Talent Acquisition appears to be facing the perfect storm. The volume of inbound applications is increasing at unprecedented levels; however, at the same time, budgets are being reduced, and TA teams are getting smaller. On top of that, hiring for specialist talent is getting harder with remote work, making talent markets truly global and increasing competition for the hardest-to-find skills.
So, how can TA Leaders navigate these disruptive waters? AI is often positioned as a magic solution, but cutting through the cacophony of marketing noise it generates is a real challenge.
My guest this week is Steve Bartel, Founder and CEO of Gem. Steve offers us insights and advice from the perspective of a vendor building solutions to the challenges TA teams face. As well as talking about the trends that matter and the long-term impact of AI, he also shares some valuable advice on properly assessing potential AI solutions and avoiding some of the common pitfalls currently out there.
In the interview, we discuss:
• The challenges TA faces
• Noise versus signal
• What are the real game-changing trends?
• Single vendor versus point solutions
• Navigating the Gen AI revolution as a vendor
• The long term impact of AI on Talent Acquisition
• The AI hype cycle
• Ranking and matching
• Delivering an exceptional candidate experience
• What should buyers be aware of
• Recruiting Nirvana
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Transcript:
Matt Alder [00:00:00]:
Support for this podcast comes from gem. GEM is the AI powered recruiting platform that TA teams love. It helps you maximize productivity, hire faster and save money, all while giving recruiters a solution that they find easy to use. Use GEM as your all in one recruiting platform or enhance your ats with integrated products for CRM, sourcing, scheduling, analytics, career sites, events and more. Over a thousand companies, from startups to industry leaders like Airbnb, wayfair, Cintas, Carmax, DoorDash and Zillow, trust Gem to hire with speed and ease. See why Gem is the recruiting industry’s most beloved solution with a 4.8 out of 5 rating on G2 by going to gem.com that’s Gem.
Matt Alder [00:01:15]:
Hi there. Welcome to episode 651 of Recruiting Future with me, Matt Alderman. Talent acquisition appears to be facing the perfect storm. The volume of inbound applications is increasing at unprecedented levels. However, at the same time, budgets are being reduced and TA teams are getting smaller. On top of that, hiring for specialist talent is getting harder, with remote work making talent markets truly global and increasing the level of competition for the hardest to find skills. So how can TA leaders navigate these disruptive waters? AI is often positioned as a magic solution, but cutting through the cacophony of marketing noise it generates can be a real challenge. My guest this week is Steve Bartel, founder and CEO of gem. Steve offers insights and advice from the perspectives of a vendor, building solutions to the challenges that TA teams face, as well as talking about the trends that matter and the long term impact of AI. He also shares some valuable advice on properly assessing potential AI solutions and avoiding some of the common pitfalls that are currently out there. Hi Steve and welcome to the podcast.
Steve Bartel [00:02:34]:
Hey, it’s great to be here. Thanks for having me.
Matt Alder [00:02:36]:
An absolute pleasure to have you on the show. Please could you introduce yourself and tell us what you do?
Steve Bartel [00:02:42]:
Absolutely. So my name is Steve. I’m the Founder CEO at gem. And at gem, we build the leading all in one recruiting platform powered by AI. So what that means a little bit more specifically is we’ve combined sourcing plus CRM plus scheduling automation plus marketing automation for recruiting as it pertains to recruiting events, but also talent marketing initiatives, plus an applicant tracking system and end to end analytics, all powered by AI into one platform.
Matt Alder [00:03:14]:
Fantastic, fantastic stuff. And it’s such an interesting time at the moment with AI and everything that’s going on, but also Lots of challenges in the industry. And I’m sure that talking to your clients, you’ve got some really interesting perspectives in terms of what’s going on. What are you seeing as the biggest challenges for talent acquisition at the moment?
