I recently returned from my annual pilgrimage to the HR Technology Conference in Las Vegas. There are a ton of conferences in our industry, but HR Tech still remains the event to come to for the most comprehensive view of innovation in talent acquisition.
It is clear that things are moving fast with technology; AI is already moving from narrow, single-use tools to orchestration layers and multiple agents that promise to revolutionise talent acquisition. Unfortunately, it is making the tech landscape very difficult to understand from a buyer’s perspective, as traditional software categories are collapsing.
At the same time, the legacy cornerstones of the recruiting process, resumes, interviews, and job descriptions, are looking increasingly inadequate, with candidates and employers caught in an AI arms race that is currently making the experience worse rather than better.
So how can TA leaders cut through the noise, balance efficiency with fairness, and bring humanity back into recruiting while taking advantage of the enormous potential AI offers? What new skills will be needed to lead in this environment, and how do organisations avoid just using AI to do the wrong things faster?
While I was at the show, I caught up with two of my regular podcast guests, Allyn Bailey, Senior Director of Brand and Communications at SmartRecuriters, and Daniel Chait, CEO of Greenhouse, both of whom offered some sensible guiding insights into what is becoming a very complex space.
In the interviews, we discuss:
• Blurring categories of vendors is confusing for buyers.
• AI’s next phase of orchestration layers and multiple agents
• The importance of open systems
• Will we finally see the end of resumes?
• The surge of AI interviewing
• Why the candidate experience keeps getting worse
• Balancing efficiency with fairness and keeping humans in the loop
• The new skills TA Leaders need
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00:00
Matt Alder
AI is revolutionizing recruiting technology at breakneck speed, but is it creating chaos for buyers and making the candidate experience worse? What’s really happening? I went to the HR Technology Conference in Las Vegas to find out. Support for this podcast comes from appcast. Appcast is changing the game when it comes to hiring. Using powerful tech, data driven insights and deep recruiting expertise, appcast helps employers find qualified candidates quickly and efficiently. In fact, companies using Appcast see a 50% drop in cost per hire and fill roles faster. Whether you’re building a brand or filling mission critical roles, appcast delivers results that move the needle. To learn more, go to Appcast.io. That’s Appcast.io. Hi there. Welcome to episode 733 of Recruiting Future with me, Matt Alder Recruiting Future helps talent acquisition teams drive measurable impact by developing strategic capability in foresight, influence talent, and technology.
01:36
Matt Alder
If you’re interested in finding out how your TA function measures up in these four critical areas, I’ve created the free Fit for the Future assessment. It’ll give you personalized insights to help you build strategic clarity and drive greater impact immediately. Just head over to Mattalder.me/podcast to complete the assessment. It only takes a few minutes. This episode is about technology. I recently returned from my annual pilgrimage to the HR Technology Conference in Vegas. There are a ton of conferences in our industry, but HR tech still remains the event to come to for the most comprehensive view of innovation in talent acquisition. It’s clear that things are moving very fast with technology at the moment. AI is already moving from narrow single use tools to orchestration layers and multiple agents that promise to revolutionize talent acquisition.
02:34
Matt Alder
Unfortunately, it’s making the tech landscape very difficult to understand from a buyer’s perspective, as traditional software categories are collapsing. At the same time, the legacy cornerstones of the recruiting process resumes, income interviews and job descriptions are looking increasingly inadequate with candidates and employers caught in an AI arms race that is currently making the candidate experience worse rather than better. So how can TA leaders cut through this noise, balance efficiency with fairness, and bring the humanity back into recruiting while taking advantage of the enormous potential that AI offers? What new skills will be needed to lead in this environment? And how do organizations avoid just using AI to do the wrong things faster?
03:24
Matt Alder
While I was at the show, I caught up with two of my regular podcast guests, Allyn Bailey, Senior Director of Brand and Communications at Smart Recruiters, and Daniel Chait, CEO of Greenhouse, both of whom offered some sensible guiding insights into what is becoming a. A very complicated space.
03:43
Matt Alder
Hi, Allyn, how are you doing?
03:45
Allyn Bailey
I’m doing fabulous. How are you?
03:46
Matt Alder
I’m very good. It’s HR Tech again.
03:49
Allyn Bailey
Here we are.
