Summary
Recruitment today is broken. Businesses are grappling with challenges like misalignment between hiring and business goals, overburdened recruiters, and poor candidate communication.
These inefficiencies are costly. According to HBR, the wrong hire can cost a company 5-7 times the employee’s annual salary when considering hiring, training, and lost productivity. Additionally, a study by Glassdoor found that a single job opening costs companies $4,129 on average, with costs increasing the longer a position remains unfilled.
In the first episode of The Peoplebox AI Talk, Abhinav Chugh, CEO and Co-founder at Peoplebox, sits down with Suzanne Salzberg, a veteran talent leader with over three decades of experience at leading tech companies like Highspot and TextNow.
Suzanne discusses how AI can streamline processes, from creating unbiased job descriptions to improving candidate communication and making data-driven hiring decisions.
Full Transcript
Abhinav (00:00)
If there’s one thing everyone is speaking about today, it’s AI. It’s going to disrupt every aspect of our professional lives. And some may say it has already started. So what will be its impact on the future of work, especially how we hire, develop, and retain our most valuable asset, People
and which part of the employee life cycle from hiring to retirement is going to see a biggest change What does it mean for the companies and HR? Hi everyone. I’m Abhinav, and welcome to the new season of our podcast, Peoplebox AI Talk, where we invite incredible leaders to go deep into the fascinating intersection of talent and AI. Today, I’m delighted to have Suzanne Salzberg on the show
Suzanne comes with over three decades of experience in the talent space. She has been the head of talent for big tech companies like Highspot and TextNow, and she’s now also a visiting lecturer at the University of
Welcome to the show, Suzanne.
Suzanne Salzberg (01:00)
Thank you, I’m happy to be here.
Abhinav (01:02)
Suzanne, you have been a talent leader for some of the most high tech companies. Let’s start with speaking about the disruption of AI in the talent space. Where do you see its biggest impact in the employee life cycle?
Suzanne Salzberg (01:16)
Well, I can, I can focus on the candidate’s life cycle in the talent acquisition you know context. I really think the, the biggest impact is going to become, honestly from the minute they read the job description because I think I see AI really helping to create complete, unbiased, easy to understand job descriptions. and it’ll also help hiring managers because one of the biggest pain points for talent teams is waiting for that job description.
The next big impact would be how fast a candidate hears back in the process, whether it means they applied and they get a response or if they’re in first, second, third, fourth interviews getting a response because I talk to a lot of candidates every day. And one of the biggest grievances from candidates is that they’re being ghosted.
And then I think the other major impact will be is how recruiting softwares are actually using AI on their backend and taking some of that load off of talent teams.
Abhinav (02:20)
That’s actually so well said. You’ve been in this industry for over three decades. Where do you believe that recruitment is most broken today and craving for AI to fix?
Suzanne Salzberg (02:24)
Right. Well, I feel like it’s changed, but I feel like right now where it is most broken is because recruiting teams have become so much leaner. The hiring is slowed. So full teams got laid off or there’s one recruiter left. And so those small teams have so, you know time management is a huge problem because now they’re doing four jobs. They’re the recruiting coordinator. They’re the travel coordinator. They’re looking at resumes. They’re doing the interviews. And so it’s almost impossible for them to go through a thousand resumes that they’re getting in a day because they’re also doing, I was talking to a previous recruiter that I worked with and she said that she was, you know, a CMO was coming in, took her eight hours to schedule their onsite, you know, with everybody’s schedules and I’m , and so that’s eight hours that she can’t be recruiting.
And so because AI can help with a lot of those administrative tasks, it’s great at doing travel planning, scheduling, you know, screening those initial resumes, like we said before it can really help with JDs. And so I think that that is a huge place where AI can help. I think the other place that it’s broken, is when you’re hiring for technical roles and engineers and they have to take a coding test, right? And that coding test is only as good as the person writing it. And so many times from a talent perspectiveyou know, someone will get a question wrong and it’s not even something that they’re measuring for that this person is going to do. And so I think if AI can write some amazing coding tests or tests that engineers or QA employees can do, like that will be a huge piece that is a big pain point for recruiting.
