The Breakthrough Hiring Show: Recruiting and Talent Acquisition Conversations
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The Breakthrough Hiring Show: Recruiting and Talent Acquisition Conversations
EP 169: What’s Next for AI and Automation in Recruiting: Insights from Jason Heilman, Sr VP of Product, Automation, and AI at Bullhorn
Jason Heilman, Senior Vice President of Product, Automation, and AI at Bullhorn, and our host James Mackey, offer a masterclass in AI and Automation for recruiting organizations. Drawing from Jason’s experience as co-founder of Herefish (acquired by Bullhorn in 2019), Jason reveals how automation serves as the essential foundation for effective AI implementation in recruiting.
While many companies experiment with AI tools, Jason emphasizes focusing on core recruiter functions - particularly candidate matching and screening. These high-leverage activities not only boost efficiency but also create measurable competitive advantages. Bullhorn's data shows a striking 36% productivity increase for recruiters using automation tools compared to those who don't.
Bullhorn report: HERE
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Hello, welcome to the Breakthrough Hiring Show. I'm your host, James Mackey. We got Jason Heilman with us today. He is the Senior Vice President of Product and Automation and AI over at Bullhorn. Jason, thanks for joining us today.
Speaker 2:Hey, james, excited about it, my pleasure.
Speaker 1:Yeah, really excited to have you on the show. Just given your background and what you're doing right now, I think a lot of people are going to be very interested in learning more about how Bullhorn is approaching automation and AI, just as an industry leader and a company that everyone is very familiar with, both in-house teams and staffing agencies. And, of course, bullhorn has been an incredibly successful company, arguably one of the most successful, if not the most successful, applicant tracking system and, I'm sure at this point, a much larger product suite than down the pipe applicant tracking. So, before we jump into some of the interesting use cases related to AI and how Bullhorn is approaching it, it would be great for our audience to learn a little bit more about you and understand your background.
Speaker 2:Yeah, absolutely, and yes, we definitely excited to offer the whole recruiting solution space through Bullhorn, and that's very much tied to my background. So I've been in the industry almost 20 years now, starting off at another competitive applicant tracking system and been working just in staffing for this whole time. But the probably most recent and relevant experience I was the founder co-founder of a company by the name of Hearfish, which is essentially recruitment automation. It does automation in the staffing industry. We started that in 2014. The idea there is very closely related to where we are today, in 2025, which is to say that in staffing, in any type of hiring, you get a massive amount of interest and only so much time to dedicate to responding to that interest by human. So let's just take the most obvious example Whenever you open a job and you get 400, 500, 1,000 applicants, there's no world where every one of those applicants are being looked at by a human. We all must be honest with this. But there definitely is, and always should have been, a world where those applicants at least get a response back from a system letting them know that you've gotten their message or you've gotten their interest and can respond back about if they're not going to be a good fit and let them move on with their day. So that's really where we started is. We knew staffing firms needed the ability to quickly communicate and just better engage with their applicant pool and their clients. So that's really what Bullhorn Automation now formerly HearFish was all about candidates and their customers by automating kind of some of the lower value touch points that, for a staffing firm, are low value, but for the candidates and contacts, it's very important that they hear from them.
Speaker 2:Bullhorn acquired HearFish in 2019, really built on the baseline of continuing to do what we'd always done, which is help people to create a better experience, but also knowing that, as the world was continuing to evolve, every staffing firm is going to need to add automation, and where that's led us to today is that automation is really the foundation that's necessary to take full advantage of all of the AI capabilities that are happening today. Which takes us to where we are today, where, at Bullhorn, I oversee our automation and AI initiatives, and that's very intentionally very closely held together, because you can have automation without AI and still have a great business even as we continue aggressively down this AI driven future. But you can't really have AI without automation. You need control, you need to be able to scale those solutions. So that's what we're doing.
Speaker 2:We're working on a lot of exciting stuff, but I want to turn it over to you for a little while, James, because I've been monologuing.
Speaker 1:Oh no, it's a really helpful introduction. So thanks, and just so I understand the lay of the land with Bullhorn right now, are you still primarily working with staffing agencies or are you building and breaking into other industries as well? Are you supporting in-house teams at this?
