Bennett Sung – HR Tech 2024 – AI’s Current and Future Role in HR

Connect with Bennett:

• 

Connect with David:

• • 

• david.turetsky@salary.com

Podcast Manager, Karissa Harris:

• HRDataLabs@salary.com

 

Production by Affogato Media

Resources:

• Salary.com Consulting practice
• HR Data Labs Season 8 Episode 25
• HR Data Labs Season 8 Episode 23

• “Following the money is important for HR to master . . . to build business cases for the long term.”

Announcer: 0:01

The world of business is more complex than ever. The world of human resources and compensation is also getting more complex. Welcome to the HR Data Labs podcast, your direct source for the latest trends from experts inside and outside the world of human resources. Listen as we explore the impact that compensation strategy, data and people analytics can have on your organization. This podcast is sponsored by Salary.com, your source for data technology and consulting for compensation and beyond. Now here are your hosts, David Turetsky and Dwight Brown.

 

David Turetsky: 0:38

Hello and welcome to the HR Data Labs podcast. I'm your host, David Turetsky, live at the HR Technology Show in Las Vegas, Nevada, and I have with me one of my best friends for a very long time, Bennett Sung. Bennett, how are you?

 

Bennett Sung: 0:52

I am doing well. Thank you for having me back on the podcast!

 

David Turetsky: 0:55

It is absolutely a pleasure, and especially when I get to do it in person!

 

Bennett Sung: 0:58

Right?

 

David Turetsky: 0:59

And actually see your face, your smiling face and see your your new hair color!

 

Bennett Sung: 1:04

Newest hair color, yes.

 

David Turetsky: 1:05

And it is a orangish reddish yellow,

 

Bennett Sung: 1:09

Yes

 

David Turetsky: 1:10

with gray highlights.

 

Bennett Sung: 1:13

It sure is. This is a three, it's three months old, but it's still showcasing its color.

 

David Turetsky: 1:19

Yes

 

Bennett Sung: 1:20

I don't mind the gray. Gray is great.

 

David Turetsky: 1:22

Yeah

 

Bennett Sung: 1:22

Gray is trendy. I love it.

 

David Turetsky: 1:24

It shows your maturity, right?

 

Bennett Sung: 1:26

Right

 

David Turetsky: 1:26

I'm sorry. I didn't do that. No, I

 

Bennett Sung: 1:29

Oh don't worry.

 

David Turetsky: 1:29

So what we do for every one of our guests on the HR Data Labs podcast, Bennett, what's one fun thing that no one knows about you?

 

Bennett Sung: 1:37

Ooh, or any new fun thing?

 

David Turetsky: 1:38

We need a new fun thing

 

Bennett Sung: 1:40

I've already told probably the most hilarious one fainting from from aldehyde in animal science class. That was just to bring everybody back to that, back to three years ago.

 

David Turetsky: 1:52

Yeah

 

Bennett Sung: 1:53

Well, this time, you know, I had a bit of an incident getting to HR Tech. In a context like I had. I tripped on these amazing new shoes of mine that are red.

 

David Turetsky: 2:03

Yeah, they're Pumas. They're really nice!

 

Bennett Sung: 2:06

you know, so, but I tripped over them, and I had to, like, like, brace myself for a face plant. No! yeah. And now, now I can barely shake hands.

 

David Turetsky: 2:16

So when was this?

 

Bennett Sung: 2:18

From Seattle to Las Vegas.

 

David Turetsky: 2:20

No!

 

Bennett Sung: 2:21

yeah. So I got off the train in Bay in Seattle, and boom, oh, I was on. I was on the ground. I said, Oh my goodness. What's going on here? This is not how I wanted to start my HR Tech travels. But nonetheless, it is what it is.

 

David Turetsky: 2:35

But you look okay.

 

Bennett Sung: 2:35

Yeah, I'm fine.

 

David Turetsky: 2:36

Now show me your hands. Oh yeah.

 

Bennett Sung: 2:39

Did they look bruised?

 

David Turetsky: 2:40

No, not at all. So if, for those of you don't

 

Bennett Sung: 2:45

It has been a while, and things have changed. know Bennett, Bennett's a brilliant guy. I've met him a long time ago when we were working for ADP, his company had just gotten acquired, and my company just got acquired by I mean priorities. Priorities definitely have shifted, yet at ADP, and we kind of bonded over that newness, but also we did a lot of conversations around talent management and how, you know, working in an environment of payroll and HR, and how do the same time stayed relatively the same. you get more people thinking about the world of not just at that point, applicant tracking, talent management, but also,

 

David Turetsky: 3:12

Yes

 

Bennett Sung: 3:12

Because I think when I began to kind of look, do what does that really mean in the context of business? So, right? That's been a while ago. a reflection of, you know, the since back in 2006 when we were together.

 

David Turetsky: 3:36

Right, wow

 

Bennett Sung: 3:36

You know, so many things have stayed the same, right? So many of the topics have relatively stayed the same!

 

David Turetsky: 3:42

Right

 

Bennett Sung: 3:42

Candidate matching. We're still struggling to figure why we can't figure that out, right?

 

David Turetsky: 3:47

Right

 

Bennett Sung: 3:47

And there's just a lot of small, little, small, little, mini milestones we all have to accomplish in order to get get that piece of functionality right. And I'm not sure if we ever will be happy with it anyways. So

 

David Turetsky: 4:00

Well, it's so difficult, and especially in the world now where, and we want to talk a little bit about artificial intelligence, but yeah, within the world of applicant tracking and recruiting, there's still so much complexity with where am I hiring people, who am I going to hire, and who do I actually get to talk to, given the fact that a lot of the AIs are actually filtering people out.