03:49
Matt Alder
Yeah, absolutely.
03:51
Allyn Bailey
Well, back again.
03:52
Matt Alder
Yes.
03:53
Allyn Bailey
This feels like. What are we on? Like year three, year five, year 20?
03:57
Matt Alder
I don’t know, it kind of all blends into one. How’s this one been? How do you think? Has this one been the same as normal? Has it been different to the others?
04:05
Allyn Bailey
You know what’s interesting? And I did not get to do enough of a walkthrough like I usually like to do. But the. But my general impression is this one. I feel like the show in size is back to where I’ve seen it before. I’m not so sure in numbers, but we always. That’s just a challenge. There are a lot of smaller side players that I have in all sorts of spaces I haven’t seen, but they’re all over the place. There are a million of these kind and they’re not cheap. I mean, they’re, they’ve shown up. This is not kind of startup stage stuff. There’s a lot of new stuff out here and I don’t know what it is, but I’m interested to know.
04:44
Matt Alder
Yeah, I think that’s a good point.
04:45
Matt Alder
I noticed that as well. There are lots of like smaller, you know, well designed stands with people in the market. So it’s. Yeah, it’s kind of indicative of, I suppose, what we’ve seen in terms of, you know, investment in AI from investors and all that kind of stuff. So. Yeah, Interesting. So it’s two years ago now since we sat down and talked about recruiterless recruiting.
05:08
Allyn Bailey
I know everybody. And all of the comments we got, Matt, they were like, no, you can’t do that. The humans have to be there.
05:17
Matt Alder
Absolutely. So it’s obviously a really big year for smart recruiters with the launch of the new AI first approach to everything. What have you learned? Where. Where are we on that, on that journey? What’s changed?
05:27
Allyn Bailey
It’s so. Well, I don’t. I. I think a lot has changed. I think the tech has evolved and we knew it was going to. That was part of the point. We said, listen, what you guys are seeing two years ago, this is the baby stuff. It’s going to be the. It’s going to be the entry and then the tech’s going to start to evolve. I think that we are seeing a expansion in the number of Use cases. I also think what we’re seeing now is differentiation between what I would call kind of alpha tested AI that came into market, you know, four or five years ago. Like the early stuff, it was great. I mean, listen, it really, I think it opened the doors, but it was confined to single use cases.
06:15
Allyn Bailey
It was very specific in action and it required a lot of deep integration and field mapping. Just the way the tech worked. Right, the way the tech work. We then moved into the LLM phase. Everybody talked about it in terms of, you know, Jenny, I. And what that was doing, but what that did was open up a new frame that said I no longer have to match field to field. I’m going to be accessing data in a different way. That was, that was two years ago when we first started saying, this is going to open up something. We’re going to get to the world of recruiters recruiting. And I think at that point everybody said, well, you know, a good conversational bot doesn’t take you to recruiters recruiting. And they were absolutely right.
06:58
Allyn Bailey
What does however, though take us further down that path is our now kind of that next evolution, which is the connection of data layers with orchestration layers, with multiple agents being used for multiple types and being able. Because in the old world, right, for those of you who are old like I am and have done this for a while, you know that the biggest issue in TA and in any tech solution was, oh my God, I’m gonna have to go through an implementation to figure out my integration to all of my stacks and figure out like just a field map. Like the nightmare, right, that’s now changing. Because the way agents work, collect and leverage data and connect into these components means I’m not integrating in the same way. It’s almost, you know, it’s much more cellular and it’s hard to.
07:55
Matt Alder
I know it gets really just allowing access, isn’t it?
07:58
Allyn Bailey
It’s allowing access. And once you get access, now I got access to all this. Now I got access and I can now use insights and intelligence. Right? When we get to the point, which I think will be the next phase, when we get to the point that I’ve now got the access and these agents are kind of connecting together and then I have really good orchestration, meaning the agent says, oh, I have an idea, I think you should do X. And the X can actually be achieved because there’s an orchestration layer that can actually do it, right? I kind of think of it. I love the word orchestration because it Gets a lot like an orchestra. Your agent’s a conductor out there and coming up with ideas and like telling you get more symbols.
