S4 E121 | CXR Podcast: Gal Almog digs into AI

Talenya's Gal Almog joins CXR to dig into AI and what impact it will likely have on talent sourcing over the next 15 years.

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Chris Hoyt, CXR 0:21
Welcome, everybody to another CareerXroads podcast, I’m excited that you’ve decided to either dial into the show or listen to us later when you’re on your treadmill or your stairmaster or doing your thing with the dog. Either way, we’re glad that you’re dialed in and giving us just a little bit of your attention today, we’ve got about 10 minutes that we’re going to talk with a certain industry, well, this guy’s been around a while I wouldn’t call him local, though, he’s not local to most of our listeners. So you may or you may not know who he is. Gal, welcome to the show.

Gal Almog, Talenya 0:51
Thank you. Thank you for having me.

Chris Hoyt, CXR 0:53
So for those who do not know who Gal Almog is Gal, why don’t you give us what I like to call and is now got to be getting famous this request and escalator pitch for what you do and sort of why the listeners should care about your opinion at all, like a little bit of background.

Gal Almog, Talenya 1:10
I’m a veteran entrepreneur who started the companies before in the last 20 years, my focus has been the recruitment technology industry. As you can see from my accent, I’m not from Texas, I’m from Tel Aviv. And Israel is the hub for a lot of technology companies, you may know. But a recruitment in general recruitment technology in particular has fascinated me. And I feel very fortunate to be an entrepreneur in this business that in addition to creating good businesses, also creating a lot of good in our world, helping people find jobs, helping companies find good talent. So I feel fortunate to be in that kind of a business. A, I started companies in the recruitment technology industry. Before my previous company is a company called pandologic. You may have heard about pandologic. It was acquired by Varitone, a couple months ago, successful journey that I had with that company, and then a successful exit. And about four years ago, I started the millennia to solve a different problem in the recruitment industry. That has to do with the sourcing of talent pandologic focused on active job seeker is scraping a programmatic advertising platform for recruitment advertising. The lane is focused on automating the sourcing process and bringing AI into that process.

Chris Hoyt, CXR 2:57
Nice well, so I’ve just I just learned this in the green room while we were kind of waiting to get started. So I’m gonna love a good heart string story. So before we kind of jump into the topic of AI and recruiting and sourcing, is it is it a true true fact that your your partner, she is a she is a recruiter, she was a recruiter, and now she’s an HR?

Gal Almog, Talenya 3:20
Absolutely. And I always like to say that I created the company to help my wife. And I was watching her doing sourcing on LinkedIn, entering keywords sifting through listings, contacting people one by one. And I felt it wasn’t a good use of her time. And she said, you know, if you know better invent some technology that can help me, you know, spend my time better. And I did that.

Chris Hoyt, CXR 3:49
Yeah, challenge accepted.

Gal Almog, Talenya 3:51

Chris Hoyt, CXR 3:52
Did you You oughta Did you automate her right out of recruiting? Is that why she went into HR?

Gal Almog, Talenya 3:58
She’s had, you know, over 20 years of recruitment experience, she she is actually the HR manager for Talenya, our company. So she she likes to focus on multiple aspects of HR. And since we’ve automated the recruitment sourcing. Everyone can source by themselves, we don’t need so much. They have a free course, in our company.

Chris Hoyt, CXR 4:24
Well, so let’s let’s talk a little bit about that vision then and how how, where you’re, you’re sort of thinking, the direction of the industry goes with from an AI standpoint, and if we can level set first, because everybody everybody says they’ve got some sort of AI in some sort of product that does some sort of automation or that is some sort of smart. So without talking about maybe Talenya specific Can you sort of give us an overview of sort of what you think what you think AI is in the recruiting space.

