a practicality I feel

like for a lot of recruiting teams.

500

Because if you have a thousand

resumes like what do you,

501

right.

502

So do you kind of escape the ethical

problem because of the necessity?

503

Fernando Garcia: I think you have

to be aware of the ethical problem

504

and you have to be aware of the

potential risks associated with it.

505

And then at that point, I think

it depends on the role, right?

506

If it's a critical role.

507

Then maybe you say look, this

is such an important role that I

508

will go through the 200 resumes.

509

Some other one that maybe isn't as

critical or one that maybe isn't fit

510

is not as important or who knows.

511

Whatever the parameters are.

512

Maybe that one requires a

little bit more or allows you a

513

little bit more space in that.

514

But again, I think there are elements

of you always have to be aware of.

515

And the biases are there.

516

And but again, I think

there are risk both sides.

517

'Cause the bias of a person we're

reviewing the resumes could also

518

be as important as a bias in the

technology or how we're separating

519

it or doing the first cut through AI.

520

You are never gonna completely eliminate.

521

I think regardless of the two.

522

Gotta be aware of it and

you gotta be mindful of it.

523

Thomas Kunjappu: Yeah.

524

One idea I had as you're saying that is

that the roles which the organization

525

has hired like hundreds of in the past.

526

You've had like over many years and it's

like the same kind of background that's

527

successful and you've established that

qualitatively and quantitatively, right?

528

So these is all input into like whatever

you're using for screening as an AI tool.

529

So the more I guess validated

specific input data you have on

530

a specific decision, the more

maybe you've controlled bias.

531

And you're maybe more comfortable

ethically, you know, moving efficiency

532

around versus hiring for the first time

for a role ever in in a new context.

533

You just literally don't know.

534

right?

535

What is the background or like what

are the set of characters that a

536

resume can say that actually represent

success if it's never been done.

537

Especially at this organization before.

538

Fernando Garcia: But again, there's no

single answer and no single right answer.

539

Because again, you always hear

that the most dangerous words are

540

we've always done it that way.

541

So just because always hired this way

and obtained this level of performance,

542

you don't know if taking a different

approach or hiring people maybe who

543

are not normally the people you would

hire for that particular role is not

544

gonna elevate level of performance.

545

So you also have to every once in

a while just break up from that

546

trend and be able to think outside

the box and maybe go outside of

547

the areas you normally hire from.

548

Maybe go outside of the colleges you

normally hire from or whatever, because

549

that is how you identify potential value

that might have otherwise been lost.

550

And I think that's where AI can

maybe fail because it does look at

551

trending, it does look at what have

you done and it establishes a basement.

552

But sometimes you wanna go

above and beyond that basement.

553

I think that's when you don't

even be a lawyer or anything else.

554

The creativity of a novel argument

or some additional way of looking at

555

something which has not been done before

is when you're truly adding value and

556

you're elevating that performance from

what is normally you're accustomed to.

557

And the question is, will AI ever

get to the point where it can do that

558

additional critical thinking or jump to

say, this is what you've always done,

559

this is what you've always achieved,

but if you do something different,

560

you might be able to get here now.

561

Because we tend to learn from the past.

562

We tend to replicate the results.

563

But the question is, it starts

getting to the point where it's now

564

cognitive and starting to make it's

learn and go beyond just the confines

565

of the past or previous decisions.

566

That's when it starts getting interesting.

567

Thomas Kunjappu: Right.

568

Like incorporating new data about

like what the business needs

569

now, for example, or like what's

shifted now and yeah, absolutely.

570

Fernando Garcia: much risk is your

company willing to take in this role.

571

To say look, maybe we go outside of

the normal beaten path and maybe look

572

for that purple unicorn or it was a

purple squirrel that they call it.

573

That additional person and sometimes

you gotta go outside of that to find it.

574

Thomas Kunjappu: Let's get

a little bit practical then.

575

Can you tell me about the key workflows,

use cases that you've personally seen.

576

Like some success in and maybe others

that you're excited about where AI can

577

start changing the way work has done.

578

Fernando Garcia: Yeah, some of

the interesting functions that

579

I've seen or applications are

things like employee surveys.

580

Finding trends and identifying things

that maybe you need to focus on developing

581

training programs for individuals.

582

Go in there and say, look,

this is where I'm having a gap.

583

How do you recommend that?

584

training, it can help you

develop training programs.

585

We talked about the recruiting

obviously that's a critical

586

one and job descriptions.

587

Helping you take that initial

draft and the things that you do.

588

The letters, you have a transformation

coming up and all of a sudden

589

you're last minute rushing it.

590

It can help you get the first draft

going and then you can perfect it.