Speaker 2:point. No, we are very much focused on only staffing, with one minor exception, which is we recently acquired a company by the name of TexKernel. Probably just about anyone who listens to this show uses one of their solutions, likely through parsing, so they're the global leader in parsing. Just about every resume that goes into an applicant tracking system runs through a text kernel solution, so a number of our partners on the corporate ATS side use that solution. So, with that isolated, unique part of the business, everywhere else it's staffing and that's very relevant because one of the areas where AI is always the most valuable is whenever you've got a unique and very large data set and that kind of helps you. That's why you mentioned how Bullhorn was large and we serve a lot of staffing firms. The reason that's good for people is that allows us to deliver solutions on kind of this unique data set that's very specific to staffing and all about how the process works and when we see success, how we can use AI to replicate that.
Speaker 1:Yeah, absolutely. And so for staffing companies, where do you see the highest leverage opportunities for automation and AI right now?
Speaker 2:Yes, absolutely what we did. So you know everyone whenever the chat GPT moment, right when it came out and everybody was so excited about everything that it can do, we share that excitement, of course, but we all went through this kind of learning process of everybody very quickly brought out tools that helped you to write emails better, helped to summarize resumes, helped to do some of the things that we would call around the edges that a recruiter does on a regular basis and help them do the things that they do a little faster, maybe a little better Although now, looking back at GPT 3.5, I don't know if it was that much better. But where we've evolved to with our customers is, rather than working around the edges, we really want to go to the heart of what recruiters do all day, every day that they maybe don't need to anymore. So kind of the biggest two areas. There's a bunch of nuance in actually delivering it, but the biggest two areas are a job opens I need to find the best candidates right, like in my database, or externally. So that was the first big area where we're applying a lot of AI. And again, this isn't chat GPT style AI, right, you don't. You can't have a job and do matching against a database of millions of people with an LLM. So this is a whole different class of AI which we probably don't need to go into, but that's a really important one and I would say over the 20 years that I've been working in staffing, that was the first, second, third and fourth and fifth reason, or the thing that people wanted from AI Helped me to better find better candidates more quickly.
Speaker 2:This has been a problem that's existed for 20 years and AI was always the potential solution, but I think we've really gotten there now. Some of that is through some of the recent advancements. It's also again I described it like we've got this large data pool of all of our customers so much staffing, specific information. So that's one big area is helping recruiters to find the best people quickly, still giving them the control if they want it, or allowing that to work fully autonomously. So, as soon as a job opens, finding the best people, sending messages or letting the recruiter click a button to see it. That's one thing, and then the next really big part of it is all around screening. Earlier, I described how you get 400 applicants, 500 applicants, whatever it might be. Today, everyone could probably see that actually those numbers are way up because the job boards have done a really good job of making it very easy for candidates to express interest in a role and apply to a role. That does not make a staffing firm's job any easier. That makes it much harder.
Speaker 2:I read an article the other day on Reddit. Someone was talking about how they applied to 13 or 1500 jobs and their point was how they only got five interviews or whatever it was. The message they were trying to tell in their story was how little feedback they got. What I read from that is that person applied to 1500 jobs in two weeks. How interested were they in any of those jobs? How much time could you have spent actually evaluating them?
Speaker 2:Our customers need tools to help evaluate the people who can very quickly express interest. So that's. The other big part is screening and, james, I know you can speak to this too. When a candidate comes into the database, ai is a great solution where they can call them and have an actual voice conversation with someone to just validate that they've got some of the specific key requirements whether that's location, pay, whatever that might be but then also have an open-ended discussion with them about the job and about their experience. So I think we could probably spend a lot of time talking about why that's valuable, but that's the other big area is helping to screen out the very large pool of potential talent and only surfacing the most qualified and most interested to the recruiting teams, again, just to allow them to focus more where they're better.