Gal Almog, Talenya 4:58
So a lot of people talk about about AI, and I’m sure HR professionals Data Acquisition Professional, I hear the buzzword, AI and a lot, there’s a lot of hope, but a lot of disappointment. And this is because number one, people don’t really understand what AI is. And number two, it’s difficult. You and me would look at the same resume and see different things, you cannot create a widget that would know what to do. In every case, there’s a lot of psychology, the biggest challenges are lack of data. We use primarily LinkedIn. But if you’re an engineer, more more of your information would be on sites like GitHub or StackOverflow. And you may not be even found on LinkedIn, LinkedIn is limited to three degrees of separation. So you cannot access you know, the entire talent pool of 780 million on LinkedIn. It’s dispersed, outdated. Anyone you start with that, you know, in sourcing, you’re already on a disadvantage. That’s one thing. The other challenge is the fact that you use keywords in today’s recruitment. And keywords are both inefficient and discriminatory, you’ll only find people who happen to have the right keywords on the profile. And, you know, good recruiters have developed skills and capabilities to come up with the right job title, add keyword, eliminate keyword, AI can change that completely, and do it in a more efficient, comprehensive and immediate way without spending hours. And the challenge is to bridge the gap between what recruiters have in their minds as far as the position that are hiring for and what AI can understand. And it requires an interaction between algorithm and humans, because there’s no replacement to the human mind. And no matter how good is the job description, it would never describe completely, its marketing document. So it cannot reflect in in I often see a job description. And the client says, No, but I need a person like this. And I say, it’s not in the job description. And they say, Oh, the job description is just a marketing document. It’s not reflective of you know what we need. So there’s a lot of nuances that are only in the human head. And the challenge for AI is to bridge that gap, and teach the AI what you want, what your preferences, what your priorities, and things like that. And in addition, of course, there’s the challenge of diversity, and the ability to overcome the limitation that LinkedIn as, as far as you know, not to have to look at pictures to find diverse talent, you know, there are better ways. And these are some of the challenges that AI can overcome. But the last one that I think is critical is AI can help overcome challenges of engagement with talent. Because sending messages one by one is not a very scalable way to engage with talent. But this is a situation today, the entire world, you know, as far as marketing is using automation, sales and marketing automation. It is not available for recruitment and AI has the ability to take that to a new level and automate engagement with candidates. Well,

Chris Hoyt, CXR 8:50
so gal, let me ask you, so for the sake of argument, if you’ve got a role that you’re trying to recruit for, and you’re asking the hiring manager, you’re asking the head of talent about that role. And they’re saying, Well, yeah, then we need these skills. And you’re saying they’re not in the job description. Right? How would we know that? How is it that AI? I mean, how are we training the robots to take over? Like what is the most effective way for us to sort of look at how we’re supposed to make them smarter without implementing all of our own biases in that process?

Gal Almog, Talenya 9:24
You know, I came to the conclusion that AI by itself cannot create a very high quality search, okay. For every job, you need to train the algorithm at least once. Once you’ve trained the algorithm for a particular job, AI can remember and implement it for future job. So there must be a training a start to a process and the way it’s done is by looking at candidates and giving them a thumbs up or thumbs down. And machine learning can look at the ones you’ve selected. And the one you’ve disqualified and learn from that. Okay? In some cases, it can say, I see that you’ve disqualified many candidates who did not have a particular skill. Would you like me to add that to your search, and you say yes, and that’s going to be added. But for the most part, thumbs up or thumbs down, will give you a very good way to calibrate your search. It’s not going to be 100%. Okay. And that’s one of the challenges that a lot of talent acquisition professionals are facing, because they expect the same quality of selecting each and every candidate that they want to contact, because AI will do the selection for you. It’s going to be not 100%. But the scalability is going to be so significant, you’re going to end up having more candidates to interview. So it’s, it’s it’s something between selecting them one by one to posting a job, and getting everyone who think they qualify.

Chris Hoyt, CXR 11:11
Is there anything that you see in the future from an AI standpoint, because a lot of the discussions right now, especially with this, this challenge employers are having in finding the talent at the level of experience that they’re looking for, is there anything that you see or forecast in an from an AI standpoint on potential on AI being able to identify a candidate’s potential to crush it in that role, whereas historically, they may be missing two or three skills that have have otherwise historically gotten gotten a thumbs up from from a recruiter

Gal Almog, Talenya 11:45
I’ll answer in two ways. Number one, AI has the ability to predict and add missing skills, because a lot of people have partial resumes. And especially women and minorities tend to post 20 to 30%. Less skills, AI has the ability to say, you know, I’m looking at your 90% of people, like you have this skill, you must be missing the skill, I’m going to add it to your profile. Okay, that’s one thing. The other thing AI can do, is they can look, and this may be the biggest advantage that AI can offer to the recruitment industry, think about recruitment, you’re trying to fill a job with someone who’s done exactly the same job and agreed to move from his job to your company, okay, you have to pay him more money, he may not fit. And he may not want to live, or you may be competing with 100 other companies offering the same thing. It is very difficult, very, very difficult. While in your company, there are a bunch of people who are not exactly the type of candidate you’re looking for back with two or three months of training, not only they will be as good as someone from the outside, but they will be better because they are familiar with your culture, they’ve had success in your company, and they would appreciate the opportunity of giving them a I can tell you, within your company or outside your company could fit. How do they do that? You look at career patterns, you can say, you know, according to this curry pattern, his next most likely career path is this job. Okay? Consider that person, as opposed to looking exactly for the same person that you’re trying to fill.

Chris Hoyt, CXR 13:40
That’s a beautiful thing to think that AI can begin to take on the issue of internal mobility, because we know that has wonderful ripples downstream from cost of recruitment, and hiring and DE&I all of that good stuff. But if the robots are going to decide who moves next, based on the historical moves within the organization, do we risk repeating the same moves over and over and not offering up any anybody from a different function within the organization that could still be successful in this role? And even diversify? Maybe that that function or department?