591

So I think, if people are starting to get

curious, people are starting to use it,

592

companies are developing pilot projects

and getting individuals who are trained

593

to start applying it and then once they

see an element of success and comfort and

594

they start adopting it to greater numbers.

595

Everybody's handling it differently.

596

But the beauty is people

are looking at it.

597

right?

598

And again, challenging the status quo

in many ways and just trying to be

599

more value and doing more with less.

600

Which is I think the reality of all

of our jobs and of our functions.

601

Thomas Kunjappu: So

tell me more about that.

602

What are you seeing within the world

of like HR specifically around this

603

concept of doing more with less?

604

Is that seeming like universal.

605

Like with your peers?

606

What's the solution here?

607

Like how do we get to the point of

like being productive and getting

608

resource enough to be able to do that?

609

Fernando Garcia: Yeah, I think

there are those who are the

610

trendsetters who are using it more.

611

And then you go to a conference

or you go to an event and you

612

start talking to other people.

613

This is what I've done with it.

614

This is how I used it.

615

Somebody else goes, Ooh, that's

actually a pretty good idea.

616

Yeah.

617

Try that.

618

Right.

619

The critical element of this is the people

who are gonna be the trendsetters and

620

the people who are gonna be able to adopt

the best practices or learn from what

621

others are doing and start implementing

in their own play in their own way.

622

But the key is just being

curious using experimentation.

623

Bringing things in and doing

things differently the AI and

624

where it's going and technology.

625

But again, AI is one element but

it's not the only element, right?

626

Those information that you're

taking from HRS systems, from

627

contract management systems.

628

Data is power and the information

in the technologies is critical

629

in terms of us and our functions.

630

Thomas Kunjappu: So if that's where

things are headed, like what do you

631

think are the kinds of people or

skillsets that are coming into the fore?

632

Who are gonna be more effective

going into the future?

633

A lot of what we try to talk

about is future proofing.

634

right?

635

Fernando Garcia: Yeah.

636

Thomas Kunjappu: In

like whatever function.

637

And actually maybe let me

ask a specific question.

638

Is it getting to the point where

job descriptions are starting to

639

more heavily feature, you know,

either the ability to learn...

640

Like rethink how you're doing

workflows and or all the way up to

641

demonstrated experience in leveraging

AI to bring out efficiencies.

642

Like...

643

Fernando Garcia: Yeah, I

644

Thomas Kunjappu: ...where,

645

where.

646

Fernando Garcia: ...a

647

lot of that yet.

648

I think I've seen that in terms

of jobs that are heavy with AI or

649

that are involved in the FinTech

or some of those things like that.

650

Where that's critical component right now.

651

But I think at some point I wouldn't

be surprised if we start seeing

652

things like experience in AI.

653

Yeah.

654

Or even then making the assumption that

maybe people are not coming in with that.

655

But really focusing on

training that skill set.

656

Because I think companies can do a

really good job in terms of helping

657

people develop and get comfortable

and see how that can apply.

658

Whether it's through mentorship

with people who are in the industry

659

or in your department when you

come in and they can help you.

660

Look, this is how I'm using.

661

How are you?

662

Things like lunchtime training sessions

and sharing your best practices and tips.

663

Prompting, things like that.

664

I think that they're critical.

665

So it's a question of do

you buy it or you make it.

666

And some I think it's gonna

become more and more that

667

they put that as a preference.

668

But I think at the same time, people

are saying look, let's train up.

669

Let's get this as a skill

set that we're developing.

670

No different than leadership training

or any other country that we do on a

671

day-to-day that we can do AI efficiency

training or adaptive technology training.

672

Again, it's gonna be

critical advantage one day.

673

Thomas Kunjappu: So if that's

true, how do you square that?

674

And I would imagine we'd agree

that, the enablement of that for

675

the organization is primarily gonna

be done through the HR department.

676

There's some like, individual on every

functional level, people comparing notes,

677

but you're trying to enable the entire org

strategically up level it for some ROI.

678

How do you square that with less,

fewer resources to make it so.

679

Fernando Garcia: It's one of those where

you invest early to get the benefit after.

680

But again, it doesn't

have to be expensive.

681

You can get somebody who's very

knowledgeable in AI or very

682

comfortable with it that can

just do a lunch hour session.

683

Hey, here's some peaks on the

side and come and sit down.

684

Let's, go through some

examples of how I'm using this.

685

Doesn't...

686

Thomas Kunjappu: Have you

seen the food inflation?

687

Fernando Garcia: Granted.

688

There's formal training, but

then there's training that can

689

happen through peer-to-peer.

690

There's the train-the-trainer concepts.

691

And just associations,

industries, conferences, sharing

692

best practices, sharing tips.