08:41
Allyn Bailey
But if you don’t have symbols, he can say more symbols all day long, but you’re not going to get more symbols. Right? And that’s going to be that next connector point. And then we’re off to the races. Guys, we’re already off to the races. Nothing’s going. We’re not going backwards.
08:56
Matt Alder
Yeah, totally. I mean, I think the two things that struck me, I think last year, sort of wandering around, talking to benders, everyone was building an agent, right? And now it’s multiple agents that do different things. And so I think it’s really important for, I think people listening to really understand just how quickly AI is moving here. And I think we’re getting to the point where people can actually now see what’s possible. And particularly pulling data together and the insights that can give into, you know, what goes on in talent, I think will help people along that journey because they can kind of see the results of it 100%.
09:30
Allyn Bailey
Well, I mean, listen, before I killed off recruiters, sorry, guys, I was long on the map of saying resumes are horrible, they’re static documents. People are not static, they’re dynamic. It’s you. It’s too hard to know information and how people are evolving. By the way, same thing with job descriptions. As has always been the case, right? We’ve been using the same form for job descriptions and resumes since literally the 1800s. So it’s not like, you know, this has been a highly evolved, iterative space. What this does is if I can now access in the moment, up to date insight and information and data. The translation there is. I can now have new ways and start coming up with new use cases for me to be able to get this one, guys, to actually solve workforce planning.
10:25
Matt Alder
Yeah, no, totally.
10:26
Allyn Bailey
And I can, because I can now do predictive. I can access that data. I can understand that jobs are fluid and dynamic. They’re not going to be the same. I may need a bot to do one thing and a temporary person to do another thing. And I, I can get intelligence to do it. And my insights about who you are as a person can literally evolve as fast as I can access information about you. Not as fast as you can type it on a typewriter and upload it into an ats.
10:50
Matt Alder
I think it’s truly revolutionary. I think it’s just a whole level of intelligence that has never been possible before. And I, you know, countless people that I’ve kind of spoken to over the last two days has been like, we’ve always wanted to do this, but now AI has made it not just possible, but easy and easy in the, in.
11:06
Matt Alder
The scheme of things.
11:07
Matt Alder
Nothing’s easy. And also that I think that openness is something that’s really come across in the conversations that I have. It’s like, you know, we’re open to all of this now. There are still always going to be some players who try and sort of close and protect their data. But it’s a very different vibe and atmosphere around that sort of data access 100%.
11:24
Allyn Bailey
And how you can access is why to me it’s been the easiest answer when people say, okay, as we mentioned, smart recruiters is now part of the SAP family. We’re now part of that world. We, we can still be agnostic and serve any HCM solution because integrations and data don’t work the same way they used to work before. I don’t have to be locked in, open, interconnected, multiple different types of tools from different types of vendors operating simultaneously and orchestrated successfully is the future. It is going there. It’s already started and that will change everything.
12:02
Matt Alder
This place is a bubble. It’s full of, you know, cutting edge technology and all this kind of stuff. So the kind of the reality situation, obviously, you know, you’ve launched the AI platform this year. How does it kind of resonate with customers? What’s actually going on with TA in terms of sort of taking that evolution to be able to really effectively use the tools and things that we’re talking about.
12:25
Allyn Bailey
So, so funny that. Not funny, but I will, I’m not going to go too deep into it, but we have some new research coming out. We did what Kyle and company just wrapped up. It’s going to go out this week. The whole focus on it was to try and understand the archetypes for AI maturity across the industry and to understand what is it, who’s moving and doing what and what are they doing and what are the paths forward and who’s succeeding. Here’s what it’s resonating very much for what we’re seeing as well. Those who are going in and they’re experimenting, they’re doing a piece and we’re seeing this with our customers too. And then they are expanding quickly when they see that there, you know, it’s kind of a land and expand strategy inside TA organizations. And I think it’s super smart.
13:10
Allyn Bailey
We also saw out of that, by the way, they did that because they had governance and controls in place. They already knew what their boundary conditions were. It allowed them to understand what fence they were going to work with then. And they had real cross collaboration across their different business units. Those people are moving fast. But it is a. When I used to say land and expand in businesses like this, we would say, okay, you’re going to go and get the CRM mod. You’re actually usually work more like this. You’ll go get the ATS and then you’ll figure out in two years when it’s uptime for renewal, let’s add on the CRM and then in two years when it’s time for renewal. We now got, you know, a new integration with DocuSign or whatever. Right. And that would be the operating model.