Steve Bartel [00:03:36]:
Yeah, I would bucket into a few different things. The first thing that I’m seeing, and I’m sure all of our audience, I’m sure you hear this all the time, but there’s just this massive influx of inbound applicants for so many companies. Just to get a little bit more specific, with some gem stats, 16% of our customers are seeing thousands of applications for a single role. Which is wild. Yeah. And then if you just look at it in aggregate, year over year, inbound applications are up 30% year over year the last two years. And I think not only is there what’s going on with the job market, but also there’s this onset of AI tools are enabling candidates to apply to hundreds of jobs or even more at once and reducing that friction. So it’s a really interesting time TA teams are really overwhelmed by the amount of inbound applications. I think the other trend that I’m seeing, and this is actually making that first trend even more challenging, is that teams are being asked to do more with less, just given the environment, especially in tech. Over the last few years, everybody’s been trying to be a little bit more thoughtful and mindful about budget. And then also team sizes are way down from where they used to be a few years ago. And so talent acquisition leaders are tasked with how do we hit our hiring goals, but how do we do that with fewer resources? And so everybody’s being asked to do more with less. And then I think the third thing that I’m seeing is, and this is mostly in larger enterprises, you’d think that with a lot of talent on the market, that folks would be having an easier time recruiting these days. But actually the thing that’s happened is in larger enterprises, it’s the opposite. I think that it used to be the case that a lot of larger enterprise companies had cornered certain regions of the world and they just did a ton of hiring out of those regions. There were well established brands in those regions back when we had this in person in Office World. Now that so much of talent can work remote, these large enterprise companies are competing for the same specialized tech talent, the same specialized knowledge worker talent as the massive tech companies. And it’s created some big challenges for them where actually the competition’s never been more fierce in terms of specialized talent.
Matt Alder [00:06:05]:
Yeah. And that’s really interesting as well, because those three things kind of all tie together, don’t they? So you’ve got more applications, you’ve got fewer smaller teams, and it’s more difficult to recruit people all at the same time. That’s quite the perfect storm.
Steve Bartel [00:06:19]:
That’s right, yeah.
Matt Alder [00:06:20]:
And do you have a sense of the. With the increase in applications, there’s obviously a big debate out there about what proportion of that is AI driven or what proportion of that is market driven. Do you have any inkling as to how that might split or which is kind of contributing the most?
Steve Bartel [00:06:39]:
I’d say both are a significant contribution, but if I had to guess, I would probably guess that a majority of it is market driven. What’s your take, Matt?
Matt Alder [00:06:49]:
I would say the same, but I think that people are underestimating the role of AI in this. You know, I’ve seen quite a few debates that people have been having and they’ve kind of sort of pushed the AI thing to one side. And I think it’s, you know, it’s, it’s not just about the tools that people kind of buy and subscribe to. It’s the fact that large language models are baked into everything that people, that people use. So it’s going to kind of make it sort of easier to put those applications in, essentially. And I think the other thing that’s kind of out there at the moment is there is just kind of so much noise about where the industry is going and everyone is talking about different ways of dealing with these problems and different technologies and all those kind of things. So from a TA leader perspective, it’s very difficult to kind of get a clear picture of what the solution might be, what the trends are, where the industry is going. From your perspective, you know, what, what are the most important things? What, what do you think is the, are the real game changers out there for. For TA moving forward? Yeah.
Steve Bartel [00:07:54]:
And I’m also curious to get your take on this. I’m always looking to expand my, my learning and understanding of the situation, but the two things that I’m seeing most often when I’m talking to TA leaders is first, folks are looking to consolidate. And that ties back to some of the challenges that we just talked about. But with folks being asked to do more with less, with tighter budgets, folks are looking to vendors that can do more. And one of the main reasons is if you buy seven, eight different products from the same vendor, whereas previously you were buying from different point solutions, you can save 40 to 50% on your tech stack that way. And so that’s certainly a very compelling reason in this environment. But I think there’s also a lot of excitement around just streamlining the tech stack and having to do a lot less swiveling between different tools. Actually, this is really interesting. I don’t know if you’ve heard this stat, Matt, but there were 160 vendors in 2015 in the TA tech space and that has exploded to over 550 today. So I think 390 vendors and 12 new categories too. There’s a whole lot of new types of tech being built as well. And so it’s a little bit overwhelming. I think TA teams are being asked to do more with less, but there’s also so much more to choose from. And I think everybody’s realizing they need to simplify and streamline their tech stack. So that’s the first trend that we’re seeing. I think the second trend that we’re seeing, especially when you think about the influx of inbound teams being asked to do more with less large enterprises competing for the same specialized talent. I think a lot of companies are looking at what’s happening with generative AI and they’re hoping that AI can help. And that’s kind of the promise of AI right now. And so a lot of folks are looking at some of these challenges that they’re facing and thinking, how could I apply AI to these situations? For example, to potentially help stack rank by inbound applicants because I’ve got thousands of them for a role.
Matt Alder [00:10:04]:
No, absolutely.
