The Breakthrough Hiring Show: Recruiting and Talent Acquisition Conversations
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Join our host, James Mackey, and guests as they discuss various topics, with episodes ranging from high-level thought leadership to the tactical implementation of process and technology.
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The Breakthrough Hiring Show: Recruiting and Talent Acquisition Conversations
EP 156: Leveraging AI for phone screens and evaluations with Aaron Wang, Co-founder and CEO of Apriora.
James Mackey and Elijah Elkins sit down with Apriora’s Co-founder and CEO, Aaron Wang, to discuss how their product delivers and evaluates on-demand phone screens to applicants.
They discuss the similarities between autonomous cars and AI interview evaluations and explore whether AI products should focus on co-pilot functionality on screening calls or if new AI products should remove the need for recruiters to be present on the screening call, allowing the recruiter to only engage with talent that AI approves.
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Hello, welcome to the Breakthrough Hiring Show. I am your host, james Mackey, joined again by my co-host, elijah Elkins. Elijah, what's up? I'm doing well Good. We also got Aaron Wang with us today. Aaron is the co-founder and CEO of Apriora and he's gonna tell us a little bit about his product today. Thanks for joining us.
Speaker 2:Excited to be here, james and Elijah. This is gonna be fun. Yeah, excited to be here, james and Elias, this is going to be fun. Yeah, it's going to be a good one. So I guess, to kick us off, we'd love to know, just like the high level about your product and a little bit about you, like how you came to start the company and where you are today. Sure, aprior automates phone screens and live video interviews with an autonomous recruiting agent, and so we help enterprises and staffing firms conduct thousands of interviews every day and help those recruiting teams better understand.
Speaker 2:You know, out of the hundred people that applied, out of the thousand people that applied, who are the top 5% that I should really be speaking to and investing our recruiters' time with? And so that's a little bit about the product and what we're trying to build, nice, nice. And so you started the little bit about the product and what we're trying to build.
Speaker 1:Nice, nice, and so you started the company about two years ago.
Speaker 2:Yeah, it's been about a year actually since we initially built it and since then we've been growing and scaling like crazy, and so it's been a fun ride.
Speaker 1:Okay, cool, nice. And so what gave you the idea to start this company?
Speaker 2:Like what inspired you? Yeah, start this company. What inspired you? Yeah, we had built another startup in a similar space, in the interviewing space, tailored towards candidates, and through that experience we had found a graveyard, if you will interview automation tools and learned a lot about the different parties within the hiring space. Lot about the different parties within the hiring space, the hiring manager and the candidates, the interviewer, the staffing firm and what all of these parties incentives are and what they care about. And with the advent of mainstream generative AI, now is a time when you actually can create extraordinary value for all of these parties a lot by new technology.
Speaker 1:Nice, and I saw also that you have a technical background right as an engineer, and then you're also a VC. You do some investment right.
Speaker 2:I do some investing. I wouldn't say I'm a VC myself, but I'm a venture partner at Pioneer and do some investing on the side.
Speaker 1:Okay, awesome, awesome. We're really excited to dive into your product. I'm actually really interested in this use case, so I'm excited to learn more here. I suppose, just to kick us off, when you are discussing essentially taking on, would you say okay, taking on the screening interview primarily? Is it primarily text or is it audio? How does it currently work?
Speaker 2:Yeah, we have a few products. Our first and most popular product is a video interview solution. Like how we're, a lot of your interviews might be a Zoom call or a Teams call. It's face-to-face Instead of you being on that call. An autonomous recruiting agent will actually host and interview the candidate on that call and it's over our own video conferencing platform. So the candidate doesn't have to install Zoom or Teams, but it allows the employers or the staffing firm to actually get a sense of the candidate's behavior and soft skills and during the interview the candidate and the recruiting agent have a live, personalized, genuine conversation.
Speaker 3:Got it. I just want to jump in here to clarify something, aaron. So basically, when they're doing that video interview, they're not interacting with like a live generated avatar, like people might have seen, like a video of I don't know a newscaster or something created. It's more, there's an avatar image down in the corner right and but they are getting that like live voice interaction, but it's not some ai generated person on the screen right.