 

Bennett Sung: 4:19

Yeah, for sure. I mean, there's, I mean, AI is definitely helping with, you know, getting through the volumes of candidates, especially in the employer driven world we're living in today. I'm sure, you know, next year will be a candidate driven world again, and that's all that is going to be a different strategy. But nonetheless, I think AI certainly has been helping folks out in the context of, I'm getting work done for you, I'm getting work done, I'm screening. I'm looking at people. I'm not sure if they're correct, but I'm looking at people, and I'm thinking and predicting that this person should be put in your interview bucket.

 

David Turetsky: 4:53

Right

 

Bennett Sung: 4:53

And not the disposition bucket, right?

 

David Turetsky: 4:55

Right

 

Bennett Sung: 4:55

So that you know, we're going to continue to see how that continues. See how that evolves over time in terms of its accuracy.

 

David Turetsky: 5:03

Yep

 

Bennett Sung: 5:04

And you know, it's context of not making sure that decisions are not based on previous biases and such, and

 

David Turetsky: 5:12

which has been the case!

 

Bennett Sung: 5:14

which is, which is why, which is why on the recruiting side, it's very much, for me, one of the biggest hurdles and challenges going to facing recruiting technologies today. All of them are quoting AI. They're making recommendations.

 

David Turetsky: 5:29

Right

 

Bennett Sung: 5:30

You go talk to EEOC, which I have, they are very critical about decision making capabilities that are not made, that don't have a human in the loop.

 

David Turetsky: 5:40

Right, right. So, so, so, I think one of the keys there is have the artificial intelligence help create the artifacts, but have a human review them.

 

Bennett Sung: 5:50

I mean, the artifacts are still honestly kind of subjective. I mean, you look at resumes.

 

David Turetsky: 6:00

Oh, my.

 

Bennett Sung: 6:00

We have no control over the resume or the CV, however you want to talk about it.

 

David Turetsky: 6:05

Yep.

 

Bennett Sung: 6:05

You look at the the the the content piece created by recruiters and hire managers, the requisition that's flawed, primarily because there's no process of collecting it.

 

David Turetsky: 6:17

Right. So actually, a lot of that's being built by chat GPT, because managers and recruiters are, sorry recruiters, they're lazy about this.

 

Bennett Sung: 6:24

Yeah! I mean, for sure, right? You know. And then you have to think about, is it inclusive, you know? Then you have to look at the languages associated, you know, that are you being used? But more so it's the actual process of intake, right? You know, is, because the whole notion is, I as a recruiter and you as a hiring manager, really, this is our SOW to each other.

 

David Turetsky: 6:45

That's right.

 

Bennett Sung: 6:45

And if we can't agree upon this, then the first step of the process of going out there and looking at candidates and say, yes, no, yes, no, I think sometimes humans probably could do a little bit better than AI in terms of getting it right. We'll see!

 

David Turetsky: 7:01

But go back to your original point about the bias.

 

Bennett Sung: 7:03

Yeah

 

David Turetsky: 7:04

Sometimes we've not gotten it right and and what, hopefully, what we're not training these models on, are what had been happening on the past that had gotten us into trouble in the past.

 

Bennett Sung: 7:14

Oh, yeah, for sure. Yeah,

 

David Turetsky: 7:17

By the way, we're recording live at the HR technology show, and it hasn't opened yet. So you're hearing a lot of the work that's being done to get it to open. Yes, exactly. In an hour or so.

 

Unknown: 7:36

Let's go to one of the questions that we were going to ask you, which is, to me, one of the fun things about doing these kind of conversations, especially at the beginning of the HR technology show, is I think your your opinion might be changed by the time the end of the of the show happens. Maybe not too much. So one of the questions is, beyond the hype cycle, where does AI land in the HR stack right now?

 

Bennett Sung: 7:58

So interesting enough. So I've been consulting with a company called MeBeBot. Me be bot, one of the harder names to say, but still a fun name. But we did a survey of HR folks to get a pulse check on, have they made progress since 2016 when we first did the survey, on whether or not they have they're ready for AI. Well, there's a lot of things that haven't really moved the need, they haven't moved the needle forward, right?

 

David Turetsky: 8:25

Right

 

Bennett Sung: 8:25

There are obstacles in the way. Their AI adoption on the HR side, in comparison to recruiting side, is much slower, much more methodical, and it's because, you know, the chat, the one of the big ops, one of the challenges is that now IT has gotten their, they are driving in a co shared relationship with HR. They are driving the initiatives together! So they're, they're both kind of

 

David Turetsky: 8:48

good! like, you know, obviously, you know, pros and cons and, you know, having their conversations and, you know, debates about, you know, where do we want to take this? What do we want to use? You know, have we set up the processes and the policies at front like, right? Do I have an AI steering committee that's brand new? Yeah,

 

Bennett Sung: 9:09

to to a lot of things, and, you know, that's just, but it's all, it's all for good, right? It's all for ensuring that AI is treated, is done in a responsible capacity,

 

David Turetsky: 9:21

Yeah

 

Bennett Sung: 9:22

or ethically, or however you want to use it, right?

 

David Turetsky: 9:24

Right

 

Bennett Sung: 9:24

And it's like so. So I think for the most part, there are a number of things that are challenging HR in the context of moving this needle forward faster, right? First and foremost, they're not following the money. By following not following money. I mean, they are not partnering as well as they should be with their CFO.

 

David Turetsky: 9:47

Why is that?