693

I tend to find that's really, important.

694

When I, first became how can I

say this comfortable with the

695

AI, that's how it happened.

696

I went to a conference

and we had a session on.

697

Is what I'm using it for,

these are my tips to you.

698

And now all of a sudden it's

wow, I can do so much with that.

699

So it's really having those people who

are early champions, early adopters,

700

and then having them share their

knowledge and experiences with others

701

within their industry, within the

company and just amongst their peers.

702

Thomas Kunjappu: As people are sharing

and like learning and upskilling.

703

Do you imagine new roles and

titles might even appear?

704

Especially within like HR and legal?

705

I don't know.

706

Within the compliance or

employee relations world or

707

Fernando Garcia: Yeah,

708

Thomas Kunjappu: within recruiting

or you know, just HR support...

709

Fernando Garcia: HRIS-type individuals

who are in charge of data and putting

710

in and analyzing totally see...

711

Thomas Kunjappu: like

system configuration.

712

Fernando Garcia:

Configuration and development.

713

And I took a stat here, it was from

the Conference Board of Canada.

714

Said the 4 in 10 HR teams are using

some sort of AI for talent management.

715

So just looking at that number

again, 4 out of 10, it's not

716

a lot, but it's a number.

717

4 is getting to that critical mass

point where, you know, as long as

718

they can start sharing their past

practice and their learnings with

719

the other six, you'll slowly start

seeing that shift the other way.

720

Thomas Kunjappu: Right.

721

Fernando Garcia: I wouldn't be

surprised if 10 years from now we're

722

looking at the number where eight

in 10 or nine and 10 are using it.

723

Because I think it's a tool.

724

It's no different than

725

computers came up.

726

And I remember working at a law

firm and for the most part, most

727

lawyers were using computers.

728

But there were still a few who

decided to have dictaphone and they

729

were still dictating their notes

730

Oh, interesting.

731

type it up for them.

732

So it took a while to get there.

733

I don't think you'll see that anywhere

else in the firms anymore, anywhere.

734

But there's that transition

period that has to happen.

735

There are people who are gonna

be extremely comfortable with

736

saying, look, hey, I'm curious.

737

I wanna learn.

738

I wanna develop myself and I wanna do it.

739

And there's others who are

saying, hold on a second.

740

I'm fairly confident in what I'm doing.

741

I don't need that tool.

742

So they're gonna be more

resistant to change.

743

But like anything, like any change effort.

744

right?

745

There's gonna be those who

take the change head on.

746

And those who are gonna be

more resistant to the change.

747

You just have to start persuading them

of why it's important, how they can

748

improve their performance by using it.

749

And how maybe they're more worried

about the repercussions of the

750

risks, how you're mitigating those

risks and training them to do that.

751

Thomas Kunjappu: It's funny, maybe

the Dictaphone people were actually

752

ahead of their time because if

you look at what's happening now.

753

Fernando Garcia: Right.

754

Thomas Kunjappu: No one's typing up notes.

755

So if like future focus, you're actually

having the, like an AI transcription,

756

happening off of the call to then

summarize and kind of go further.

757

Which then you might like review.

758

Which is closer in some ways, right?

759

To the voice dictation, which

then is manually written up.

760

If we kind of imagine that 4

to 10 gets to be like more like

761

10 out 10 like eventually over time,

what do you think and to your point,

762

yes, like AI it's a tool, right?

763

It's a tool set that you can leverage

humans can and will leverage.

764

And it's kind of the

next phase of technology.

765

If you just focus on the

humans for a moment, right?

766

What is the advice that you have for

someone who's young and just coming outta

767

school, maybe looking to go into HR.

768

Maybe even considering law school, right.

769

And is just trying to think about

like what they should be, like what

770

skill sets they should really be like

trying to focus on to make sure that

771

they're employable in the future.

772

What advice would you have for them?

773

Fernando Garcia: Yeah.

774

I always say try to focus on

getting the broader or as broad

775

of a skill set as possible.

776

And the curiosity and the use

of technology is one of'em.

777

Don't lose track of

the ability to network.

778

The ability to build human

connections and interactions.

779

To be able to work with people.

780

The emotional intelligence is critical

in terms of everything that we do in

781

HR, legal or anything else that we do.

782

And it goes back to that T-shaped concept.

783

right?

784

Where your legal or your HR knowledge

could be this, but then there's

785

the whole horizontal piece where

there's all these other skill sets

786

that's so critical for you to have.

787

Whether it's project management skill

sets the relationship building or with

788

diverse and international workforces.

789

That there's all these things that

add value to you as a person that

790

are not gonna be just technology.