Abhinav (04:19)
Do you think that recruiters will be replaced because of AI?
Suzanne Salzberg (04:22)
Well, I think if you talk to anybody in talent acquisition, they’ll laugh thinking like, good luck. There’s no, because I mean, honestly, so many times recruitment and talent acquisition is siloed over here. And we just live in our own world and nobody really knows what we do, right? And so like they don’t, and it’s probably bad on us for saying all the work that we do and what we do, but I just don’t ever see, and anybody that does it, knows that they should not be replaced, right? But there is a fear because the people that don’t know really what we do say, oh we can replace the talent team with AI, right? So, you know, it’s that.
Abhinav (05:03)
So you really have had thousands of resumes in a day?
Suzanne Salzberg (05:07)
Oh, 100%. If you just go on LinkedIn and look at some jobs, it literally will say, a thousand people have applied to this job, for one job, right? So if you think that every job pretty much gets 500 to a thousand resumes, so it’s, and if you know, you have 20 recs open, 20 job openings, yeah, you’re getting a thousand a day for sure.
Abhinav (05:16)
Oh my God, and how do, how do you manage that? I don’t think it’s humanly possible to go through them one by one. And you know, it’s destined to have a
Suzanne Salzberg (05:38)
What I do is I help people navigate the job market and the hiring system. And, and so, and when the first thing I help them with is their resume. And so I teach them that a recruiter probably is going to spend… 10 to 20 seconds on your resume. And that is no lie. So that first half of your resume better be good. because we, there’s you know, fortunately The applicant tracking systems have this thing, it’s called quick review. And you can go into quick review and you’re literally just tapping. And, and that’s why people you know are frustrated that the recruiters aren’t getting back to them. But I said, if you knew what a recruiter was doing right now, all of these things, like that’s, like don’t blame the recruiter. Like it’s the situation that’s happening.
Suzanne Salzberg (06:26)
That’s, it’s real. It is a real thing.
Abhinav (06:29)
I had a very interesting talk, I was at, I was at a conference where there are a lot of job boards and they’re talking about what are the things that they are doing to attract candidates. And they say, we are giving them the ability to not only create their you know resume based on AI, we are giving them the capability to actually apply for say 35 different jobs with 35 different resume, all altered on the basis of the job description.
And we were just laughing that it’s not that AI is going to fight humans or, you know candidates are going to fight AI. It’s AI fighting AI. You know AI from the recruiter side is actually fighting AI on the candidate. And good luck to the Boolean searches and the keyword searches because now everyone’s resume will be built based on the job description. How do you see that world? What are the skills that both the recruiters as well as the candidate will now need to do a better matching.
Suzanne Salzberg (07:34)
I always teach candidates that the job description is the final before the exam.
So I will look at their resume and then I’ll say, look at this job description. And when a applicant tracking systems or LinkedIn or any of those companies are matching you to the Boolean searches, right? they’re literally taking keywords from that job description that recruiter put in. And if that’s not on your resume, guess what? You’re not gonna be one of the top 30 people that show. And so
You can do it without AI. I mean, it’s harder, but like I encourage people to have a couple of different resumes. I mean, sure, if you want to make them, you can tell an AI resume. It’s still at the point where it’s a little bit of a turnoff because like, is it real? Have you searched like what this company is looking for? So there’s a trust factor. There’s a trust factor because AI can make this beautiful resume that literally matches the job description. Then you have to question, do I trust this person? Are these, is this data real?
We’re at the point now where we can tell. We can tell if it’s an AI resume. And I’ve been to, when I’ve been to conferences and you have people that, you know AI still misspells things. You can always tell there’s certain little things. It’s like when you get like a scam email, there’s certain little things you can tell that make it a scam. And so I would encourage people still to do it the old fashioned way, but use that job description as your final, like, and you know, focus on what you’ve done to match the job description.
Abhinav (09:07)
And, you know, when I’m speaking with a lot of, you know, talent heads or, you know, experts in the talent acquisition space, one of the big fear that I hear is about the AI bias.