Speaker 1:So really attacking the top of funnel, where it's the most leverage and time consuming, and allowing recruiters to essentially operate more so down funnel as much as possible? Yeah, that's, of course, like the use cases surrounding top of funnel is something that I've been really dialing in and focusing on for for quite a while, both with June and then our guests that we're bringing on the show lately, and so I'd love to dial in a little bit more on some of those use cases. Initially, you're saying we were talking about what are. The constant problem is finding people quickly, the right people, good candidates, and so I would love to learn a little bit more about the specific products and we can talk about evaluation and screening in a minute, but more so, what other products is Bullhorn offering to help companies, staffing firms, identify talent faster? I don't know if there's like from a sourcing standpoint, or is it like inbound, or are we talking candidate rediscovery?
Speaker 2:possibly it's a great call. Yeah, it's all the above. I think we can probably pretty quickly break it into three, maybe four buckets. Let's talk about the obvious ones first. The first is a new applicant applies. They go into the system however that comes in. Then we've got solutions which allow teams to automatically or more easily search external sites and their own right. I can, from a single interface, search all the different job boards in addition to my own database, and when we do that we can also set up kind of agents in the background to say, okay, I regularly get project management roles, so I don't want to have to go look all the time for project managers. I just want it to automatically run searches and either alert me whenever it finds good matches so you're the first one as soon as they pop on the job board or just add them to my system, just add them right in. So I think that's what was that. That's buckets one and two.
Speaker 2:Then I guess the third would be automating the process of just staying engaged, and this was one of the big areas that we focused on in Herefish with automation is just so often we talk to our customers they're very proud of the large database that they built over time but then whenever you go look at the database it's neglected.
Speaker 2:It's great that you have a million candidates, but if you haven't talked to any of them in the last two years, they really have a relationship with you. So just continuing the process of nurturing the talent pool and actually building these talent pools and not just trying to hit them for jobs, so that's another big solution. Let's just take a traditional. Let's just say you just send a monthly newsletter, right, like just staying engaged with your pool and obviously now there's more interesting things you can do than just a newsletter but just staying engaged. So that helps customers to really craft their own talent pool that is unique to the job boards or unique to what other people see in applicants. So those are big. I think buckets I guess it was three, that middle one about internal and external search, maybe you could bucket into two. So I think those are the big areas.
Speaker 1:Yeah, for sure, and I'm just curious so the staffing companies that you would consider more so likely to be early adopters of this type of technology Are there any market segments that you're really standing out to? For instance, is it SMB, mid-market enterprise? Is it staffing agencies that specialize in certain industries? What are you seeing out there? It's funny.
Speaker 2:I don't have an answer like that, because everyone is obviously dedicating a lot of resources to AI, right? Everyone sees this opportunity In our largest customer base. We've got some of the global public staffing companies who have dedicated a large amount of resources to making this happen, all the way down to. We've got some of the most innovative companies that have five internal employees the number one difference and, by the way, and also across industry light industrial, healthcare, professional, commercial, however you want to frame it all of which are seeing success. The differentiator, though, is it's really it's two things, to be frank. It's, right now, having an executive owner that has the ability to to actually put these changes in place. That's from looking up and making sure that they've got support from their board and the rest of the C-suite, and also looking down that they've actually got the ability within their organization to do change management, because it's a big, has the potential to be a big change.
Speaker 2:There's ways to do this in what feels like an evolutionary way, but companies that aren't great at rolling out new solutions. This is nothing new about that. This is a new piece of technology that your recruiting teams should be on board with, unless you're going fully recruitalist, which is like another discussion which I think we should. We can talk about, but let's pause that. Let's just say that this is a world where you do intend to take an existing team and really grow their capabilities, rather than completely displacing it. So just being able to roll it out and then, if the other one is that executive or that executive's team, the ones that actually are deeply involved in the process, so not only having the buy-in and getting to both directions, but just actively in with a team and having a team that can iterate, because the idea with these is they will work.
Speaker 2:It has been proven. These AI solutions 100% work in staffing, but they may not work out of the box. You may need to go in and iterate on it and adjust your messaging to improve your conversion rate of people actually taking screens, adjust your matching criteria to make sure that it's either tighter or wider. So there's a lot of different potential ways that you can A make this your own, but, b actually achieve the success that we want. So that makeup it's really about the humans is the recipe for success. It's not about the industry. It's really about having the right people and the right team that's dedicated to seeing success.