Gal Almog, Talenya 14:12
Chris, I believe so much in AI? That I think that what you just said is very possible, okay. You’re saying, if we keep moving the same people from the same position to the next position, we’re creating a pattern, okay. But a AI can look at data from different perspective and say, you know, that person doesn’t have any of the skills and experiences but based on our analysis, because of their education, and other career patterns, there may be greater risk, but you know, talk to them. And I’ll tell you, I hire data scientists straight out of school, no experience, okay. And it does take a couple of months to train them, but these young people are so brilliant, so energetic, so motivated that in a couple of months, they do a better job than if I would have hired, you know, 20 year, data scientists from a different company with more inaudible money and things like that. And I think that given the tight employment market, not only the company would start to think about these kind of internal mobilities, but they have to, they just have to, because they are not able to fill those roles. And I think it’s a blessing AI can help them in that.

Chris Hoyt, CXR 15:32
So I think I’m on the same page with you, in terms of the future of recruiting is that we, we will potentially need and let’s just pick 10 years from now, we will potentially need quite a few less, let’s say manual sourcing, entry level type of recruitment folks to sort of build those those slates up front. But let’s say I’ve got 100 recruiters today at my organization.

Gal Almog, Talenya 15:57

Chris Hoyt, CXR 15:57
And in 10 years, AI helps me reduce that to 50. B, and I’m brave. I’m all in on on gals AI theory for recruitment. But do I need to hire a different kind of talent to help my AI continue to learn? Or is it just, it’s just going to go Skynet? And it’s going to completely automate itself and just get smarter every year?

Gal Almog, Talenya 16:21
It’s a good question. And I don’t know the answer. But I’ll tell you what I think is the right answer.

Chris Hoyt, CXR 16:27
All right.

Gal Almog, Talenya 16:28
I think that what where AI would go is to look at historical data, and help the company come up with wisdom, okay. So for example, if I see that recruiters tend to hire people from a certain school, I would bring it up and put a spotlight on that and tell the company, you may want to look elsewhere, because there’s a pattern, you know, people hire people like them. And this is just one example of how we can use data to tell the company first how they hire, who they hire, and how they can change to increase diversity in the hiring. And my vision is that a recruiters will focus on interviewing people and not on sourcing people. So even though they can say, you know, thumbs up, thumbs down and train the algorithm. At the end of the day, AI will bring them interviews, and most of their time would be focused on interviewing, convincing people, onboarding new people, and the manual work that they’re doing now will be eliminated, you will have different kinds of recordings.

Chris Hoyt, CXR 17:44
Yeah, yeah. Much more of, well, you freed them up to be much more partners internally, and really focus on the engagement or the more of the human aspects, right. The the conversational aspects of recruiting.

Gal Almog, Talenya 17:55
Exactly. Yeah, exactly.

Chris Hoyt, CXR 17:57
Nice. Well, Gal, for anybody leave us from a final thoughts perspective, anybody who’s considering really looking into AI for recruitment? Is there somewhere like where would you recommend that they start? If I’m a senior recruiter, I haven’t even talked to my leaders. I just keep hearing about robots, robots robots? Is there some resource are somewhere you would recommend that they begin to do their homework out?

Gal Almog, Talenya 18:22
I know a company called Talenya.

Chris Hoyt, CXR 18:27
It’s like softball in here sometimes.

Gal Almog, Talenya 18:29
I’ll tell you, I’ll tell you what, what I do recommend, because companies need to do some research. Okay. I’m not objective. But we do have a user guide that talks about AI and recruitment from different perspective. And at least they need to know what they need to look at. When they explore AI. And that’s available on Talenya’s website. You can download it for free, and then decide in and then start your research. And then you come back to the linear

Chris Hoyt, CXR 19:01
It’s a good starting point. Gal, thank you so much. We really appreciate the time that you’ve given us today. I know you’re super busy schedule, but we’re glad you carved it out for us.

Gal Almog, Talenya 19:12
Thank you My pleasure.

Chris Hoyt, CXR 19:13
For those of you who sort of stuck with us coming up on November 23, we’re really excited Elaine Orler, who is affectionately I like to call strategy and recruiting tech thought leader and Buddy, she’s been in our space for ages. We’ve known her for years and years. We’re gonna get together and talk about what we’re thankful for. It will after all, be the week of Thanksgiving in the United States. So we’re going to talk a little bit about that. And from what I hear there might be some there might be some costumes involved. So you’re going to have to dial in live to see that and we’ll talk to you then until then we hope to see everybody online in the CXR community at CXR.works thanks very much.

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