Sourcing School by RecruitingDaily

The Opportunities of AI in HR with Jenny Cotie Kangas of WhiteRock

October 27, 2023 Brian Fink, Ryan Leary, and Shally Steckerl
Sourcing School by RecruitingDaily
The Opportunities of AI in HR with Jenny Cotie Kangas of WhiteRock
Show Notes Transcript Chapter Markers

Ready to see the future of HR tech through the eyes of an expert? Jenny Cotie Kangas, Founder and Chief Solutions Architect at WhiteRock, takes us on a journey into the world of Generative AI, illuminating its potential in reshaping the recruitment industry.

The future of HR tech is here, and we're ready to embrace it. Are you?

Special mini series recorded with Oleeo at HR Tech 2023 with hosts Ryan Leary, Brian Fink, and Shally Steckerl


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Speaker 1:

Hey everybody, welcome back to the Sourcing School podcast. I'm Brian Fink, he's Ryan Leary and we are joined by the one, the only JCK. We are excited to be on the floor here, sponsored by the team at Olio, in the Olio podcasting booth. Jenny, what's going on today? How are you?

Speaker 2:

Hi everybody. This is Jenny Cody-Kangus, or JCK as the nickname Brian mentioned. I'm doing very well. It's been a great HR tech and I'm so excited to have this conversation today.

Speaker 1:

Don't knock the champagne doors. There's a champagne cart that is going past JCK as we speak right now there is champagne.

Speaker 2:

there is alcohol everywhere at this conference. My goodness, it's the last day.

Speaker 3:

They're ready to party. It's 11.44 in the AM y'all. Can I just say I love your glasses.

Speaker 2:

They are amazing. They would look like shit on me, but I love them. Yeah, no, I thank you. Fun thing, I love different glasses and I just input my prescription on to semi-optical or Zelo and you can get. I think these are like $45 with the lenses.

Speaker 1:

Really yeah, can't beat that.

Speaker 2:

The only problem is you can try these different kind of glasses out, but I ended up falling in love with these ones and now they're discontinued. So I was like I will find a way.

Speaker 1:

There's always a way, so yes, that kind of sounds like my plight when it comes to Apple accessories that are in this bright orange color over here, right, we don't like Apple, stop it. I love my Apple accessory. All right, all right.

Speaker 3:

So I don't know about you, but this fly is the last thing I've ever seen.

Speaker 1:

Oh yeah, there's a fly that's buzzing around.

Speaker 3:

It's like It'll land on your head. It'll land on your microphone.

Speaker 1:

So, jck, you are walking the floor, People are having lots of conversations with you. 30,000 foot view you make an impact in this community. What, from a 30,000 foot view? What is it that you do that brings value to everybody who's here on the floor today?

Speaker 2:

Yeah, great question, brian. So what I do? We obviously so. For those of you who are listening in, we're sitting in a booth inside of a giant, giant room that is filled with 500 different vendors that are in our space, and so what I do is I work with customers to make sure that they have the infrastructure to be able to implement these properly, because it's not necessarily about the technology, it's about how you implement it and making sure that you've got like a foundational data strategy and you're able to tell stories with numbers and that things are working the right way. And so I'm the person that comes alongside of the buyers to help them learn how to get that right.

Speaker 1:

Okay about getting it right. What are people getting right here at HR Tech? What are they getting correct, come correct, jck.

Speaker 2:

I think they're getting right to be here right, like so, having your growth mindset I mean people listening to this podcast right now right, and being able to be curious and willing to learn. I think that part is really, really important.

Speaker 1:

Oh, ry leaned into his mic and I'm like I'm going to interrupt them.

Speaker 3:

No, I was just. I'm letting you talk, I'm tired.

Speaker 1:

All right. So why are you tired man? They're passing out the drinks. They got orange juice over there.

Speaker 3:

We'll get you a little caffeine, they've got the five hour energy too.

Speaker 2:

They have literally catacorn art from us right, yeah.

Speaker 1:

We should just go grab some Energy. You talk about implementation.

Speaker 2:

Yes.

Speaker 1:

What are the vibes that you're feeling going from 2023 to 2024 in the TA space? You got any predictions?

Speaker 2:

Do you really want my predictions?

Speaker 1:

We want your predictions. Are you going to be the anti-hero?

Speaker 2:

No, I don't know what that means, but also oh wait, that's a Taylor Swift song, right?

Speaker 1:

I think so.

Speaker 2:

So for the people listening in a little bit of context. I hit my head in 2020. I remember nothing from before it, including popular culture, and so sometimes these types of situations come up and I look at Brian and like that was a Taylor Swift song. We're referenced right.