13:54
Allyn Bailey
Now what we’re seeing is, listen, our first customers went live. The ones that were part of our design partnerships, they went live six months ago, seven months ago. Some of them, they are now two, three, four modules in. They are expanding at a rate of, you know, a new expansion module on every two months or so. It’s a, it’s a different frame. They’re moving faster because we’re moving faster and the capabilities moving faster. And if they trust it and it’s solving a problem one problem at a time.
14:29
Matt Alder
Now that makes sense. And I’ve kind of asked you, we’ve talked about this before, but I’m interested just sort of finally in your updated perspective on this. It’s obviously very disruptive. You know, lots of TA functions being disrupted in lots of different ways. Not just technology, but the economy and everything else that’s going on. What are the key skills that you think TA needs as a function kind of in the future? What, where are we now in terms of people listening who want to future proof their careers or kind of really sort of move forward in this space?
14:59
Allyn Bailey
I think you need to, I think you have to have three things now. And I think these are the new. They’re not new, but these are the big three things that you have for is on. I think you need to understand compliance and regulation at a nuanced level that we have never had to do in a business before. Which is interesting because, you know, we’re all compliance geeks. That’s how most people ended up in hr. I didn’t, I’m not one, but I didn’t mean to Be. And now I am. It’s like a. You’re in it and it’s. You know, we get a part of our job is to make sure the company doesn’t get sued.
15:28
Allyn Bailey
But with all of these new lawsuits that have gone into place what’s happening in the AI space, you need to get really versed in this and you have to get really comfortable and be able to understand what the legal words mean so you can make choices. Because what you don’t want to do is leave it up to just the lawyers in your company to tell you what you can and can’t do. I remember when I was at intel for a while and driving transformation work, one of my biggest sayings I would tell everybody is that don’t ask for permission, right? Ask forgiveness to a certain degree. And also don’t expect that your legal department understands what it is that you do or the nuances of it. And they can’t. It’s not possible.
16:13
Allyn Bailey
And so they’re going to be as conservative as possible so they can lock it down. You’re going to have to explain to them what you can do. And that means you have to know it. So that’s one, compliance and legality, you got to stand up. Two, you gotta go now a step deeper in understanding how artificial intelligence technologies work. So we had a lot of conversation in this right now talking about the difference between integrations and how data gets leveraged. You need to understand vector mapping, you need to understand embeddings. There’s a new vocabulary with a new set of skills, and you cannot leave that up to your IT department again, you need to understand it because you can’t design the new use cases unless you know what’s possible and how it actually works.
16:56
Allyn Bailey
And then the third thing you have to have is an increased capability to connect the dots between multiple business units. AI is not. There’s nothing in the tech space anymore that is a one business unit, one use case model. If you put something in TA CHROs need to know about it. Your IT department needs to know about it. Your business units are doing something in this space. Your legal departments are involved. You’re gonna have to get really good at stakeholder management and understanding how to connect the dots. So everybody’s speaking the same language that companies who are doing that are succeeding, those that are challenged with it, who are very siloed, are having trouble.
17:39
Matt Alder
Allyn, thank you very much for talking to me.
17:41
Allyn Bailey
Thank you.
17:44
Matt Alder
Hi, Daniel, how are you doing?
17:45
Daniel Chait
I’m doing exhausted. It’s the end of hr. Tech.
17:49
Matt Alder
I know that feeling. I know that feeling well. And it literally is that point where they’re starting to pack up chairs and boxes and things. Things around us.
17:56
Daniel Chait
Yeah. I mean, if you’ve come to HR tech, you know this like it’s so vast and you know, your hotel is vast and so if you like go back to your room to change, you know, your clothes, you come back, it’s like that’s a three mile walk. You want to go get a glass of water. Like that’s, you know. So you definitely get your steps in.
18:09
Matt Alder
I’d say, yeah, 20, 20 to 25,000 a day. Yeah, exactly. So reflecting on what you’ve seen, what you know, has this been different to shows before? What are your sort of takeaways? What’s the, you know, temperature? Everything, as it were.