 

Bennett Sung: 9:48

There just hasn't ever been that that kind of relationship. But the reality is, the CFO holds the purse

 

David Turetsky: 9:55

Absolutely

 

Bennett Sung: 9:55

purse strings, right? It's like, but, you know, so the things like, well, you know? So we want to invest in this technology, but it's a new line item. How am I going? What is that? What do you need from us to to, you know, get you to sign off on a business case. What's the business case? What are the what are the outcomes? And by outcomes that we don't mean how much more, what the kind of experiences? Because CFOs will not buy things based on experience. In fact, they're cutting technologies that are exclusively to experience, because there's nothing on the on the at the tail end that shows me how much revenue I've created or how much cost cutting I've been able to save, right?

 

David Turetsky: 10:34

Right, right.

 

Bennett Sung: 10:35

So following the money is important for HR to really master and build that relationship. And then you'll be able to realize when you have, when you find the tools that you're looking for, you work with, you work with CFOs to then go and really build a strict case that's going to be for the long term. Not like this is, this is not one that is going to be cut for the next year.

 

Unknown: 10:55

Sure, I would like to think about this though, there's also another side that the CFO will be interested in which is the risk side.

 

Bennett Sung: 11:01

yeah.

 

David Turetsky: 11:02

And what are the risks to not only the adoption, but what are the risks to non adoption,

 

Bennett Sung: 11:08

right!

 

David Turetsky: 11:08

Because so many of their competitors might be adopting AI tools, an AI stack

 

Bennett Sung: 11:14

yeah.

 

David Turetsky: 11:14

But, but also, we've seen a lot of AI in the consumer world.

 

Bennett Sung: 11:18

Yeah

 

David Turetsky: 11:18

ChatGPT 4.0 is available for people to kind of

 

Bennett Sung: 11:18

for sure sign up!

 

David Turetsky: 11:23

What happens if people do it and they expose data, I'll be talking about this a lot, and it's not been done with IT's knowledge or involvement, and so it's being done rogue?

 

Bennett Sung: 11:35

Yeah, I think the reality is we all we already know that It's already being done. So you have to just realize that it's a good it's actually a really good thing that individuals are using AI for their for purposes of just getting themselves acclimated to what, what is my what's the day in the life of what I'm doing today? Going to how is that going to change? Until they start experimenting, they will really, not really feel the impact. And that's one of the major benefits and kind of missions of AI. At this stage, we're about changing the behaviors of work, right?

 

David Turetsky: 12:09

Right

 

Bennett Sung: 12:10

And if we like, so, so I we're encouraging folks to experiment, but we have to experiment with with guardrails. Well, they have to develop these skills, because they have to!

 

David Turetsky: 12:20

if not, it's going to overtake what they're doing, and everybody else is going to be doing it, and they're going to be like, Well, why didn't we invest in AI?

 

Bennett Sung: 12:29

I mean, we're seeing that. And I think there's also the reality is, like, you have to understand the problems you're trying to solve. This is not like you mean, if you keep on layering technology on technology, and they're not really solving any real, real issues. Then there's, then again, we're not going to when it comes to the renewal and they ask for the outcome that's never going to be very clear.

 

Unknown: 12:52

Let's look at a consumer technology in the world of AI that everybody adopts. And I'm not talking about Siri or Alexa. I'm talking about like, a Grammarly like or or think about, you're just a spell checker that, or the grammar checker that you use in Word or whatever.

 

Bennett Sung: 13:05

For sure,

 

David Turetsky: 13:06

There are so many people that think that a Grammarly is a, what a lazy person uses it, or someone who's uneducated, no, no. A lot of people use it so that they, they, you know, what's the right then versus than, yeah, or then or right? What's the right? You know, spelling of right or higher, or

 

Bennett Sung: 13:27

Sure, the context

 

David Turetsky: 13:28

Yeah, I mean, and getting it right in a business context is so important!

 

Bennett Sung: 13:33

Exactly

 

David Turetsky: 13:33

But, but that's a consumer version of an AI tool,

 

Bennett Sung: 13:36

yes,

 

David Turetsky: 13:37

that people have just kind of built into a lot of tools, whether it's making emails work or,

 

Bennett Sung: 13:43

yeah, I mean, it's all anything that is content generation is probably going to have a Grammarly, a Grammarly, like functionality built into it, without you maybe even knowing!

 

David Turetsky: 13:53

Exactly!

 

Bennett Sung: 13:53

And so a lot of times, there's a lot of tools that we're probably using that we don't ever realize.

 

David Turetsky: 13:58

Right

 

Bennett Sung: 13:58

Like, you know, we'll take a step back into the days of Virtual Edge.

 

David Turetsky: 14:04

That was one of those technologies that got bought by ADP, that brought Bennett to ADP.

 

Bennett Sung: 14:09

Yeah, but what folks didn't know is that it had a built in candidate matching tool that was using a machine learning, natural logic processing, you know, algorithm called ingenuine back in the day. It was like a desk, it was like a premise based, like machine learning tool. It wasn't even put into the cloud yet until, until Virtual Edge got a hold of it. But the reality is, not many folks knew about that in the days and and so, you know, it's we, it's been around, let's just be real. I mean, AI has been embedded in so many different things. I mean, you talk about, you know, Grammarly being lazy isn't a calculator the same way? Like, Excel, like my mathematical capability of

 

David Turetsky: 14:46

Oh, yeah! comprehending mathematical equations have definitely slowed down. Oh, sure, right.

 

Bennett Sung: 14:55

But nonetheless, it's the we know in the back of our heads. It's made us more productive.

 

David Turetsky: 15:00

Yep, right.

 

Bennett Sung: 15:01

We can get to answers faster.

 

David Turetsky: 15:02

absolutely, right.