What do you think both the companies as well as the you know AI tools can do to mitigate this bias in the AI -driven, you know world.
Suzanne Salzberg (09:28)
Yeah, I totally agree that bias can cause AI to make decisions that are, you know, systematically unfair to particular groups of people. it can discriminate based on race, biological sex, national, you know everything.
And so because humans are choosing the data that the algorithms use, and even if like these humans are making a conscious effort to eliminate bias, it can still be baked into the data that they select, right? And so you can do extensive testing and diverse teams can act as effective, you know, safeguards. But even with these measures in place, I mean, you’ve heard the old saying garbage in, garbage out, right?
Suzanne Salzberg (10:11)
And so bias can still enter that machine learning process and AI systems can then automate and perpetuate bias models going forward and then you’re in big trouble, right? And so one of the ways that you can help to mitigate the problem, and I think this is where companies really need to focus on, is that businesses should look to engage their data science teams, all the other functions, like very early on in their organization as early as possible. And so then they can assure that the models accurately reflecting the decision -making process and that you know, the data is just weighed accurately. But engaging those people after the fact is not a smart decision. So just getting everybody in early and preventing that bias early is what’s gonna help because if we don’t then it’s just gonna keep perpetuating that bad bias going forward
Abhinav (11:04)
Yeah, and just about those checks, you know, there are a lot of laws coming up about using AI in recruitment. There are recent law in Europe. New York recently passed a law to build more checks when it comes to recruitment. What are your thoughts? Do you think these laws and compliances, will they help the technology or will they become a blocker in the technological advancement?
Suzanne Salzberg (11:28)
It’s probably a mix of both. I mean, it’s going to be a learning process. think it’s good that there, there are laws. I think there definitely needs to be regulation in AI. And it’s, it’s going to be a lot of trial and error, honestly. I mean, things are going to happen. Things are going to break. And I hope they just fail fast and fix them fast. But I definitely think there should be some regulations. just like when GDPR became a huge thing.
Other countries besides ours were like, you know you have to delete our data within three months and you have to put on there, like, do you want us to delete your data? So yes, it was a blocker, but it was also a good thing, right? And so, anytime something new is, that’s what happens.
Abhinav (12:11)
Absolutely. And I want to talk also about the data. You know data has been one of the most important things when it comes to you know making recruitment more effective, making it better. You know the more the enrichment you can do of the candidate profile, the more you know diverse data you can do that. You know in this world of AI, How, What role do you play that data will take in making better talent decisions? And how can AI further put a fuel to that.
Suzanne Salzberg (12:39)
Data plays a huge role in making, you know, better talent decisions. I mean, I talked to you about, you know, when CEOs want data, right? So where does this data come from? It used to be like, just my information, right? And so data can play a huge role in making better hiring decisions. We talked about the analytics in the process, huge, right? So just to give you an example, if you build a great dashboard, you can tell in every part of the process how long it’s taking how many diverse underrepresented groups are in the pipeline.
It’s a lot of pipeline analytics that are really important because if you want to do great diversity hiring, then it has to be intentional. And it starts at the beginning of the pipeline. It doesn’t just happen at the end, right? And so let’s say you have a hiring manager that you notice underrepresented groups are just never getting through.
Like, you know, then that’s when you talk with HR and you say, hey, this hiring manager’s never letting through a person from an underrepresented group, right? And so those, it helps you to make better decisions. It also really helps with, one of the biggest mistakes I think people are making is they’re thinking, oh, we need 30 QA engineers.
But AI can help you build these models based on your revenue goals and all these things. And then you can reverse engineer based on these models, how many people should we actually be hiring? And, and what skills should they actually be? Here’s our problem of company X. What skills should the people we hire actually possess.
Suzanne Salzberg (14:22)
The other piece that’s huge is keeping up with compensation. So companies like Radford, I don’t know if you’re familiar with Radford, but companies like Radford that most people use to like look at what we should be paying people, you know, they have 35 ,000 companies that feed input into their, their software.