18:21
Daniel Chait
I mean, the. One of the big differences I think that is represented here this year is it used to be that there were sort of clearly defined boxes and categories that everyone fit into. And it was like, oh, you’re a payroll company, you’re an ATS company. And I think those boxes are just being wildly redrawn and people are like trying to push out of their box into other boxes or erase the boxes altogether and do all kinds of stuff. And I think it’s exciting and innovative and fun. It’s also, I think I have a lot of empathy if you’re a buyer, to try to even tell the difference between these things and what are they.
18:58
Matt Alder
And who are they.
18:58
Daniel Chait
And you know, a company’s like, we do everything you ever need in hr. And then you’re like. But you look at you like, no, you’re like a one one manager or like you’re like a, you know, 401k plan. So I think it’s really hard. It’s getting harder to tell what all the pieces are that you even need because lots of vendors are saying they’re everything to everyone.
19:17
Matt Alder
Yeah, absolutely. It’s kind of a real sort of, you know, gold rush to owning everything everyone can own and own everything. I mean, I think one of the things also that kind of strikes me almost kind of the, I suppose, oppose. The almost the opposite side of that coin is we’re kind of seeing the recruitment process broken into different bits. So we’ve got, you know, recruitment, marketing, sourcing, interviewing, all this sort of stuff and people seem to be sort of AI ing. AI ing that all separately or dealing with it all separately, which doesn’t seem to me to be the way to really get the benefit of what AI can give. I mean, what’s your perspective on that?
19:52
Daniel Chait
Yeah, well, I mean, in some ways it’s like the ultimate. Like if all you have is a hammer situation, it’s like, I have AI, I’m going to aim it at whatever part of the world I exist in and say like, AI is the solution to your point. X, Y, Z. So yeah, like lots of people are applying it in every way, shape or form and we’ll see where that all goes. I think one of the ways that it is starting to really break out is interviewing. I think I’ve described it as going through the Condi curve. If, you know, Gandhi famously said, you know, first they ignore you, then they laugh at you, then they fight you, then you win.
20:26
Daniel Chait
And I think AI interviewing is going through that at breakneck speed where, you know, it wasn’t that long ago you go on TikTok or YouTube or Instagram and you see people making fun of the silly questions that AI interview asked them or how inappropriate it was. And like, yeah, but I don’t think it’s that far from soon. You know, people are fighting it a little bit. I think it’s to going to win at the same time, how it’s going to win, who’s going to win, what they’re going to do with it. Wildly unknown. There’s probably like conservatively 700 companies here doing AI interviewing and it’s like every modality, there’s voice, there’s video, there’s avatars, there’s chat, there’s like top of funnel, middle funnel, bottom of funnel interviews.
21:05
Daniel Chait
There’s like skills assessment, there’s is like, who knows of all that where it’s going to shake out. That’s to me the biggest know question. But whether or not people will be doing more or less AI interviewing next year. That’s not a question to me. I mean, absolutely, it’s on the rise.
21:19
Matt Alder
Yeah, no, I completely agree. I think it’s an unstoppable force and I suppose on that they’re still mainly driven by lawsuits and things that are going on and also the sheer number of people who are looking for jobs at the moment, which means the candidate experience is probably worse than it’s been for a while. There’s so much kind of like, you know, media coverage and things about people are applying for jobs with AI and AI is screening them out and all this sort of stuff. Do you think that sort of collectively, as an industry doing a good enough job to actually explain what some of the benefits of it are and actually what some of the misconceptions are around it.
21:56
Daniel Chait
Yeah, no, to be clear, when I was saying I’m very sure that it’s coming, I was not saying I’m very sure that it’s going to be all positive. Like, I just want to be really clear about that. To your point, there are tremendous concerns and drawbacks. And I think the real challenge for anyone navigating this, whether you’re a vendor, whether you’re an employer trying to use technology, whether you’re a job seeker, is like, how do you use these technologies to get the benefits, to deliver the benefits without the drawbacks while minimizing those risks? And they’re, and they’re very real ones. You talk about, hey, like, companies that are using AI algorithms automatically to make hiring decisions are finding themselves subject to a variety of laws and lawsuits across different jurisdictions.