 

Bennett Sung: 15:03

But when it comes down to investments in technology, and we're asking for lots of new money, like, sometimes efficiencies and experiences will not cut it, like we have to, again, not to use the term phrase follow the money. The reality is, CFOs are looking, how much are you gonna rate, how much more revenue you're gonna give me, or how much money are you gonna reduce?

 

David Turetsky: 15:27

Right

 

Bennett Sung: 15:27

Those are the two things, that's all they care about. So so you have to have your you have to have that business case tight and really focus

 

David Turetsky: 15:34

Absolutely

 

Bennett Sung: 15:35

on the on those two line line items. So

 

David Turetsky: 15:38

Absolutely

 

Announcer: 15:41

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David Turetsky: 15:50

I want to take us on a little bit different directions. This is, this is a little bit selfish for me, but, How does it change the game in recruiting but you've been in the recruiting space for a long

 

Bennett Sung: 15:56

Yeah. when now they have to disclose the pay range when they're in time, and now we're seeing pay transparency. I have to take you this direction. Pay transparency is really huge in a lot of different states, and it's and it's going to be huge across many organizations who are using the, let's call it the highest common denominator, whatever the state is that has the most rigorous regulations. the midst of the requisition and in that candidate cycle? Yeah. I mean, I think in the long term, it's leveling the playing field, right? It's giving it's going to make candidates, you know, maybe it's going to be a vehicle for screening candidates out or in,

 

David Turetsky: 16:42

Absolutely

 

Bennett Sung: 16:43

right? Because they, you know, they have their own personal expectations of kind of money that they want to make, right?

 

David Turetsky: 16:49

Right

 

Bennett Sung: 16:49

So I do feel, from a recruiting perspective, it's, it can be used as a absolute attraction, right, you know, and, and the reality is, I think it also reflects culture. Transparency is one of those, one of those cultural elements that employees value, you know, and so I think it's, you know, it's also then aligning, like, if it is something you really put forth and prioritize, and it's gonna be reflected in your company's entire, entire way of communicating. So, yeah, so that those are the things that when I look at pay transparency, or anything that's transparent, AI, you know, AI is a it's all about transparency! It's nothing. It's not about hiding anything, right, right? It's only going to get it's only going to get more granular and more visible and more accessible.

 

David Turetsky: 17:37

Absolutely. When I think about transparency in the world of recruiting, I also think about, what are the programs and how do I educate the candidate and the employee as to, what is it the value proposition is that they're working here for what are the rewards there they have the opportunity to get?

 

Bennett Sung: 17:54

Right

 

David Turetsky: 17:54

And also making a more mature relationship between the employer and the employee, because now you're trusting your managers, all the stakeholders in this. You're trusting them to make the best business decisions for the company

 

Bennett Sung: 18:07

totally Yeah, I, you know, I think one of the things that

 

David Turetsky: 18:08

and the person. candidates and companies don't prioritize, or it's very rare to see they focus exclusively on salary, and never really, I never really bring in all of the other influencers of compensation. Benefits, how much they put towards your benefit programs or contributions to your 401k, all of these things that don't what they call total compensation statements. Yeah

 

Bennett Sung: 18:35

Those need to be. Those are amazing recruiting tools, if you you know when you put it into, when you put it into, put it into play. I just don't see a lot of folks, they say, Here's your here's your offer and salary and and here's how many days you get off, right? I just don't feel like I have a full understanding of, like, what I'm what value I I'm getting from the company, right? I know what I could bring to them, but I really don't feel like I have a good sense of the end to end, understanding of how much they're investing in me.

 

David Turetsky: 19:05

And I think once we get beyond the regulations in pay transparency, what you're going to start to see is that more companies are going to be much more open about their other benefits and other pay pay elements and things like that, because the regulations that exist only talk about base pay. Why? Because it's so complex in the world of everything else.

 

Bennett Sung: 19:25

Oh gosh, everything

 

David Turetsky: 19:25

You know, what is an incentive? What's a sales incentive versus a commission versus just a short or long term incentive?

 

Bennett Sung: 19:31

Right

 

David Turetsky: 19:31

Because those things are so variable by company, by culture, as you mentioned before, that the a lot of the regulators, and one of the regulators I was speaking to last week said, Look, we thought about doing beyond base pay, but we really couldn't get what a good definition of those other things are. So to me, what's going to happen is, once we get beyond the regulations, companies are going to use their culture,

 

Bennett Sung: 19:52

yeah,

 

David Turetsky: 19:53

and they're going to and they're going to say, well, our culture is a total compensation culture, and then people are going to learn more from the beginning.

 

Bennett Sung: 20:00

Yeah, you know, I also just feel like it's an education for candidates and employees. It's like, let me tell you what, let me help you understand the total investment. And that's as good. Once I hear that, I think them, they're going to be very like, they're going to embrace a lot of the things that they're talking about, and they're going to like, really revalue the organization that they joined, and it's going to give them more motivation and and, you know, and they're going to feel more, you know, belonged in the organization and valued and such so

 

David Turetsky: 20:29

and now, and that will be a better tool for retention than trying to change their pay or giving more of something.

 

Bennett Sung: 20:37

Right. I mean, you know, I think, I think there's some folks that no matter what it's always going to be the base pay and the salary, and that's all they can look at, right? I mean,

 

David Turetsky: 20:44

right.

 

Bennett Sung: 20:45

And I think there's a good part of

 

David Turetsky: 20:46

pay the bills

 

Bennett Sung: 20:47

they have to pay the bills, right? I gotta keep the lights on!