Speaker 1:Yeah, for sure, and we actually. We recently had Hugo Milan on the show. He's the president over at Kelly Services. He runs their entire engineering division. I think it's like a $400 million division for Kelly and we spent a lot of time talking about just the state of the staffing industry and he was talking about essentially a contraction right in staff augmentation, services primarily, and he had a pretty interesting take on why this is happening. By the way, for everybody listening and Jason, if you're interested, it's, I think, probably the last episode we actually released. It was pretty cool.
Speaker 1:So one thing that just came top of mind is what are your thoughts on the correlation between companies adopting AI solutions and staffing and the relationship between that and the staffing industry being in essentially a recession right now? I could see it going either way, where it's like, okay, we have to be more efficient, right, we're already service like staffing companies are already services companies with tight margins. They're not software companies, right, so they have to be mindful of that. So you could see, okay, they're going to be driving more toward this type of technology, probably even faster. Or you could say they have budget budgetary constraints, right, they're not really thinking about adding on additional software. What correlation, if any, are you seeing between those two things?
Speaker 2:Yes. Okay, let's first talk about, I think, the market as a whole and the contraction in the current state. So I think, like last year, sia put out their study. I think across the industry there's pockets where it's different, but essentially the staffing industry took something like around a 10% compression Pretty brutal right. Yeah, not great percent compression Pretty brutal, right. I guess.
Speaker 2:One question to answer flat out is how much of that is due to AI from their end customers. I would say that's roughly zero. Like I do not think. Yeah, I don't think. Yet at least People that use staffing, they're not using staffing because they've got such great AI tools, because most of those, you know that. I don't think. That's it.
Speaker 2:So then we go to, okay, the staffing suppliers how or, I guess, the suppliers, the staffing companies, how are they implementing and what success are they seeing? And I think what we are seeing is there are still companies that are growing. They're taking share from the companies that aren't advancing as quickly. It's pretty flat out, Like we can see, for example, we have a pretty explicit study that we've shared widely. Like customers that use automation here at Fish Bullhorn Automation and other automation solutions not just ours that we offer, they're 36% more productive than those that don't. So each recruiter half the company using it hires 36% more candidates per recruiter. So that's how we gauge the productivity placements per recruiter Pretty simple metric like that doesn't take into account margin or anything like that. So that's our first step. So those companies that 36% wasn't due to a growth in the industry, that 36% came from where they beat other suppliers to their mutual customers. So that's what we're really seeing is like it's a little bit of a story, a tale of two cities where those that are aggressive and implementing solutions even if it isn't the latest AI solution they're the ones who are still growing.
Speaker 2:We've got a large contingent of our customer base who is growing. They are adding seeds. We are. They've got their finances running through our system. They're making more money. Their margins at the top line are increasing. You can see it all the way down to the very bottom line.
Speaker 2:So that's what we're seeing. It will be a market of winners and losers and there'll be a middle period, and I don't know if we want to go one step farther, but where this naturally will go, if we look backwards at previous cycles, is these people that are winning to come in and start to take business by offering lower markups and lower rates to the customer. So then that becomes a double-edged sword where not only are those customers who aren't able to deliver at the lower cost profile are losing the business they already have, they're going to start to lose logos to those that can supply at a lower rate, and then the whole industry. This is natural price compression. We hope it doesn't happen, but it feels like that's probably going to happen when our customer, when the buyers of staffing services, start to see that there's enough suppliers that can offer a lower cost basis.
Speaker 1:Because of automation and AI. Essentially, the recruiters are more productive and so they're able to undercut. That's right, and just due to staffing, industry is just so insanely competitive, right, there's just so many out there.
Speaker 2:And so think, if you're a 20-person staffing firm, that's very motivated, you want to grow and you have any deal where you might lose it by dropping a margin percentage, you're going to take that deal because your net at the end of the day is still high enough to support that business, to deliver at a lower rate. And then, especially, every company has it where you've also got the already incredibly low margin business and then so much business that you aren't servicing today Our best in class customers maybe have call it a 25 or 30% fill rate. That's 70% of the roles that you aren't hiring and it's likely, because you don't have, you can't effectively deliver to those customers, given your current cost profile. Maybe you work it, but not really you don't put your best on it. Maybe you outsource it. That business can now be further driven down your own cost basis. I don't know. I was going to try to keep a very cohesive answer, I feel like I've gone a little far.