22:33
Daniel Chait
Even down at the state and city level across the world, it’s a big mess. And I think people have real concerns about fairness. They have real concerns about the employee experience. Are people going to like this or not? Is it going to turn away the good talent? So there’s a lot of worries, I think people are right to have, about how this is going to work. And then you talk about on the candidate side, you’ve got job seekers using AI as well. So if you’re sitting there in HR going, oh, we’re going to use all the AI, it’s going to solve the problem. Like, I got bad news for you because the job seekers are using AI also as much or more than you are. And so, and again, I have a lot of empathy for them.
23:07
Daniel Chait
If you’re a job seeker, what else should you do? The job market isn’t working for you. It’s getting worse, not better. You send your resume and it goes into a black hole. You never hear back. And if you ever find out something, it’s at your 10,000th in line for this job. So of course you’re going to use automation to update your resume automatically to make it sound more relevant to the job you’re applying for. Of course you’re going to use AI to automatically apply for tens or hundreds of jobs at a time to give yourself a chance. So individually, people are doing what they, you know, are responding to the environment that they’re in. And I don’t blame them for that. What it means collectively is that the process is getting worse, not better. It’s getting easier to apply for jobs.
23:46
Daniel Chait
So People are applying to more and more of them. It’s getting harder to get a job.
23:50
Matt Alder
What’s really surprised me is in the conversations I’ve had so far, no one’s really kind of addressing that. So, you know, thousands of applications for jobs and other than a very sort of implicit steer that AI is somehow going to absolve that, I’m not really hearing people sort of taking that on head on. Obviously, it’s something that your customers are facing. I mean, how. How are you kind of helping them with that?
24:13
Daniel Chait
Yeah, well, we are taking it head on. And I think, you know, we’ve described it as a doom loop. As, you know, each side uses more and more AI, it’s making the process worse and forcing the other to respond with even more AI and like thinking somehow that’s going to solve the problem. It’s just not. And we’re delivering AI tools as well to our customers because they want them, but it’s not going to solve that problem without some intervention. The first thing we did, we launched My Greenhouse earlier this year. My Greenhouse, a candidate portal. So this is something a job seeker uses when they apply to a job at a company that’s using Greenhouse and they can store their profile.
24:44
Daniel Chait
They can then easily apply to more jobs, save their status and update, get updates automatically as to where they are so they get some transparency. We did dream job feature for them. So as a job seeker, you can designate one job a month as your dream job. And what that does is it indicates to the employer like, hey, of all the jobs I’m applying to, and I may be applying to dozens or hundreds of, this is the one that I care the most about. This is the one that I think I’m the best at. This is the one that I think I have the best chance to get. And so that’s a really useful signal as a job, as an employer, when you’re looking at 1,000 applicants, you’re not going to read all those resumes.
25:18
Daniel Chait
How about the ones that said, this is my dream job? Let’s look at those first. And so those shows up inside Greenhouse in your prioritized inbox. So that’s a way where I think what we started to see is we cannot solve the problems our customers are having without engaging with the problems job seekers are having as well. We have to start solving job seeker problems if we’re going to really deliver what we need to our customers, to the employers. And so that’s why we’re doing things like my Greenhouse and Dream Job and Greenhouse Jobs and all these other things that we’ve launched for job seekers. Because when you look at how that turns around and benefits our customer, you see that it’s actually cutting through the AI Doom loop and bringing the humanity back.
25:57
Daniel Chait
Dream Jobs AI is a checkbox, but what it is it gives you an expressive tool of all the other things that are happening to say a little bit about yourself and stand out. And so what we’re envisioning is a whole bunch of more things that we can do in the My Greenhouse product to give job seekers a way to express themselves, to bring the humanity back and say, who are you really? What are you really good at? What do you really want to be doing and how do you want to be doing it so that we can help you find. Find a better job? And so I think the way out of this mess lies a lot more in bringing humanity in. And ironically, the more the world gets dominated by AI and kind of AI slop, the more valuable that human factor becomes.
26:37
Matt Alder
Yeah, and I agree. And I think we kind of just seeing that, it’s like, how do you stand out in the wrath of everything that’s sort of going on? And where do you think that we might end up? Because we’re obviously in a place where the job search and the recruitment process feels quite broken. It’s interesting that whenever anyone says that on LinkedIn, people kind of jump to its defense. And then the counter argument is, well, try being a candidate right now and tell me that it’s not. Tell me that it’s not broken.