Speaker 1:

Okay, so for reference, JCK and I talk all the time right, so this is like a conversation between friends. Like, Ryan is the odd man out here, Ryan.

Speaker 3:

that's all I thought.

Speaker 1:

I didn't know if this was a Taylor Swift joke, because you know like Maddie is all about. So everybody knows my daughter. If you don't know her from the podcast, you know her from HRTX or you know her from my newsletter where I beg you for money for her school.

Speaker 3:

You know he spent $1,400 on tickets Two.

Speaker 1:

We are never ever ever talking about that together. We are never ever ever.

Speaker 2:

I love it All right. So sorry everybody for the quick like sidestep on Taylor Swift, I think there's. So to go back to your question, which is what do you think is gonna come in 20, or what's kind of?

Speaker 3:

20, 24.

Speaker 2:

I think we're about to step into a reckoning.

Speaker 1:

A reckoning.

Speaker 2:

Yeah, in a pretty big way, and so what I mean by that is Generative AI has changed the game in a lot of ways. Right, Like I'm a huge proponent of Generative AI, I'm somebody with a disability and Generative AI helps me do so much more. That's not having to like drain the batteries of like who I am, and so I'm able to go so much further and faster. So, big fan of Gen AI. However, there's a lot of technology that's coming out of the Gen AI space right now, including technology that's gonna allow you to, you know, mass apply to like 200 plus jobs with the click of a button. Our infrastructures that we have on the town acquisition standpoint, they're not ready for that, and so what I mean is these companies, probably in the next, probably three months or so, are going to be flooded with hundreds and hundreds and hundreds of thousands of applications.

Speaker 1:

That are Gen AI. That are Gen AI bonds. Yes.

Speaker 2:

And so what's gonna have to happen is these, these applicant tracking systems, the different technologies that you're using are gonna have to figure out some way to have like a digital footprint to assess whether or not this is like a bot or not a bot, right?

Speaker 3:

Like so that's gonna be a step ahead.

Speaker 2:

They're gonna have to. But, as we know, with applicant tracking systems, when we implement them and we customize them, often they are taken off a vendor roadmap and that makes them really difficult to play with right.

Speaker 1:

Oh no.

Speaker 2:

So there is gonna be. I think there's gonna be a reckoning, and if you think it's hard to go through the applications that you have today for your job, just imagine if now I got 400 applications and I'm gonna get 400,000.

Speaker 1:

Okay, so then let me come back to this Is that there's been a big theme here and over the past six months. You and I were at RecFest and there were a lot of people that were talking about the death of sourcing, and I define sourcing as finding passive talent. You're talking about an influx of active talent and active applicants, right?

Speaker 2:

100%, I am. And just to double click on the sourcing piece those of you listening it turns out humans are not one size fits all, turns out right, that's what we do in the sourcing world is being able to, like, ask right sharp questions and figure out what's needed, and then we're gonna go and try to find that needed thing out there, right? So Jenn AI today and probably for the next several years, isn't going to be able to understand the nuance of a human. It's gonna be a lot harder. And so, yes, there may eventually be certain things that aren't gonna be that Jenn AI will take over. But sourcing just going away y'all, like if you know how to find a purple, sparkly unicorn OpenAI is not gonna be able to help you find a purple, sparkly unicorn Like.

Speaker 1:

it's just not how it works Now.

Speaker 2:

that being said, sorcerers are so sorry, I'm like totally like oddest like what is it speech?

Speaker 3:

box, soap box or whatever. She's about to fire all the sorcerers in the world.

Speaker 2:

No, so sorcerers are uniquely positioned to become super users of Jenn AI because, like, honestly, like Boolean search string you guys is a prompt right and so ChatGPT does not do good, boon, they won't. No, but here's. I need to connect the dots for you here.

Speaker 1:

Okay.

Speaker 2:

So, in order to make Jenn AI work the best, I need to call out. So, at its core, sorcerers are able to understand and find people and the nuance of people right. In order to get Gen AI to work properly, you need to understand the nuance of what you're looking for. So, if I'm able to call out similar to like I need a redact, whatever right, like if I'm able to call out the hat that I need the person to wear and the lens. I want it to look through you are able to get ridiculous responses in terms of, like prompt engineering and so like I truly believe that sourceers have a massive leg up because you already understand that. Like it's the right sharp questions right that you're gonna need in order to find the right answer. So I will pause for a second. But yeah, brian looks like he has something to say.

Speaker 3:

I like it. I mean I like everything you're saying, and again I mean a couple of the products that we spoke with over the last two days. They're all saying the same thing and they're all preparing for that. I don't know that any of them have accomplished it by the look on the face.