Speaker 2:Yeah, you've got that exactly right. We found that and happy to chat about this more. But what we really care about is the candidate experience, and what we found is that generating a live avatar throughout an interview degrades the candidate experience. Although that technology is super cool, it's not what the candidate's like, and so you're correct. During the video interview, we essentially have a profile picture of the candidates like, and so you're correct. During the video interview, we essentially have a profile picture of the recruiting agent, so that when they're having that conversation, the candidates can feel comfortable and give their all during that interview.
Speaker 3:Nice, yeah, thank you for clarifying that.
Speaker 1:So it's voice AI, so asking questions and there's a conversation, but it's a conversational AI. Okay, so how's that going? Because sometimes when I'm using voice ai, it still can be pretty clunky. You know, particularly when there's like stuff like pauses and whatnot people talk a different cadence, stuff like that. How do you smooth over that experience? How do you make that work?
Speaker 2:yeah, I think the the tug is really between two aspects of the technology. There's one, so there are two things that make a great conversation. Two things are latency right how long does it take for me to respond to you after you've finished your response? And the second is intelligence right. Are you going to remember what I said three minutes ago and bake that into your next response? And so with both of those, we or I should say we built a lot of these technologies from the ground up, and that's allowed us to control these aspects. We also have really great partnerships with the folks at OpenAI and Azure, allowing us to really utilize the best that the AI technologies have to offer. You mentioned that. I have my engineering and AI research background and that really helps, because we truly understand the technology and we're able to make these trade-offs so that we can maximize the candidate experience. It just feels like a natural, fluid conversation.
Speaker 1:For sure. Do the candidates have the ability to respond by text, or is it only voice?
Speaker 2:And do the candidates have the ability to respond by text or is it only voice? During the interview, they respond over voice, both in the video interviews, and we also have a phone call product as well the second that you apply, you'll get a phone call, and so that's growing in popularity. We do have a portion where they can actually respond to a text. For example, let's say you apply for a job and our recruiting agent calls you but you're not available. The recruiting agent will actually send you a text and say, hey, it looks like I missed you.
Speaker 1:I'll probably give you another call in the next couple of hours if that works for you. Oh, that's awesome. I really love that.
Speaker 2:Yeah, increase the essentially the engagement of the candidate and trying to make that high quality.
Speaker 1:So is it primarily in terms of how your customers engage? Do you see, as soon as somebody applies, do most customers want them to just have the ability to start the screening process, or do you see customers want to essentially do an initial review of the profile and then have them decide from there if they want to screen the candidate? How do you see it work typically?
Speaker 2:what's really unique about what we offer is that companies now have the ability to engage with every candidate at scale, and what that means is they're now able to widen their talent aperture and not only consider the folks that had a 4.0 and went to a great school and had the best career backgrounds, but also those that, hey, maybe they didn't have the most opportunity throughout their career, but they have the skills and they have the knowledge to prove it and be a great employee. They have the skills and they have the knowledge to prove it and be a great employee, and we shouldn't be overlooking those folks. And the way that is articulated in the use cases of our customers is all the time they'll just interview every candidate because it's just so cost effective and it's a way to access talent that maybe your competitors aren't accessing today, aren't accessing today.
Speaker 1:So, that being said, it's like this tool is not evaluating the talent per se. It's collecting the screening data and then allowing the hiring team to make, essentially giving them a lot more information to evaluate and decide if they want to move forward in the process. Is that accurate?
Speaker 2:Yeah, so after every interview, the AI recruiting agent will write up detailed feedback notes and, for example, upload that or sync that to your applicant tracking system so that, for example, your recruiters can make a well-informed decision. The AI recruiting agent today can score, so you can give it a rubric for the things that you care about for that particular role or requisition and we'll score it at the candidate based on that interview interaction. And what's great about that is it allows the recruiters to focus their time on the candidates that do meet the requirements of the role, as opposed to those that maybe don't.
Speaker 1:So basically, the hiring team can filter based on certain criteria to identify the candidates that match best on the filters or whatever is that?
Speaker 2:exactly right. So, for example, maybe there's a, let's say, a light industrial role right where you need to be authorized to work in the united states, and you need to. You know it's located in boston, massachusetts, so you'll be able to drive up to Boston every day. The AI recruiting agent can ask those questions and then tag that applicant as okay, great, they're authorized to work in the US and they're able to work in Boston in person, and that just makes it easier for the recruiter to go back into their ATS and say, okay, great, I want to talk to those folks because they meet the criteria.