 

David Turetsky: 20:50

Right

 

Bennett Sung: 20:50

But, but, you know, I think over time, hopefully as more folks do like start to kind of think about their large, the larger picture in life, then they're going to realize the importance of all of those additional pay elements.

 

David Turetsky: 21:03

Absolutely. Hey, are you listening to this and thinking to yourself, Man, I wish I could talk to David about this. Well, you're in luck. We have a special offer for listeners of the HR Data Labs podcast, a free half hour call with me about any of the topics we cover on the podcast or whatever is on your mind. Go to salary.com/hrdlconsulting to schedule your free 30 minute call today. So let's talk beyond transparency now. Let's go back to our list of questions and get one last one, which I think a lot of people are thinking about, is 2025 the year that we see AI break into HR in a major way? I know you have an opinion on this.

 

Bennett Sung: 21:47

Um, we're gonna wait another year. It's gonna be 2026 I believe.

 

David Turetsky: 21:51

So you think 2026 will be the year that HR really adopts AI in a major way?

 

Bennett Sung: 21:57

In a, in a, in a more in a scalable way.

 

David Turetsky: 22:01

Okay,

 

Bennett Sung: 22:01

We're still asked there's, there's way too many organizations who haven't even done basic things around using AI! Like again, I'll kind of reflect back on MeBeBot, which does AI employee support. There are 24 digital HR generalists. Who doesn't like, what organization HR people ops teams want to answer repetitive questions every day?

 

David Turetsky: 22:25

None of them. They hate it.

 

Bennett Sung: 22:26

They hate it! But

 

David Turetsky: 22:27

slows everything else down

 

Bennett Sung: 22:28

But yet no investment. So there's kind of this like double edged sword, of like, do more with less, yet they never get the investment to actually augment the team to help do more with less, in terms of, like, the overall head count, right? So it feels so for me, I feel like there's still a big stride away. There's a lot of cool things happening here at HR tech!

 

David Turetsky: 22:52

Oh yeah!

 

Bennett Sung: 22:52

Right? I mean, there's a lot of innovation, but so much, like many, like a lot of things, it's all about timing. It comes down to time.

 

David Turetsky: 23:01

Last year we saw a lot of hype cycle here at HR tech around AI, this year is no exception.

 

Bennett Sung: 23:08

Yeah, we're still in the delusional stage.

 

David Turetsky: 23:10

Oh my gosh, yes.

 

Bennett Sung: 23:11

Delon, delusional. We just don't because what, what we don't see is there's not enough, like there's not enough ability to play with the technology. So the AI, the difference between AI and applicant tracking system is, in the case of AI, you have to vet like, is it doing the job as it's designed? So, which means you have to get access to that AI algorithm, and you have to play with it.

 

David Turetsky: 23:38

That's right.

 

Bennett Sung: 23:40

between traditional software and what we're seeing today in this AI software. And yeah, it is definitely kind of flipping or changing the dynamic of how the solution providers are actually selling.

 

Unknown: 24:02

well, you have to make sure that decisions it's making would be the same decisions you would have wanted it to make!

 

Bennett Sung: 24:07

No, exactly. No.

 

David Turetsky: 24:08

At scale!

 

Bennett Sung: 24:09

And that's what, and that's the hope. That is why, also the solution providers are going to be pressured to provide transparency on how the algorithm works, right? Which, which? I think a lot of folks feel like, oh, that's, that's like, secret sauce, yeah, I can't give that away! Well, you're not gonna have much choice, because you're gonna have legislation

 

David Turetsky: 24:31

Exactly.

 

Bennett Sung: 24:31

Legislation is gonna tell you. You gotta expose this all

 

David Turetsky: 24:33

Absolutely.

 

Bennett Sung: 24:34

You cannot hide. This cannot be hidden.

 

David Turetsky: 24:36

Well, if you don't have it through legislation, you're gonna have it through lawsuits. So,

 

Bennett Sung: 24:41

right? Do you want reputation hurdle? You want to like we already see in the consumer side?

 

David Turetsky: 24:46

Yeah, right.

 

Bennett Sung: 24:47

I mean, the consumer side just saw Air Canada get through, go through a lawsuit because their chat bot was delusional about bereavement travel policies.

 

David Turetsky: 24:58

Yes, I heard

 

Bennett Sung: 24:58

right? And then you hear the same thing happening in, I think, New York, New York City there are, they're they're giving information, wrong information about everything, because their chat bot is ingesting wrong information, outdated information. So,

 

David Turetsky: 25:11

yeah,

 

Bennett Sung: 25:12

the reality is, we ought to hold everybody accountable. You got, but you also, you realize that you have to understand, again, what are the problems you're solving? How would you go about solving that? And it's no more different from the days of assessments, right?

 

David Turetsky: 25:24

Yeah, of course.

 

Bennett Sung: 25:24

Assessments were one of those tools, early AI tools that were done by, on paper,

 

David Turetsky: 25:28

yeah,

 

Bennett Sung: 25:29

and but nobody they had to provide the evidence and the receipts to to defend what, what potentially could be a lawsuit or a reputation issue.

 

David Turetsky: 25:38

Well, we also saw WorkDay.

 

Bennett Sung: 25:41

We're still, we're, we're waiting for that judgment to happen, right? We kind of, it's been exposed. It's nothing secretive, but now it's going to be in, you know, who's accountable

 

David Turetsky: 25:51

Right

 

Bennett Sung: 25:52

for the AI, the algorithm itself. I think this again. This is history repeating itself. It comes full circle like we're we're here again, 20 years later, 10 years later, still talking about the same things, maybe in a slightly different context, but but the ramifications and the thought process is all the same.