Speaker 1:

I'm saying no. Jenny is sticking her finger in her mouth as she is going to throw up. I'm commenting everywhere. This is a visual pot. Oh, okay, I'm sorry.

Speaker 2:

So here's the thing?

Speaker 1:

I don't think that.

Speaker 2:

Jenny has now removed her glasses. Oh God and Brian knows that that's a tell for me that I'm about to say something. All right, all right, okay. There were some incredible presentations y'all yesterday, specifically about like how Jenny is gonna change the world and like all the way through.

Speaker 3:

So you're calling BS on all of this.

Speaker 2:

No, I'm not calling BS on it.

Speaker 3:

Buyer syndrome.

Speaker 2:

I am highlighting a very, very, very important flaw that exists. So what was said, just to like, connect the dots, was that, because of the growth of these gender-divine products, all of our problems are going to be solved. Right, which is cool, that's awesome. Yes, in order to like, if you have the proper data infrastructure and you can you and I know this word, data nerds right, it's my favorite four letter word. But, like, if you have the right data infrastructure, your data is clean in that lake. I can put Gen AI or something that's on there to connect the dots to that. The problem is, most of the buyers who are here don't understand how to build the proper foundation in order to get the data clean, and if we don't do that, it's garbage in, garbage out, y'all.

Speaker 1:

It doesn't matter.

Speaker 2:

It's such an important piece. If we want to help our organizations get this right, we have to start storytelling Like what does it actually look like? Yes, there is this cool, like you know, pie in the sky, we can do this. It's a mountain with, like the new world or whatever. I don't know all the hisms. I'm playing my head in drink.

Speaker 1:

Let's unpack that a little bit. Let's unpack that a little bit.

Speaker 3:

How does an organization with really just bad data, how do they start to get that prepared for this next move?

Speaker 2:

Number one step y'all is you have to have a map of your decision-making processes and your experience from high to fire. If you don't have that, you really aren't positioned to be able to leverage like AI or automation, because in order to get AI or automation right, you need to be putting it where there's friction, and if you can't assess where there's friction, that's the wrong way to do it. So step one is going to be utilize those design thinking skills to understand what the problem is and actually map it, and then to be able to ask the right, sharp questions. And, as we know, I grew up as a project manager before I hit my head. But one of the rules that we have in the project management space is, like I was saying, Scrum master. The problem that presents itself y'all is often not the problem you need to fix, and so you've got to ask the right sharp questions to figure that out and really clarify and verify that Five wise, five wise. Yes, and what Brian's referring to is like you have a situation, you ask, but why? And then you get an answer and you ask, but why? And you ask, and like it sounds silly y'all, but like this is a really important piece that we need to go through, because when resources are lean and our teams are a lot smaller and we're having to do more with less, it is imperative that we are actually working on the right things. And so, yeah, I know I'm like probably way over time, you guys, but Two minutes and 15 seconds.

Speaker 3:

You're good. Yay, yay, yay, only two minutes over, okay this has been a really impactful conversation.

Speaker 1:

I hope that people will give this a listen and that people are going to share this out, because you have laid out You've laid out what you need to do to be I mean not just what you need to do to be actionable, but what you need to do to create success in your organization. And there are a lot of buzzwords, there's a lot of junk. It is data. It is good data in good data out. It is bad data in bad data out. This is an interesting time for us in an interesting environment. We'll see what the reckoning looks like in 2024. Will you come back in 2024 and have another conversation with us.

Speaker 3:

We need to have you back on and like when we get home, let's have her back on and get a full 30 minutes.

Speaker 1:

Okay, that sounds like a plan.

Speaker 2:

Yes, and the last thing that I just want to like double-click on here not to interrupt you, brian. She's going to go to 14 minutes now you guys, the only way to solve a hard problem is to choose to begin, and you're not going to know the entire blueprint, but when you choose to begin, you're going to be able to assess what's the first right step and then, based on again on data favorite word right Like where are we drifting, where are we shifting in order to get that right? And so these things we're talking about, like how do you get work right? You got to start right. Choose to begin Amen, and it's not necessarily about having the perfect strategy. It's actually about having the perfect strategy to drift and shift your strategy when you get it wrong. And remember that getting it right is gleamed through getting it wrong y'all. So failure is the blueprint where we can gleam the blueprint for getting it right. So be intentional. Yes.

Speaker 1:

Oh, listen to that. A round of applause for JCK.

Speaker 3:

We're going to wrap this up.

Speaker 1:

We are coming to you live from the Olio podcasting booth at HRTech. Thank you so much, JCK. Jck, we will see you soon on the Sourcing School podcast. Thank you.

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