Matt Alder [00:10:04]:
I think it’s been fascinating in the last few weeks to really see all the established vendors out there properly launching AI products after so much talk for 12 months or so. So I think it’s almost less about adoption and more about people realizing the potential of what they could do with some of the enhancements to the tools that they already have.
Steve Bartel [00:10:28]:
Yeah, totally. And I’m kind of curious actually, before we, I don’t know, chat more about either of these trends, is there anything else you’re seeing from the industry? What did I miss?
Matt Alder [00:10:37]:
I think the other thing is, which sometimes sort of gets buried under all of the technology, is the focus on skills, is the thinking about skills, the move towards skills based hiring. And it’s interesting because employers aren’t really there yet and it’s something where I think everyone kind of sees the value, but there’s a long way to go. But it really slots into all of these things as part of the solution. And I think that’s the other main thing that I think is probably on people’s minds the most at the moment.
Steve Bartel [00:11:14]:
Cool. Gotcha. Gotcha.
Matt Alder [00:11:16]:
So let’s sort of drill specifically into.
Matt Alder [00:11:18]:
AI for a bit because I’m sort of really fascinated about, you know, what it’s like to be an established vendor like Gem and then sort of AI, or certainly Gen AI burst onto the scene 18 months, two years ago. What’s that been like from the software vendor perspective in terms of your roadmap, how you’ve dealt with it, new competition, all of those kind of things?
Steve Bartel [00:11:44]:
Let me tell you, it’s been wild and exciting. I think that it’s interesting. You know, we’ve been building GEM for seven, eight years now, and even before Generative AI, there was some good solid demand from the market for AI. But as a vendor that really. And a company that really prides itself in driving value for recruiting teams and making sure that every single thing we build is going to live up to expectations, we just didn’t really feel like AI was quite there yet, you know, both in terms of the efficacy of the previous way that AI was done, the previous technology, the quality just wasn’t there. But there were also some pretty big limitations with previous AI technology, including the fact that typically it could take tons and tons of training data for any given customer for the AI to get good enough to be helpful. And I think a lot of customers didn’t realize that when they were buying AI. And for some customers, they might have bought AI previously and not really seen any value at all because they didn’t even have the volume to support it. And then there’s also this challenge that AI was largely a black box in the sense that you didn’t really have any visibility into why it was making the decisions it was, or any control into the inputs. And so for a lot of reasons, we felt like AI wasn’t driving the kind of value that customers expected. And we actually stayed away from it for the first six years of the company just because we cared so much about actually driving value for customers and meeting their expectations. Now, when Generative AI came out, all of that changed. We were like, holy cow. All right, this is the real deal. It’s both really powerful, the efficacy is really good, but also it solves for a lot of those limitations with old AI models, in the sense that you have a lot more visibility into the algorithm, you have a lot more control over it as an end user and recruiter, you can actually feed prompts into it to get the desired results out. And so we got really excited about the potential and basically dropped everything to spin up a whole team around it and we’ve been making it a massive priority.
Matt Alder [00:14:10]:
Fantastic. Yeah, it’s kind of a real sense of a real sort of whirlwind in terms of what’s happened, but also getting it right. And what do you now see as the long term impact of AI on talent acquisition? How are things going to develop?
Steve Bartel [00:14:25]:
So I think that the industry is going to fundamentally change in a big way. So first of all, I think that any kind of use case that involves text, there’s going to be some really interesting applications for AI. And so obviously you’ve got things like interviews and interview recordings and speech to text and transcribing your notes, summarizing your notes, that’s already seeing some pretty big impact in the industry in terms of saving recruiters time. But fundamentally, resumes are text, job descriptions are text. You know, so much of the underlying building blocks of talent acquisition are text based. And so I think that generative AI is going to have a massive impact across a ton of different use cases. You know, the one that we’re really excited about and focused on is the ranking and matching problem. Basically take a resume or a set of resumes and help rank them against very specific criteria for a job. Like that’s all text based. So generative AI is really effective at, you know, plugging those inputs in and getting, you know, pretty good scores and rankings out. And you can apply that to so many different use cases. Recruiting, there’s obviously the ranking of your inbound, which is solving for one of those big challenges that we were talking about earlier. But there’s also ranking of all of your CRM and ATS candidates so that you can start a search with the folks that have already raised their hand in the past and you can take that a step further and potentially rank your employees as well from an internal mobility perspective so that you can fill roles with folks that you’ve already hired, which is also great for their careers. And then there’s of course, the sourcing applications of that of I’m recruiting for this role start with the hundreds of millions or even billions of people out there in the world and narrow that into the curated list of the top 50, 100 per week that are best ranked for this role that I’m recruiting for and help me actually identify that new talent that I don’t have. And so we’re really excited about all of those use cases and we’re threading those into the end to end GEM platform in a very native way.