Speaker 1:Yeah, folks, because they meet the criteria, yeah, yeah, because, like so. With this tool, it's really where it saves time is ensuring that when recruiters or hiring teams do speak with somebody, they're much more likely to make it to the next round. It's not necessarily saving time at the very top of the funnel because the recruiters still have to go through all of the candidates. Essentially, it's like more like that one layer deeper within the funnel where it's saving time. Is that accurate?
Speaker 2:Yeah, and I think there's more to it. That is because we score every interview. You can, let's say we score them out of 100,. For example, you know, as a recruiter, I can set up an automation. You know, we have an automation, for example, with many ATSs, and so the second someone applies, they can get access to an interview. They take that interview. That data gets automatically populated into their ATS the employer's ATS and that includes a score.
Speaker 1:And so they can filter and sort based on that. Okay, cool, all right. So I'm just trying to think I might be a little bit redundant, I just want to make sure I'm dialing in. It is providing a very clear score for each interviewer, but that so that, and I guess that's based on if they match the criteria. But then you start to get into AI making like the doing the evaluation versus just packaging data for to make it easier for the hiring team to evaluate. So I guess my question is on the.
Speaker 1:You know, we I just had a really interesting conversation with steve bartell, ceo of gem, and we were talking about ai's role in recruiting and the difference between like essentially enablement and packaging data versus doing the evaluation directly, and so he was talking about like just like the legal kind of gray area, so to speak. And so I'm just curious how you think about that. And with that scoring, do you see that? Well, no, it's just like scoring based like are you remote or in person? Those are like very basic criteria. It's not evaluating based off anything deeper.
Speaker 2:I'm kind of curious how you think about that in terms of your product. Yeah, so we're firm believers in human in the loop. What we don't do is we don't allow at this time the recruiting agents to automatically create a disposition of the candidate and have that actually be synced to the ATS. We think of the evaluation as a data point. We tell you, hey, this person has, let's say, an 80 in communication skill. And then let me tell you exactly why I gave them an 80, right, because three minutes of the interview they had a really great explanation of this, but three minutes of the interview they kind of had some trouble discussing this particular experience at their last role here. And so I think evaluation certainly plays an important role in bringing value to the recruiting teams. I think it's important to make it both have human in the loop, but also make it explainable and data-driven. So don't just give me a score, but tell me, hey, how did you come to this? And let me make my own decision on the actual candidate.
Speaker 1:Yeah for sure. Yes, it's an interesting topic right when people are trying to figure out exactly what AI's role should be and then also, as legal cases start to happen. Right Right now, for instance, what's going on with Workday? I don't know if you guys are familiar with that there's a huge class action lawsuit on their AI discriminating upon race, age and whatnot. Now, who knows if there's any validity to it? Right, we don't know yet, but that's something that's current and a lot of folks are saying. Steve was saying that's probably going to set a precedent for future years to come. But yeah, it's really interesting. We're speaking with some CEOs who are very aggressive and others that are very reserved. I would say Greenhouse, the CEO, from what I can tell, seems to be incredibly reserved. Oh yeah, but you got Workable's CEO who we had on Elijah, what like two weeks ago.
Speaker 3:Yeah, nikos.
Speaker 1:I think, yeah, workable's incredibly aggressive, yeah, I mean they're implementing AI in every part of the funnel for talent acquisition and employee experience. They're an HRIS right.
Speaker 3:They built one within the last couple of years, but they started as an ATS only.
Speaker 1:Yeah, they just started that. So everything's sourcing to HR. They're just going all in, it seems. But yeah, I'm in the same. I think philosophically, I think about it the way that you are. It's like thinking about building a product of ultimately what's going to create the most value for the user and just pushing aggressively in that direction, and I think getting into evaluation territories is ultimately more valuable, and then just like putting in safeguards in place to make sure that we know exactly what the ai is actually evaluating off of is really important. But yeah, I think this is the future.