They do it once every six months, right? And so like say in 2022, what was happening was because salaries were going so high, so fast in the US companies started going outside of the US to hire, right? Canada, South America, that was happening a lot. And the salaries were half, which isn’t great, but, but companies were like, let’s go to Canada cuz you know, but so what was happening, the salaries in Canada and other countries were going up so fast
Because every company got this great idea. And I would come back and say, hey, the senior engineer is now making this much. And they’re like, what? Like there’s no way, right? There’s people just didn’t believe you. And so if AI could, could, you know, take that data and analyze it and quickly and give me like actual data that I can say, no, look here, that would be amazing. And then because you wouldn’t lose candidates, you know, based on the fan companies were just offering 50 grand more per person just to get them, you know? So the smaller companies were like, what do we do? like you know, so, and then the employees that had brought on, before that from those countries were now like making way less. It was, it was crazy. I’ve never seen anything like it in all my years. So, so I think the data on compensation can really help create better models.
Abhinav (16:06)
I think it’s so interesting, they said that how AI or data can actually help align companies business objectives to their hiring goals. And this is one of the big problem that we see that when majority of the companies, this whole talent acquisition and talent managements are staying silos and completely disconnected. You know, I would love to hear your thoughts on how can companies better align both the talent acquisition and talent management to just build a more cohesive ecosystem.
Suzanne Salzberg (16:35)
This is a big problem that’s happening right now in the talent ecosystem, and it’s looming very large right now. And because of the crazy market that’s been, right now employees and candidates are feeling that, you know, going back three to five years, that was, we’re people first. We care about people. We’re people before profit
Like you heard all these things of like people are a number one goal and which is great but now it’s like it’s a bottom line and all we care about and which is you know as a CEO it’s important right? It’s important that you consider the bottom line, but now so what’s happening is Employees are not feeling like companies are loyal to them so guess what we’re not gonna be loyal to you so when Suzanne reaches out as a recruiter I’m getting people way easier to jump ship from a company because they think well we could have a layoff next month because we’ve already had three so I’m just gonna leave right.
The other thing that’s happening is candidates are seeing this or they’re just been burned because they’ve been laid off three times in the last two years so they’re interviewing, they’re getting job offers and then they’re continuing to interview.
And so I’ve had in the past probably six months where candidates literally called the day before and said, oh, I decided to take another job because they gave me 20 ,000 more dollars. so nobody’s loyal. So everybody’s pretty much just like, sorry, not sorry. You know like you haven’t been, you know, helping me at all.
Companies need to be, especially HR, needs to do a better job in hiring better leaders that are understanding hiring the right people and budget forecasting. So we’re trying to mitigate all of this and we just really need to have better succession planning and it’s just instead of everything always being on fire and oh the first, the first solution is to do a layoff, right? And so companies have to really get back to valuing the people, not just staying there, but actually valuing the people. I feel like that’s, that’s really bad right now.
Abhinav (18:43)
We have spoken about hiring Suzzane, but what about post -hiring? You know do you think that AI will make a difference in providing overall employee experience as well, especially say from the day one right from their onboarding
Suzanne Salzberg (18:58)
Yeah, yes, for sure. think it will. I also think that it really helps people. I mean I talk to people that companies every day that’s like, Oh I had to make this PowerPoint presentation and AI helped me make these beautiful slides like that used to take someone a long time to do. Right. So it helps again now that companies are leaner. It’s helping take a lot of those administrative tasks, even off of onboarding and all of those things.
As in recruiting, I don’t think AI should replace onboarding. I think you should have real people doing people’s onboarding because again, it’s the first impression from these companies. I think, this is a really interesting aspect that I think can help a ton, is
If you ask any employee at a tech company, especially right now, is they’re always having to fill out these engagement surveys? How are we doing? What can we do better? Like on and people are very honest because a lot of times they’re anonymous, right? So what happens is the company fills it out, HR is saying, oh make sure you get your engagement survey filled out. And then they have an all hands meeting and they report the findings and people can do you know anonymous questions.