 

Unknown: 26:12

but I think you mentioned before, transparency helps provide that layer of trust,

 

Bennett Sung: 26:18

yeah,

 

David Turetsky: 26:19

whether it's talking about a chat bot, Whether it's talking about an AI assessment of a candidate. And why did you choose this one over that one? And why did you choose to, you know, let this one go from the process or pay transparency or whatever, yeah, treating people with respect and providing them the insight to understand why a decision was made or how it

 

Bennett Sung: 26:37

Everybody wants an answer

 

David Turetsky: 26:38

It has to and have to. I mean, we'll get legislated, or we'll get a lawsuit.

 

Bennett Sung: 26:42

you know, and or we're just going to be where we are today, with frustrated employees and candidates, where, you know, it's like, Why didn't, why didn't you choose me? Well, you can't really say, I already, like, there are these, there is these communication like, kind of restrictions about what you can say, What you cannot say. It's like, you know, let's, oh, we have to open this up! Like there is no reason why you couldn't tell somebody they were not chosen for this particular reason. The problem is that they actually, and probably the AI doesn't actually know the reason.

 

David Turetsky: 27:11

Right. They just made it.

 

Bennett Sung: 27:13

They probably just made it up

 

Unknown: 27:15

Well, and for those of us who have gone through the process of trying to apply for a job,

 

Bennett Sung: 27:19

oh gosh, yeah

 

David Turetsky: 27:20

and getting an email back five seconds after you hit submit, that said, thank you very much. You've got really great experience, but we've gone on with other candidates who are better suited than you, bullshit!

 

Bennett Sung: 27:31

right, right? What they probably forgot to do is close the requisition. That is going to be my guess, that the requisition has forgot to be closed. What they're saying is, ooh, we've got a disposition from these people, same way, and this is how we're gonna do it. We're gonna give them as the most generic email that you can possibly exist.

 

David Turetsky: 27:49

But doesn't that? I mean, talk about reputational risk there though, Bennett, I mean, isn't that, like, really embarrassing?

 

Bennett Sung: 27:55

It's embarrassing. But you know what, who's talking about it? Like, nope. Like, you'll get a few of these naysayers on TikTok.

 

David Turetsky: 28:02

Yeah,

 

Bennett Sung: 28:02

we've heard them all,

 

David Turetsky: 28:03

yes,

 

Bennett Sung: 28:03

right? I mean, they're, some of them are very, very like, self promotional and will put themselves out there saying, Oh, my goodness, can you believe what just happened to me?

 

David Turetsky: 28:11

Right?

 

Bennett Sung: 28:12

Versus, you know, but most people just, you know, they're accustomed to it. They're just like, okay,

 

David Turetsky: 28:17

yeah, right.

 

Bennett Sung: 28:18

There's not, I mean, there's nothing else I can do about it, right?

 

David Turetsky: 28:21

Right

 

Bennett Sung: 28:21

I mean, I can call them. Nobody answers the phone. Nobody even responds to emails, right? So,

 

David Turetsky: 28:26

Oh there's, there's no phone number. You can't, you can't call a recruiter and say,

 

Bennett Sung: 28:29

I'm gonna find a way to say

 

David Turetsky: 28:30

why?

 

Bennett Sung: 28:31

I'm gonna figure out a way to reach the recruiter

 

David Turetsky: 28:32

Why didn't you choose me? I'm the best candidate!

 

Bennett Sung: 28:35

exactly, you know. So, I mean, does? I mean it's just, you know, it's a vicious cycle of things that there's, like legacy practices that are still in play that just have to be kind of like, what, let's, let's find a way to tell people why they didn't get the job, why they were, why, what, why their compensation is where it's at

 

David Turetsky: 28:53

right, right,

 

Bennett Sung: 28:54

or why the answers to these questions are the way they are at right? So it's, it's all comes down to again, changing the changing the changing the behavior, to change the culture, to reflect and change and get different outcomes.

 

David Turetsky: 29:08

Absolutely. And let's just say this, because I did crap on recruiters before, and I apologize, I wasn't calling them lazy. I was joking. But recruiters have a tough job, especially these days, trying to find the best candidates in a very, very big sea, and these tools are trying to help the recruiter get the best person, because it's about their reputation. It's about the recruiter's reputation too!

 

Bennett Sung: 29:32

equally as that, yeah, for sure.

 

David Turetsky: 29:34

And they're looking for these technologies to be able to make their lives a little bit more livable,

 

Bennett Sung: 29:42

yeah,

 

David Turetsky: 29:42

to be able to do that,

 

Bennett Sung: 29:43

I figured, I think some of the technology, you know, at the end of the day, you have to look at the people process and and people process and technology tools, right? So, yeah, so the people are the people is not the issue. Usually, the process I could be improved a little bit. The technologies are the ones that you know, have much further to go, because expectations are just great.

 

David Turetsky: 30:03

Oh, yeah,

 

Bennett Sung: 30:04

right? It's like, I just don't want you to tell me exact the exact match will now also expand that exact match.

 

David Turetsky: 30:10

Yeah,

 

Bennett Sung: 30:10

do who potentially could do this? Like, there should be tiers of candidates in your pool that you until you talk to them and talk to them, you'll never be able to get a full sense of whether or not they'll be a good fit.

 

David Turetsky: 30:22

That's right

 

Bennett Sung: 30:23

fit into the organization, the role the team, right? So, so at the end of the day, some of the technologies have to understand, like, how do I build a pool of candidates that are based on potential? oh. I know!