27:05
Daniel Chait
Wait, are you telling me that online discussions are not reasonable and produce effective outcomes?
27:11
Matt Alder
If they did, we probably will be a very different place. But so what do you think when. How do you think the process is going to evolve? Where do you think we might end up with it all?
27:22
Daniel Chait
Yeah, I mean, I think, you know, obviously there’s a lot of cliches I’m going to say here, but bear with me for a second. Like, AI is here to stay. It’s going to become more and more a part of everyday life. I think, you know, that evolution I talked about earlier, about the perceptions of, for example, AI. Interviewing. Like, societal views on these things are evolving extremely rapidly. What used to be seen as very unacceptable is going to soon become the norm. That happened, by the way. It’s not the first time it happened. I’m old enough to remember when people said there is no way someone’s going to apply For a job on the Internet. Come on, you’re applying for a job, of course, that nice paper, you know, that you’re going to put your resume on, like that means something.
27:55
Daniel Chait
You’re not, you know, to put that into a website, into a computer now. So there’s just a way to say that I think society evolves with technology, but the technology often leads and there’s a period of discomfort along the way. Well, that’s going to continue, that’s going to accelerate. I think the positive of it is a lot of the efficiency gains, a lot of the productivity gains that we haven’t quite been able to measure, I think will come. A lot of people are experimenting, A lot of people are putting these technologies to use. And I do think that we’re going to be able to do a lot more with a lot less in the years to come.
28:28
Daniel Chait
So things like scheduling interviews, things like automating, outreach to people to see if they’re interested, following up on your internal team to make sure that they input their feedback after an interview, all the kind of data, even things like running reports or reading reports and thinking about what they mean. A lot of that hard work is going to be done by the computer increasingly. So I think there’s a huge amount of efficiency yet to come that’s going to be delivered by these technologies. At the same time, I think if you just look at the trend, application volumes go up and up as it gets easier and easier to apply, and that gets more. More and more automated?
29:00
Daniel Chait
Ultimately, doesn’t that get to a point where there’s no such thing as a job application because you open up a job and all 850 million LinkedIn profiles are in your inbox immediately. And so it’s like if you have 800 million profiles, you have none. And so that’s gonna. That’s kind of already happened. And so then what. And I think where we’re getting to is a place where you can stand out more and more as a human being. Amidst all that noise, you can verify that you’re a real person, not a bot. That’s a big question online today. Being able to prove that you’re actually someone that’s.
29:30
Daniel Chait
We didn’t use stuff to do that, but that’s coming, I think, you know, being able to say a lot more about who you are, what you want, what you’re good at, what you’re looking for, that’s coming more and more. And then on the same, on the employer side is like, are there ways where having automated all the process stuff. Can they bring back the humanity into the recruiting piece of itself and say, no, what I want to do is spend time with people who want to get a job in my company.
29:54
Matt Alder
Absolutely. And I think that is, that’s just really the key message is like how we think about humanity and where it kind of gets deployed, deploying humanity kind of phrases that.
30:05
Daniel Chait
You know what I mean? Today’s episode of Black Mirror.
30:07
Matt Alder
Absolutely. I’ve spent too long at the technology conference, as that’s obviously right. But just like letting humans be humans and kind of understanding that, yeah, I.
30:15
Daniel Chait
Think everybody wants that. And I think that’s really a vision that we have is let AI do AI and let’s bring the human back in to where the people can do what we do best.
30:23
Matt Alder
Daniel, thank you very much for talking to me.
30:25
Daniel Chait
Thanks so much, Matt. This has been a blast.
30:28
Matt Alder
My thanks to Allyn and Daniel. Don’t forget, if you haven’t already, you can benchmark your talent acquisition capability quickly and easily by completing the free Fit for the Future assessment. Just head over to Mattalder.me/podcast. It only takes a few minutes and you’ll receive valuable insights straight away. You can follow this podcast on Apple Podcasts, on Spotify or wherever you listen to your podcasts. You can also search through all the past episodes at recruitingfuture.com where you can also subscribe to our weekly newsletter, Recruiting Future Feast, and get the inside track on everything that’s coming up on the show. Thanks very much for listening. I’ll be back next time and I hope you’ll join me.