Speaker 2:really I think there are different philosophies for how you want to approach new technologies. I think you see that in every platform ship, whether that's the cloud or mobile, of course, the internet and the question you have to ask yourself as a leader is at what point do you put your chips in and how much? And what are just the opportunity costs of doing so and, more importantly, not doing so? And we're much more of the opinion that we think generative AI is here to stay, and it's very hard to imagine a world where there's going to be less AI in recruiting in the next five to 10 years, and so it's much more important to find those value cases, those use cases where customers will find value, and doing so in a safe manner, to ensure you're in a good spot.
Speaker 3:I think it's really interesting, too right. If you've worked with startups before, oftentimes you're dealing with first-time hiring managers, first-time interviewers, and for some reason, companies seem to feel there's less risk from having untrained interviewers that could be asking highly inappropriate or even illegal questions and they feel like there's more risk from that interviewer or that there's less risk from an interviewer doing that and giving an evaluation, a genuine evaluation that impacts hiring outcomes, versus an AI that can be like fully audited, like where you can refine it over time, like you're saying, aaron. You can know why it's giving different scores. You can also make sure it doesn't ask illegal questions. That, to me, is much lower risk than the bias you're going to get from an AI. It seems like it would be potentially lower risk than all the untrained interviewers who could essentially say whatever they want and put your company at risk.
Speaker 2:And I think you mentioned a good point there is that it's for an AI. It's measurable, right. You can do statistical analyses and figure out what is the kind of bias we're looking at today, Because you can measure it and you can plot it over time. You can take different actions to lower that over time, right. That's much harder to do with something you can't measure, like a human interviewer that might be the first time interviewing, or they woke up on the wrong side of the bed, or they didn't have a cup of coffee. If you can measure it, it's much easier to be able to control it, and so I think a lot of the big players that you mentioned are going to be caught up in these larger scale litigations. I think a good comparison is the autonomous driving market.
Speaker 1:I was thinking about this yesterday. I think that's a fantastic. It's a very relevant comparison.
Speaker 2:Yeah, and you see that I don't know if you guys have been in San Francisco recently, but I'm sure a lot of the listeners have. There are Waymos everywhere, people are taking Waymos left and right. They're completely autonomous. People love it. People pay more for Waymos because they can take meetings during the car right, it's a great experience and yeah, you definitely have some casualties, like Cruise, for example, got dragged in the mud in the news for a bit, but in the long run, that's probably going to be the future of driving it is.
Speaker 1:You know it's like. The other thing, too is like when you're building a product, particularly at an early stage, it's like at the rate it is moving. Do you really want to build a product for, like where you are today or where we've been for the past six months, are you building the product of the future?
Speaker 1:like yeah and it just seems obvious to me. It's like we should be building products that are like actually going to represent what the future holds. Yes, there are going to be roadblocks potentially, or just lessons learned is going to be risk, but that's where the opportunity is as well. That's where we get like the biggest lift and are creating the most value. So I think you know startups need to be aggressive here. I think, aaron, I think what you're doing is smart. I think that you have to push in this direction. I think there's a ton of value here. I'm curious, though when are you seeing the best traction now? I know you raised money. I think back in May you raised a couple million bucks, right?
Speaker 2:Yeah, our last round was 3 million around that time, and I think that's a question we think a lot about, because I think this is a broad generalization. But I think the point is clear. It's like, every company hires and thus it's very important to focus, because you need to pick one ICP, focus on them, solve their problems, because not all the markets will be ready, like I think a very obvious example is executive search. Right, that's not really an interviewing or a screening problem and it's more of a sourcing problem and finding those right people, so that market's not quite ready. So the question is okay, what markets are ready? And a great way to look at that is just sort by value, right, or I guess the inverse of that, which is pain, right, who is spending the most on interviewing and in screening?
Speaker 2:Today we found a lot of success in the external recruiting side of things. That's been very good for us and that's in their entire business, right, and it's a very good for us and that's in their entire business, right, and it's a very market sensitive business for them. And so if you can introduce automation that actually brings value to them and saves them time, increases placements for them, of course, software is going to be much cheaper than any type of human-based labor. That is a lot of value that you can provide and we've had a lot of success there.
Speaker 1:Okay, and with these staffing firms are you seeing, is it more like on the SMB, mid-market or enterprise?