And the biggest pet peeve of employees is they take the time fill these out, they give you the feedback, and then they never hear anything about what’s going to be done to fix what we just told you was wrong. And so I feel like, because it takes HR teams a long time to compile this data, look at where the problems are, and I think AI can do that really fast, and then also maybe recommend some solutions to helping, right? And so then HR is going to be the one that executes them, but they can get that stuff done faster because HR so many things on their plate, again, it just takes that administrative stuff off. So I think it helps everybody, everybody’s employee experience.
Abhinav (20:53)
Absolutely, being an employee engagement platform. I can 100 % you know relate to what you’re saying. It’s not about the effort to take a survey. It is not even about an effort to go and collect the feedback. It’s about what to do with that. And like they say that you know a feedback taken and not done anything is actually worse than no feedback taken, 100%
Because HR has so many different things to do and so many fire to douse, if you just tell them that this is what your number one thing to increase your ENPS or your retention, they would absolutely grab that. And I think that’s a great opportunity for AI. And my last question, you know, we’re speaking about it today, but I want, you know, I would love to hear your thoughts on that one thing, that biggest impact that you believe that AI will make in the talent life cycle in the next 10 years from now
Suzanne Salzberg (21:27)
For sure. You’re gonna see a lot of trial and error which I said well I think you’re gonna see a lot of trial and error which works, but I think the analytics and seeing where the process is working or not working. I think it’s really gonna help make data driven decisions as well as taking the time off the recruiting team on parsing those resumes that we get so many resumes I would say a lot of it depends on the industry for an example
I have a friend who’s a radiologist, and he literally said to me, there will not be radiologists. AI is going to completely take over, just the radiologists that are reading the scans, not the ones that are doing you know surgery. He said they can do it faster, they don’t make mistakes, and, and people can get that information way faster, right? So like you’re sitting there, you just got a scan, and you have to wait for the results. Painful, right? You can literally get it in 10 seconds.
Suzanne Salzberg (22:44)
And so he said, he literally told me, goes, my job is not going to exist. So a lot of it depends on the industry, right? So that is one job that yes, AI can replace that job.
Abhinav (22:44)
Wow.
Suzanne Salzberg (22:56)
Right? And so, yeah. And I think that what’s happening right now is we’re between generations. Right? And so even Gen Z, like they’ve had human interaction and AI right now, but like say a Gen A, like after Gen Z, they’re fine with no human interaction. Right? They’re like, I don’t want to talk to people because they can’t have a conversation. Right? I don’t want to talk to people. I’m fine if an avatar does my interview. So I’m not saying 10 years from now what’s gonna happen
Abhinav (22:56)
my god.
Suzanne Salzberg (23:27)
But I think right now there’s too many people that were in this flux between the generations where that’s why it’s not gonna happen but hey, I am not naive enough to say that like if you have future generations that have no problem never talking to a human it might not, you know replace it. That’s my biggest fear I would be very sad if that happened, but you know, some of it’s probably inevitable
Abhinav (23:49)
I want to say one thing to your radiologist friend that I am talking to, everybody. Like, I’m hearing this from a programmer. I’m hearing from an SDR. I’m hearing from a copywriter, from a marketer that our job will be replaced by AI. And to be honest with you, I honestly, I don’t think so. I think we humans have an incredible capability to adapt and learn and build new skills that an AI can’t do. So I’m
I’m sure there’s both of us to see that what the next 10 years we do, but I’m very optimistic that it’s going to be something good and not very negative. Well Suzanne, thank you so much for taking the time to speak with me. I just loved our conversation and this industry is moving with such a high speed. And I’m sure when we speak again, we’ll have a different you know AI landscape and new challenges.
Suzanne Salzberg (24:24)
Exactly.
Abhinav (24:42)
I’m sure we both and you know all our audience will be fully prepared for that. Have a wonderful day and thank you so much for your time.
Suzanne Salzberg (24:49)
Thank you. I enjoyed it. Have a great day. Bye.
Abhinav (24:52)
Thank you.