 

David Turetsky: 30:32

Right? Well, and God knows, we also need succession plans, right? Oh, and so somebody moves up. Well, yeah, people leave, People go,

 

Bennett Sung: 30:43

yes,

 

David Turetsky: 30:44

and then, and actually, that's a really important thing. People are gonna be going a lot more now, because the bubble of baby boomers, the people in my generation, you know, Gen X, Gen X, we're gonna be retiring!

 

Bennett Sung: 30:55

Yeah,

 

David Turetsky: 30:55

I mean, I'm 57 so I got, I got at least 20 more years

 

Bennett Sung: 30:58

right? We'll be doing 20 more years of podcasting

 

David Turetsky: 31:01

yeah, I'll be talking to Bennett in like 2037

 

Bennett Sung: 31:06

Is it still gonna still be in the same facility?

 

David Turetsky: 31:09

The HR Tech show will still be here in Vegas.

 

Bennett Sung: 31:11

It will, it will never go away.

 

David Turetsky: 31:13

Never! But, but, I mean, seriously though there's gonna be this demographic bubble that is leaving, and there are gonna be a lot of holes left in organizations.

 

Bennett Sung: 31:23

Yeah.

 

David Turetsky: 31:23

I mean, look at recruitment, retirement statistics are going to through the roof soon and and the recruiters job is going to be not just about filling today, but also filling tomorrow.

 

Bennett Sung: 31:32

Yeah. I mean, I think this is why organizations need to really get a handle on retention, right? Because the reality is, I am it's like retention that you can control, right? And so, because the the the it's just recruiting and retention are the same coin, but on the opposite sides.

 

David Turetsky: 31:50

Absolutely.

 

Bennett Sung: 31:51

So we need to continue, you know when, when retention is high, recruiters are just strapped to refill seats

 

David Turetsky: 31:58

Absolutely

 

Bennett Sung: 31:59

versus refilling for the future,

 

David Turetsky: 32:01

Right

 

Bennett Sung: 32:01

So, so we got to help recruiters. We all have to help each other by really addressing being rigorous on retention, so that recruiters can actually recruit for the future, recruit to to fill, find the folks to be able to come in to support or replay or so, you know, replace the the the retirements that are are going to happen in droves!

 

David Turetsky: 32:24

absolutely.

 

Bennett Sung: 32:24

And they need skills. They need experiences. And so organizations have to figure out what, how do I get these individuals the experiences that they need?

 

David Turetsky: 32:35

Yep,

 

Bennett Sung: 32:35

right? And that's not so much saying they need technical skills. Sometimes it's just, it's just, they just need the experiences of being in leadership, the experiences and doing specific types of projects.

 

David Turetsky: 32:44

or mentorship too!

 

Bennett Sung: 32:45

Mentorship!

 

David Turetsky: 32:46

Being able to do it the right way, not just being able to do it.

 

Bennett Sung: 32:48

Yeah, exactly. So,

 

David Turetsky: 32:51

so we're gonna be talking about this for another 20 years. So next, the next 20 years, we're gonna talk about how AI took over the world.

 

Bennett Sung: 32:57

Yeah, took over the world. But you know, what's also interesting is this new genre of chat bot called AI agent.

 

David Turetsky: 33:05

Yes,

 

Bennett Sung: 33:06

We've heard about it from WorkDay, Salesforce and such, right? There's all these agents coming about. What's really exciting about that is that it's really going to change. It's really going to pro this version of AI that's currently being pushed out is going to be able to be proactive in seeing the areas of gaps in organizations, organizational systems, right, to then fill it, figure out how to get them back in order, right? So, which is that one of the hardest things, which is, you know, why a lot of companies have struggled with their you know, the HR tech stacks, is that they're so kind of non integrated data is all, kind of all over the place, and so it's very hard for them to realize, oh my goodness, this I have all these gaps in compliance because people moved, or we went from remote work to you better get your get back into the office, folks, which means it's going to have a trickle down effect on taxes, so and all sorts of other things. But no, no.

 

David Turetsky: 34:03

So what you're talking about agents are, these are little AI bots that that serve a specific purpose. They do a specific job, and they're trained on one thing,

 

Bennett Sung: 34:12

yeah,

 

David Turetsky: 34:13

and they fill that gap. Or it may be, it may be what someone used to do, or it may be something completely new.

 

Bennett Sung: 34:20

It's probably somewhat somewhere in between. It's because, I mean, anybody, if we had the time and the time, enough, more time, and, you know, to be able to go into our systems and figure out the data, and then look at it and then realize, oh, here are the 20 compliance gaps that we have right now, and here's a list of things that we need to do to fix them all that's very routine. Those are all routine things that can be nicely performed by an AI agent.

 

David Turetsky: 34:46

Sure

 

Bennett Sung: 34:46

Right? And so, so, so a lot of times the non compliance things, because our systems are just out of order, right? right Because they're missing something. They're missing things. They're missing they're not talking to each other, they're missing data points, all sorts of things. And so, so we have, it's, I think it's the AI agent is a great way to maybe scale the fixing of a lot of systems, because the AI agent can't be really, you know, do its like true, automatic automation, until they get the data straight.

 

Unknown: 35:16

So, so what you're saying is, is that we need another layer to help fix the data, and then things will be okay?

 

Bennett Sung: 35:24

I think it's a good, it's a good, yeah, it's not a it's not a patch, but it's a good thing that it's a good starting point, because I don't think people know where to do instead of, like, starting from ground zero and implementing new systems and importing all this data, it's like, Okay, I think we can, we can fix existing data through these AI agents, and you really get the actual integrity of the data in a in the in the way that we need it to be so that we can now just move on from that, and then look at other AI tools to be able to layer on top.