Speaker 1:All the extra context is it's really helpful? Yeah, it's. It's really interesting to think about how it's going to impact the competitive landscape of staffing and I think you you made a really good point, right, it's the in order to grow. Particularly, it's always it's hard to grow any staffing company and essentially any market because there's so much competition, right. But beyond that, now when you're looking at a market contraction, right, it probably will force early adoption by agencies if they do want to compete, and I think there's a lot of companies and staffing that are really old school and probably will not change and they're probably going to get left behind, right.
Speaker 2:Yeah, it's going to be tough for them. I will say though I will hedge it a little bit with this isn't happening tomorrow. So to throw a little bit of maybe numbers into the context, we recently did a survey of a large our grid survey and 52% of our customers are evaluating and testing AI solutions. Only 15% have purchased and implemented and seeing benefits from AI solutions, so pretty early. And, by the way, that 15% source and match. So like the ability to automatically run searches and find candidates. Of that 15%, that was like 70% of it.
Speaker 2:So it's also not even all this new stuff like the screening, like the hyper-personalized messaging. It's things that have been around for a little bit longer. So this isn't gonna happen tomorrow, but there is gonna be. Let's pretend like it's two, three, five years, whatever that window is, before the serious compression starts. Some people are gonna make hay like there's gonna be some companies that grow like crazy or reap massive margin benefits during that time. But I don't know In my mind, given the previous technological changes and all the humans involved in staffing, this isn't going to happen overnight. I don't know if maybe five years is overnight, but it's not like next year. It's not like this year where, all of a sudden, the whole market dynamics shift.
Speaker 1:Yeah, it's going to take time. I think you briefly touched on this earlier. It's the first couple of years people after ChatGPT came out, people are just essentially experimenting, trying to figure out which use cases essentially are actually creating real value versus maybe not quite as much. I think sometimes some of the tools or products that have been created were really just shifting where you're doing the work. I don't know how much they were actually driving productivity per se, but I think, like we're, you know at least folks that are leading the charge right, like people such as yourself. At this point we have a pretty good pulse on what's driving real productivity and the use cases, that customers are becoming a little bit more educated right and starting to really figure out where they can, where they could, drive outcomes. You shared that stat about 50% of staffing companies, I think you said experimenting with AI, and then 15% actually driving value or having found it implemented, a use case that's really like just they're paying for it and rolled it out enterprise Okay.
Speaker 1:I got it I was reading in the Wall Street Journal is something like overall in the US economy, 61% companies are experimenting with AI, but I think it was like less than 6% have actually rolled out an application that's generating like real ROI, tangible value for the organization, which is pretty wild. It's a very small, so there's still a lot of education in the market. That needs to happen too. Yeah, it's going to take time.
Speaker 2:I want to pull one thread from what you just described about how, when people add these solutions and it just moves the work, tie that back to earlier, what we talked about how, where we're seeing success, and it's all about the leadership in the actual companies that are driving it One of the number one things that must be done. So let's take the old world versus the new world. So let's pretend like a recruiter has 10 actual live conversations a day. Hopefully it's more than that, but let's pretend like it's 10. Today those conversations are at least half of them are talking to people that aren't qualified, that we just throw in the trash, right, we re-engage them and we find out right, but we don't use them for that day or that month. And then we talk to a few that are okay and then two that are awesome.
Speaker 2:Now imagine the world whenever every candidate you talk to has been pre-screened, already found time on your calendar. So let's pretend like they still only have 10 conversations. Every one of those should be someone that's a good candidate and qualified, but not all for one job. So in the old world, I'm talking to 10 people to fill one role. In the new world, I should be talking to 10 people to fill three or four roles.
Speaker 1:You need fewer candidates, because they're already qualified and good.
Speaker 2:So then, what does that mean? So I, as a staffing firm, in order to achieve that outcome, had to spend money to invest in solutions to get that. You're investing so you cannot have the recruiter's metrics remain the same. You can't still expect them to build the same margin, because it's going to be way If you make it so that they have to have the same criteria to make a comfortable lifestyle.