Speaker 2:players, yeah, so we've been really excited to be working with folks across the board. I think the bigger there's a very clear value add for companies like in the mid-market because they it's very hard to scale like a staffing business to the level that they want to. There's just so thin margins. Even if you look at the 10Ks of public staffing firms today, you'll see folks that are doing 6 billion in revenue versus 18 billion in revenue annually. They're taking home the same amount of profit or being very close to break, even though one's doing a 3X the amount of annual revenue. And we're seeing a lot of uptake in the mid-market section.
Speaker 1:That's awesome and this might actually be the same for in-house teams too. We can just look at my agents' design for now. The specific types of roles they fill, I'm sure in the industry they serve, I'm sure impacts it. We were speaking. It was David Tell at Qual who was saying you're seeing a lot of in light industrial. He was just seeing a ton of demand. What types of staffing agencies are you seeing? Is it like temp hiring, perm placement? What types of industries and roles are they working on?
Speaker 2:Yeah, it really has been across the board, which is really exciting. It turns out, when you have something that is, you know, an intelligent and intelligent agents, what you find is that if they can do, if that agent can screen for a senior software engineer or a senior NET developer, then it can probably ask the questions required to screen for a warehouse associate or a forklift operator, and so that's been really exciting for us. A lot of our customers today are in, for example, it staffing, light industrials, hospitality, healthcare, a lot of temp, and I think that these cases are extremely obvious because a lot of those tend to be much more higher volume.
Speaker 1:Got it, so you to be much more higher volume. Got it, so you see more of the higher volume side. Do you see this as? Where do you think a product like this fits in with maybe lower volume? I mean, I think lower volume.
Speaker 1:The products that we're seeing, like we brought on CEO of BrightHire and Pillar and they're doing like internet interview intelligence platforms, where it's like AI co-pilots that are doing a really fantastic job of packaging data to help companies evaluate faster these are, I think, primarily on lower volume searches. There could be like a b2b growth stage mid-market tech company, something like that. They're hiring a software engineer. Maybe they have 10 candidates in the funnel. You know they're leveraging BrightHire to.
Speaker 1:It does, of course, like the job description generation, custom question generation, which is all very basic stuff, and then packaging the data effectively and then also give like some gong-like feedback on where they're like interview quality, how good are the interviewers doing? Are they starting on time? That kind of stuff. So it's pretty cool. I do a lot of. They have a lot of features Like. Like do you see your product fitting in on some of those lower volume uh use cases as well? Or like how do you I'm just curious if there's an application for what you're doing and some of those other use cases yeah, I think there's certainly.
Speaker 2:I think there certainly is we. The value prop is going to be a bit different because hiring for value prop is going to be a bit different, because hiring for those folks is going to be a bit different.
Speaker 2:Again the incentives are different. So for those folks, if they're hiring a senior software engineer in San Francisco and they don't hire too many of those then it turns out what they really want is someone that's super high quality, and so having an AI recruiting agent that can do that super technical, in-depth interview ends up being really useful for them, because you can essentially bubble up a very in-depth technical screen to that first interview, to that first interaction. You'd love to know if someone is technically competent right away, but it's really difficult because you know your engineers are, you know, very well paid and quite expensive, and so they're expensive, but they also don't have a lot of time and you pay them to do. You know to code and build product. Imagine where ai has read all the documentation, understands your tech stack and understands the tech stack that's on the candidate's resume, and they can have a really in-depth technical conversation. That ends up being a very, very interesting value prop for those folks.
Speaker 1:Yeah, and that's like what I'm getting at too. I see a very strong use case for lower volume searches as well, because I think that it would make a lot of sense for, when people are applying inbound, to just be able to open up a screening call so that when people are looking at resumes there's just so many screening calls where you're just wasting time. Yeah, we have the salary range posted on the job description but somebody doesn't look. It's like okay, we got to do that. Or are they available for hybrid or are they if it's a salesperson? Do they work with like mid-market enterprise customers? Are they available for hybrid or are they if it's a salesperson? Do they work with mid-market enterprise customers? Are they primarily SMB?
Speaker 1:There's just stuff that we have to know that even an experienced recruiter if you ask those up front and you can get off the phone in five minutes, it's still just a big waste of time where it's like you can improve the conversion rate from that initial conversation with a recruiter to the hiring manager if you have more information going into that call. It's just interesting because most of the application of product your product and then a couple of similar they're not exactly the same products we've seen. It's like we're on this like high volume side as the primary use case we're seeing. So it's just it's interesting to me. I see this incredible use case for low volume searches as well that I don't know.