Matt Alder [00:16:45]:
What do you think that because obviously this is all about doing massive things very, very quickly and opening up kind of new opportunities, new ways of thinking and new speeds of operating. What do you think the impact is on TA teams? How are they going to be different in the future? Sort of different structures? What do you think? How do you think that’s going to pan out?
Steve Bartel [00:17:07]:
That’s a great question. So, first of all, I think that AI has the potential to automate a bunch of the manual tedious work in recruiting, but also every industry. And so I think that as the AI gets better, as more solutions embedded into their product directly, and as TA teams start to adopt it more, we’re going to move towards this world where a lot of the manual tedious work in recruiting you no longer have to worry about. And so I think about that and I imagine that world. And first off, I’m really excited about that. I think that it’s going to free up recruiters, RCs, sourcers from all of that, you know, manual scheduling, manual sourcing, and allow everybody to focus on, I think, why we got into the industry in the first place, which is to build relationships with talent and help, like be a strategic partner to the rest of the business. And so I’m really excited about what that means in terms of freeing up time so that the role of the recruiter, the sourcer, the RC can be a lot more strategic. And what I think that means is folks are finally going to be able to focus more on delivering an exceptional candidate experience. I think what that means is recruiters are going to start to think more like business owners and be looking at a lot more data, being a lot more data driven, taking that data back to other stakeholders in the organization and showing up as like a trusted partner and more of a strategic partner to the rest of the organization. And overall, I think it’s just going to be, be have a wonderful impact for the industry.
Matt Alder [00:18:49]:
I mean, already at the moment, the technology is fundamentally doing different things to what it was doing even two years ago. And there’s just all kinds of hype flying around about what’s possible, what people should be doing, all that kind of thing. What should buyers beware of within all of this? Because obviously there’s legislation, there’s all kinds of other risks out there. What do you think people should be most aware of when they’re looking at this whole new world of products and possibilities, abilities?
Steve Bartel [00:19:20]:
Ooh, that’s a good one. Because with all this promise, with all this excitement comes a lot of hype and it’s hard to Know what’s real and what’s not. So actually Gartner has this whole concept of a hype cycle. Have you heard of the hype cycle?
Matt Alder [00:19:34]:
Yep, absolutely.
Steve Bartel [00:19:35]:
So you’re well versed in that. But for our listeners, it’s this idea that for any new major technology disruptor, there’s this excitement curve. And it starts with the phase of high expectations where everybody’s just really excited about the potential of this technology. We don’t quite know what all the real use cases are going to be yet. So folks are throwing it at everything. And I think people are maybe overexcited about what it can achieve. Now there’s still like a ton of real stuff there, but it becomes really hard to separate the noise from the signal just because the industry hasn’t quite landed on like, what are the, what are the top 5 to 10 killer use cases of this technology? And folks are trying out 50 to 100 things. So how do you actually find the 1 in 10 solutions that are actually going to drive value and be real? It’s really challenging. And just so you know, like, next comes the trough of disillusionment where everybody gets burnt out by trying all these different AI tools and most of them don’t, don’t work, aren’t there yet, or maybe weren’t even real use cases to begin with. And so, so how do TA leaders avoid that? I’ve been thinking about it a lot. I think there’s a few things, like a few things folks can look for when they’re, when they’re evaluating AI today to like help avoid, you know, buying some of these solutions that may end us up in the trough of disillusionment. And I think that the first thing is to actually really understand whether the tech that underpins these different AI products is actually built on the new generative AI disruption. Because I think one of the things that’s happened is there’s been so much buzz and hype around AI that vendors from two plus years ago who have always been selling AI and maybe selling a little bit of AI that doesn’t quite work as well as well as it should, they’ve been jumping on this hype cycle, kind of selling their old AI technology to folks that don’t quite realize that it wasn’t actually built on the new stuff. And so I think that’s like thing number one. It’s actually pretty easy. You can just ask what underlying models folks are using and are they using any of the new gen AI models, But I don’t know that everybody’s thinking to do that. I think that the second thing that folks can do is think about the applications we were talking about earlier, how generative AI is good at anything that’s text based. And so if the use case doesn’t involve text, fundamentally that might be a little bit of a warning signal for, hey, is this actually going to drive real value? Is it actually going to work? I think third thing that folks can do to separate the hype from the noise is to try to run a trial. One of the challenges that we’re running into with AI right now is that it’s very easy to demo it demos super well in a controlled environment with specifically the right prompts. Right. But then when you put the AI in the wild in the hands of like recruiters, they’re going to do all sorts of things because it’s the real world and it’s hard to know whether the AI is actually going to work for real applications and use cases unless you get your hands on it. So I don’t know. I think in terms of avoiding the hype cycle right now, those are some things that buyers might want to think about.