Speaker 2:Sure, there's going to be some that go above and beyond and absolutely crush it and make a million dollars a year or whatever, but the norm is they're going to just go back to a comfortable place and let's pretend like you need to add five, three new starts every month. Even they have all these tools, they're just going to keep adding three new starts, unless you expect them to add six. So that's the other part. To drive change and to actually drive it, you need to have confidence in actually that these tools will work and change their outcomes and change the metrics that drive it, and that's a hard change Recruiters do not want to hear, yeah, your requirements are doubling.
Speaker 2:To make the same amount of money, you have to have a lot of proof points. There's a lot of change management that goes into it. So that's the part of the transition. That's where it can get bumpy and where another area that we have to watch to make sure you get the outcomes you want.
Speaker 1:Yeah, for sure you should be evaluating and tracking exactly how much this is truly impacting revenue. I'm curious so your customers, are they primarily looking at these technologies more from a boosting revenue perspective, or efficiency or margin bottom line? What is driving them to the purchasing decision? That's an excellent question.
Speaker 2:So the short answer is that we think most want to ultimately increase the top line, drive more revenue, expand their business. Right now, though, given the market conditions and everyone's internal cost cutting that they're forced to go through, sometimes they go into it looking at it for that as an opportunity. So it's a little bit of a blend. There's a little bit of short-term pain that people are feeling right now that maybe forces them to look a little bit more inward and look at ways they can cut costs, but ultimately, everyone knows they're actually investing in these solutions to more rapidly grow and better serve their customers, and that's a really big part of it. Even if you aren't using these tools to add new logos, wouldn't it be nice if you were actually just making your customers that already exist today much happier with you being the platinum supplier, right Like getting all the awards and value that accrues from just doing a better job, but with the jobs you've already got today?
Speaker 1:Yeah, for sure. Look, Jason, we're coming up on time here and I wanted to see if there are any other topics or anything else you want to mention about what you're doing at Bullhorn that you want to share with the audience.
Speaker 2:I don't think so. The only other thing that I think is always very important we just talked about how we can make customers happy by backfilling. The only other thing that I think is important I think you can speak to as well is just what about the candidate's experience? Is this better, worse, the same? We've got data that talks about how candidates are very much ready to adopt AI. We don't live in this utopia where every candidate gets responded to. If we did, AI might make it a little more rocky, but we know today they want faster response times, they want to get to work faster, and AI can actually help them to achieve those. So I guess that's the other interesting part is, it's not about putting your work on the candidate and sacrificing that. It's actually this helps you to deliver a better candidate experience.
Speaker 1:Yeah, it's a much better candidate experience and it's honestly speaking with folks even in staffing. A lot of people do think it's going to hurt candidate experience and it surprises me a little bit because it's like getting into the evaluation tools that we're both building pre-screening conversations Folks come inbound to provide recruiters with qualified candidate shortlists and speak to folks that are actually qualified. A lot of people are worried that candidates are not going to want to engage with this technology, but to me it's like it's so valuable to you apply to a job and you immediately get a call or a text to engage you in the interview process. I'm in the headspace, I just applied to the job, I'm in front of my phone, I got my phone on me and my computer. I'm available essentially and you can move a lot faster.
Speaker 1:But the other thing that's curious is and it does make sense to be concerned about this we need to be very careful. But the ideas of AI and bias, ai discrimination and I think generally there's just an education that needs to occur on how generative AI actually works versus AI models. Potentially in the past that more so operated in a black box where it was harder to see why it was making certain evaluation decisions, but I see the tools coming out right now. Certain evaluation decisions, but I see the tools coming out right now, like the ones we're building, as something to actually create less bias processes. I think people are a big issue when it comes to bias right, so I think these technologies actually can level the playing field and create a much better and more fair and equitable process for people.
Speaker 2:Absolutely. It's very hard to change how millions of people go about their Absolutely. It's very hard to change how millions of people go about their day. It's very easy to tell a computer how to operate. Even the challenges that everyone's heard in the news stories in the past, it's because the way those models were built is. They replicate previous human behaviors, so all that they're doing is continuing to push out more and yeah, and then the other part. I think that's really important.