791

So you've got to be careful not to be the.

792

the person focuses on a

technology's helping you do A.

793

But what else are you doing?

794

How else are you doing in your

skill set and how else are you

795

contributing and adding value to it?

796

The technology's gonna help us

get to a certain point, but the

797

human piece is always what's gonna

take you above and beyond that and

798

make you successful and adaptable.

799

And adding value to whatever organization

you're in or whatever function

800

or task or role you're taking on.

801

Thomas Kunjappu: That's great advice

and seems timeless in some ways.

802

But then while I have you,

I have to ask, Fernando.

803

Before I let you go, as you're looking

in the horizon of the next couple of

804

years, is there anything in general that

you're working on or a concept that you

805

feel like is going to come to fruition

that you're particularly passionate

806

about that you'd be willing to share?

807

Fernando Garcia: That's interesting.

808

Personally, I've been working a lot in

terms of the legal industry, in terms of

809

making sure that we think of ourselves

as especially as in-house counsel, more

810

as business executives with a legal

background or in an HR background.

811

And really thinking about how we're

adding value to our organization.

812

How we're helping people grow within

the industry or within our companies.

813

How we're identifying talent, how

we're helping those talents stay.

814

I think there isn't one particular

area, but I think it's more about how

815

holistically we're all becoming a little

bit more knowledgeable, a little bit

816

more skilled, and how we're incorporating

all those skill sets to do better work.

817

And to make sure that we truly say

that people value, people matter.

818

And that's one of our strengths

and we're adopting all these tools.

819

Because the one risk of technology

is if you stick to it too

820

much, it might dehumanize you.

821

I think at the end of the day,

that human element of it will

822

never go outta style, will never be

something that doesn't add value.

823

And that's not something we

should ever stop developing.

824

Thomas Kunjappu: I love that thought.

825

And it's something I can personally relate

to and having wonderful conversations

826

like this on this podcast is I feel

it humanizes me more personally.

827

I'm in terms of having conversations.

828

Because you know, working in the

software and AI world constantly,

829

you're just kind of honed in there.

830

But this helps you keep that

human connection no matter

831

what it is that you're doing.

832

So thank you for this

conversation, Fernando.

833

Because we covered a lot of ground

from some I didn't expect to go

834

into the trolley problem where

835

the remix is that AI is making

the decision and you are one

836

of the lives not these others.

837

And relating that to talent

acquisition funnel problems.

838

But it's really interesting how

you're kind of looking at things

839

from a legal, customer contract and

compliance perspective while also

840

very much keeping the HR hat on.

841

And I would think that maybe you

could put finance in there as well.

842

But you know, these are the functions

that typically are the most risk-averse I

843

think it's fair to say in an organization.

844

And maybe by design, sales and

marketing and the CEO is supposed

845

to push for new boundaries.

846

And you're trying to say hey, you

don't want to do that because we'll

847

get sued and we've got to hold back.

848

But it's really refreshing to

hear about your nuanced position.

849

Because even if that's true, you're

very much like an early adopter of

850

AI tools, which have ethical and

efficiency issues and trade-offs.

851

But simply cannot be ignored.

852

And you know, I like the

nuance in our conversation.

853

Where it's every company and every

role might have a different nuance for

854

how you might use AI versus people.

855

And that probably goes more broadly.

856

And it's really important

to weigh those things.

857

Even though you have some fixed

guardrails to get started with.

858

And thanks for going through

some of those, because

859

Fernando Garcia: Yeah.

860

Thomas Kunjappu: A lot of companies

are just getting in the early stages

861

of that journey of figuring out how

to go wall to wall or enable people.

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So I think that would be helpful for

folks who are out there listening,

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who are looking to future proof

their own functions in HR but

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also their organizations overall.

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So thank you once again,

Fernando, for the conversation.

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Fernando Garcia: It'll be interesting.

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Five years from now, we'll look back

on this and say wow, we either got it

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right or we completely missed the boat.

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Or technology and AI started

developing completely different

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ways and the applications were

that we never thought about.

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But it's an interesting time and

if I can say anything it's just

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stay curious and do it safely.

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And do it within the guardrails.

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But do it because it's an exciting time.

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We have an incredible tool that we're

seeing developed in front of our

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eyes that's growing exponentially.

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And you don't wanna miss out on that.

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Thomas Kunjappu: Absolutely.

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So let's leave it there.

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So thank you and everyone out there.

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We'll see you on the next one.

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Bye now.

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Thanks for joining us on this

episode of Future Proof HR.

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If you like the discussion, make

sure you leave us a five star

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Or share this with a friend or colleague

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See you next time as we keep our pulse on

how we can all thrive in the age on AI.