Matt Alder [00:23:20]:
Yeah, it’s really, I think that’s fantastic advice and it’s interesting in terms of the hype cycle this time because it just feels like we’re going through it much quicker than with other technology. Because thinking back just sort of, we are almost two years ago now, there were very respected tech commentators making statements like everyone will be out of a job in six months time. That level of hype was. It was kind of extraordinary. And I think that, yeah, I think the kind of. The risk is that as people do perhaps get disillusioned with the abilities of some of the things that they’re finding, they’re actually missing the bigger picture that actually things are fundamentally changing and are going to change really quickly. So I think it’s a really. Yeah, it’s a really interesting and confusing time for people, definitely at the moment. Yeah, so you kind of alluded to this already, but a few weeks ago I was recording interviews on the GEM stand at HR Tech and we did a whole episode based around recruiting nirvana. So asking people what they thought was possible, what the future might look like and what they hoped recruiting would look like in the future. Now you. Moving forward now, you’ve given us some thoughts on this already, but perhaps as a summary, give us your vision of recruiting nirvana. If this all works out brilliantly, where are we going to be in a few years time?
Steve Bartel [00:24:42]:
Yeah, and I think we might be there even sooner than a few years time. I could see us being there in the next 12 years, but I think that recruiting is going to be a whole lot more efficient. I think that TA teams are going to have to juggle a lot fewer tools. Everything’s just going to feel so much more streamlined. I think that as a result there’s actually going to be such better data because today when you’re juggling so many different tools, you have all these different data silos. Things aren’t really truly writing back to a single source of truth. And so there’s going to be better data that’s going to allow TA teams to be more data driven. And then I think maybe the biggest thing is just I think that the promise of AI will actually be delivered on in terms of automating a lot of the manual tedious like worst parts of the jobs. So manual sourcing, manually reviewing thousands of applicants, manually writing down your interview notes and it’s going to allow TA teams to focus more on the strategic parts of the job. And so yeah, I’m really, really excited for that and what that world’s going to look like.
Matt Alder [00:25:51]:
As a final question, how do we get there and what kind of happens in the short term? So we’re recording this right at the end of October 2024. It’s going to be 2025 soon. TA teams are planning and preparing. What should they be thinking about and how might they make the first steps to kind of move towards that?
Steve Bartel [00:26:14]:
Well, I think a very simple first step on that front is to go out there and take a look at a few different AI applications and what some of the leading vendors are doing in those spaces. Obviously that sounds pretty self surfing, but I don’t mean just gem. There’s a lot of really cool, impactful things happening outside of some of the use cases that we talked about with gem. I think for example, on the call intelligence and interview side of the house, I’ve heard great things about some of the stuff that’s happening over there with transcribing interview notes, with summarizing those calls and we’ve seen that have a massive impact for the sales space with companies like Gong and such like things like that. So you know, I think, I think there’s some really exciting things happening, you know, obviously on the AI ranking and matching side of the house. But you know, I think as we’re right at that perfect time, end of year where budgets are being decided, so carving out something to take that step in the direction of implementing AI across a few different use cases for that first year. It could even just be a mission of like, let’s figure out what works. Let’s figure out what some of those real use cases are so that we can double down on them in the following year and fundamentally transform our team and what we’re able to deliver.
Matt Alder [00:27:38]:
Steve, thank you very much for talking to me.
Steve Bartel [00:27:40]:
It’s been great to be here. Thanks for having me. Matt.
Matt Alder [00:27:43]:
My thanks to Steve. You can follow this podcast on Apple Podcasts on Spotify, or wherever you get your podcasts. You can search all the past episodes@recruitingfuture.com on that site. 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.
Matt Alder [00:28:05]:
Thanks very much for listening. I’ll be back next time, and I.
Matt Alder [00:28:09]:
Hope you’ll join me.