Speaker 2:We talk about the candidate experience is, today all the decisions are made based on a piece of paper and everyone knows on a resume, right? Everyone knows a resume can never reflect A you as a person more holistically or B your specific qualifications for a given role. These screening solutions just allow them to tell more of the story, talk about why they're a good fit, and I'm sure you've seen this. There's been very many times when someone's been a relatively low resume fit but then have gone through a screen and they've been a perfect match for that role, because the maids are not effective at actually telling a story about how good of a fit you'll be for a role.
Speaker 1:And particularly, I think, maybe some industries more than others too. Folks may not really have great resumes, so it's just having a level of clarity you could get from a screen is, I think, a lot more valuable. So we're definitely on the same page there. Yeah, for sure.
Speaker 2:And again, just maybe. One very last thing. We've got some stats like those screening ages. Again, is it weird to talk to an AI person? I don't know, Maybe, but it's going to be the new future and it isn't.
Speaker 2:If you've ever done one of these, Maybe in this thing I can put a link to your screener or somebody's screener so people can experience these. They're actually really good and it's funny when people are having these discussions they talk like they're talking to a person. They're like, oh, that's a good question, or sorry, I didn't hear that, Can you repeat it? And this is the human talking to the AI. And then whenever I'm sure you do this we do surveys after every single screen to say how their experience was, and they're overwhelmingly positive 82% give an 8, 9, or a 10. And I think this is important, but that's 82%. There are some that give a one and a two and it's actually pretty polarizing. The ones that give the low scores. It's usually.
Speaker 2:I don't think AI should be doing hiring. I don't want to have my future. They've got very opinionated, dogmatic concerns and I want to bring that up. Whether that's valid or not, every customer that implements one of these is going to have a recruiter that tells them a story about a candidate who reached out with this opinion. But we just have to weigh in the counterbalance of that's a very small subset that's 2% Whereas the vast majority really actually like the experience. So there are going to be some that don't love it, but that's anything in life.
Speaker 1:What it reminds me of is back in the day, when there's a lot of industries, right Even like when it comes to buying stocks where you used to have to essentially speak with a salesperson early in the process, and remember when a lot of that went online and became automated, a lot of stockbrokers and people would say, oh, they need to speak to us, right, they're not going to be interested in working through automation.
Speaker 1:Think about just how many industries have made that shift, have made that shift. And it's the same thing. Like, people don't necessarily want to speak with somebody early on. If they could just do the screen and get a little down funnel, let's see if it's actually worth the time. Scheduling an interview and then also these screen products are also good for candidates to be able to ask questions too and learn more about the opportunity. So the idea that people want to speak with people early on, it's not necessarily people want to speak with people early on. It's not necessarily they want to speak with somebody if they know it's a relevant opportunity. Nobody wants to waste their time and you get scheduling and rescheduling and it's just, but that's also making the assumption that ever has that that's happening today.
Speaker 1:Like that is the difference.
Speaker 2:Like the stockbrokers, had a very vested interest in calling a bunch of people and trying to sell them. But we don't have. Let's pretend like only 100 people apply to a job. 95% of them are never going to have a conversation. They don't even get the chance to have a conversation.
Speaker 1:Yeah.
Speaker 1:So it's yes it levels the playing field and you're right, it gives folks the opportunity to talk about their skill set that might otherwise have not been reached. So I think people are going to come around and it's from a product perspective. It's important for us to be building products of the future and clearly things are going to go in this direction and people are going to become more comfortable with it over time. There's always going to be people that, regardless what you do to the hiring process, they're not going to like it. People don't like it if you don't like getting turned down for jobs. So there's always going to be some negative feedback, regardless if it's people or AI or anything else. Yeah, yeah, going to be some negative feedback, regardless if it's people or AI or anything else. Yeah, yeah, jason, thank you so much for joining us today. This has been a lot of fun. You've shared a lot of great insights with our audience today, so I know everybody will have learned a lot. I really appreciate your contribution to the show.
Speaker 2:Absolutely. Thank you so much for having me and excited to talk again.
Speaker 1:Yeah, absolutely. You're welcome to come back on anytime.
Speaker 2:Nice.