 

David Turetsky: 35:57

And those, those agents don't stop. They continue doing their job, refining, refining, refining,

 

Bennett Sung: 36:03

Always refining, and that is, that is a job in itself!

 

David Turetsky: 36:06

Right

 

Bennett Sung: 36:07

That's worth, it's priceless in my books!

 

Unknown: 36:10

Well, and since it's an AI, it's probably relatively inexpensive compared to people that you would have been paying for doing that.

 

Bennett Sung: 36:16

Yeah, exactly,

 

David Turetsky: 36:17

And they'd be bored out of their freaking brains!

 

Bennett Sung: 36:19

Yeah. Talk about things, probably some jobs that will cause them to want to leave,

 

David Turetsky: 36:24

yes,

 

Bennett Sung: 36:24

right? Unless they really, I don't really think the most obsessed data person would would want to stay for that kind of job.

 

David Turetsky: 36:32

Nope!

 

Bennett Sung: 36:33

you know?

 

David Turetsky: 36:33

nope. I think you're right.

 

Bennett Sung: 36:35

But that's kind of, that's kind of exciting part of like, where AI is, where AI is today, that compared to last year, like, I mean, these are just this, all of this AI agent conversation, and we're seeing it in real life, is, is really kind of another layer of vision, and

 

David Turetsky: 36:51

it's a refinement.

 

Bennett Sung: 36:52

It's a refinement,

 

David Turetsky: 36:52

yeah,

 

Bennett Sung: 36:53

and I think it's also going to help refine the employee, the employee engagement. So when you think about, remember the days of Employee Self Service Portal?

 

David Turetsky: 37:00

Oh, sure!

 

Bennett Sung: 37:00

ESS?

 

David Turetsky: 37:01

yeah. Well, well, they're still here, but,

 

Bennett Sung: 37:03

Yeah, they're going to get replaced. They're going to be replaced by these, chat, these AI agents for employees.

 

David Turetsky: 37:08

So the AI agent is going to contact the employees and say, Hey, have you updated your w4 in a long time?

 

Bennett Sung: 37:14

It's going to it's going to enable them to go in there and say, Tell me how. Tell me I need to fill out my expense report. Well, this is how you do it, and I'm gonna lead you through. And don't worry, you don't have to log into concur. You don't have to log into expendify. We're gonna work

 

David Turetsky: 37:28

Here's an expense that we found on your Amex. Give me the did you take a picture of the receipt?

 

Bennett Sung: 37:34

Yep.

 

David Turetsky: 37:34

If you did, right? Send it to me.

 

Bennett Sung: 37:36

Yeah, yeah.

 

David Turetsky: 37:37

Send it to me at this address. Yeah.

 

Bennett Sung: 37:39

So it's really gonna, you know when, because when you pull back the IT applications that is being supporting organizations. It's, it's astounding,

 

David Turetsky: 37:49

Yeah

 

Bennett Sung: 37:50

right? There are some companies that have 600 employees and have 600 applications. It's like, application, it's, it's suffocation,

 

David Turetsky: 37:59

Yes

 

Bennett Sung: 38:00

of applications and like, these are applications, like, maybe once a year I use it?

 

David Turetsky: 38:04

yeah, right. It's like, who's the expert in

 

Bennett Sung: 38:06

AI agent, hey, help me figure out how to use this? this one tool that I do once a year called benefits enrollment!

 

David Turetsky: 38:15

Oh yeah.

 

Bennett Sung: 38:17

So, you know, I mean, there's some exciting things coming down when it looks, when you look at like trying to stream, simplify the simplify the employee engagement in these technologies, and then also, most importantly, really helping leadership and operations teams really get the things that they need to get done so that they can focus so not to so they can focus on things that you know, maybe move their their career for it, or help bring in new, new solutions to address other

 

David Turetsky: 38:45

scalability. It provides them a scalability that they wouldn't have had, because they have to call every employee to make sure that they're doing their benefit enrollment. Well, I said, train the bot to do it, and then

 

Bennett Sung: 38:57

Bot keep reminding these folks, go into the system. Oh, who hasn't done it? Get send them another reminder. Oh, you need help? We are, yeah,

 

David Turetsky: 39:04

let me help you!

 

Bennett Sung: 39:05

Recommend. I can recommend you something your dependents change? No. Next step now, yeah. So exciting things. I mean, that's why they're calling, at least in the healthcare world, they've called this digital front door. The digital front door to employee engagement, which just enables organizations to not to still have all these disparate systems in the back back office, but really could provide a seamless, one, one user interface to the employee, which is really kind of the what employees crave, because it's a consumer, it's a consumer approach.

 

David Turetsky: 39:36

That's right.

 

Bennett Sung: 39:36

right?

 

David Turetsky: 39:37

That's right. Well Bennett, I think we could talk about this forever.

 

Bennett Sung: 39:48

Oh yeah, give me a couple more hours.

 

David Turetsky: 39:52

But I know, but I know the show is going to start soon.

 

Bennett Sung: 39:54

Is it really?

 

David Turetsky: 39:55

Yes!

 

Bennett Sung: 39:56

How long have we been here?

 

David Turetsky: 39:57

Well, we've been doing this now for 38 minutes.

 

Bennett Sung: 39:59

There we go!

 

David Turetsky: 40:00

Isn't that before, actually 39 now!

 

Bennett Sung: 40:01

right?

 

David Turetsky: 40:02

Bennett, thank you so much for your insights. It's such a pleasure to talk to you.

 

Bennett Sung: 40:06

Always!

 

David Turetsky: 40:07

Thank you and take care and stay safe.

 

Announcer: 40:10

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