Speaker 2:Yeah, I think what you bring up there is important is we're not only increasing basically the quantity or the bandwidth that your recruiting team can handle, but also just increase the quality. Your recruiters it's unlikely that they have a super experienced background in engineering, right? I mean, this is a technical hire. Or they were maybe never led go-to-market if it were a sales hire. And so what does that good sales hire look like? Well, it turns out that the AI actually knows, because it's read everything there is to know about what is a good sales hire and what experiences are good to have. And if you can give the AI recruiter, for example, the job description and the company's culture, then the AI recruiter can also help sell the role and the position and again just increase the quality of every interaction that you're having with the candidate.
Speaker 2:I think is something super special. We're not hiring hundreds of people every month. We actually use our own product, our own recruiting agent, to do a lot of the hiring, In fact, the last two people again, so we're pretty low volume. Our last two folks we hired were both using our AI recruiting agent and both of them have turned out exceptional, right? One of them's an engineer and one of them heads up our go-to-market and so sales hiring, so I think that's really exciting and heads up our go-to-market and so sales hiring, so I think that's really exciting and we are hiring.
Speaker 2:So feel free to everybody out there, feel free to uh, yeah, yeah, I mean that's uh, that's great.
Speaker 1:It's like when you're growing as a startup too, it's like you need to hire. This is a product that you need for, arguably like the most important part of your business, like your team is gonna for a product. It doesn't matter what kind of company. Your team is fundamental to anything you're going to build and any success you're going to have. It's the input for any level of success. But building anything great of value in the world.
Speaker 2:No, that's right. Yeah, I think an important note is what's best and what you're looking for in that next hire, and so our hope is to get you to a yes as soon as possible. Get you in front of the candidate, that is great, and if you're, let's say, your acceptance rate is at 1%, then let me just put that one candidate in front of you and the other 99, you know, not direct them to you, not have you have to filter through every single one of them, have a conversation with every single one of them.
Speaker 1:Yeah, for sure. So I've been monopolizing a lot of the questions. Elijah, Do you have any burning questions right now? I could keep going all day on this.
Speaker 3:Yeah, I have a couple of questions, but we did the sourcing technology one the other day that I got to geek out on and dominate things, so I appreciate that. I'm curious, aaron, how do you see things shifting in the market? So we've got the early stage video interviewing tools that were mostly kind of one way. You've got companies like SparkHire and there's a couple other big ones that I'm not remembering their names. Then you've got this just within the last few years probably, companies like James mentioned on the interview intelligence side, so like BrightHire, pillar, metaview, et cetera. How do you see Apriora coming in and fitting into that? Are those companies, the interview intelligence going to build their own AI agents, do you think? Or are they going to want to maybe I don't know create an agent, but actually it's Ap priori in the background that's actually delivering. I'm just curious how you see these shifts happening and your role in that.
Speaker 2:There are a lot of companies that do talent intelligence or interview intelligence, and that takes a lot of times the form of having a note taker on the call right and being able to essentially be like a gong for interviews. I think there are a lot of those types of companies. It's a fantastic product. Today, we really, we really want to skate to where the puck is going to be and not where it is today.
Speaker 2:I think today, you know that recruiter might not be on that call, or at least they're going to be a lot less recruited being on those calls, because they're going to be instead speaking with people that are actually qualified and not spending time with people that might not be. And so we're really, really bullish on complete autonomous agents, and that's what we're, you know. Of course, that's what we're really, really bullish on complete autonomous agents and that's what we're. Of course, that's what we're building out and what our customers love about us today. And again, it all goes back to value, right? If we look at that Waymo analogy, these interview intelligence platforms would be Ubers. They're great and they're very convenient, they're very helpful, but there still needs to be a driver there, right?
Speaker 1:do you want to build a red box or netflix like?
Speaker 2:exactly, exactly and and I think it's particularly this way is actually particularly interesting, because what you do is because you have a driver there right, and you again the you mentioned.
Speaker 2:it's very hard to measure how good that driver is, you just get in the car Right, and but you'd be, you'd feel a lot safer if you knew that, hey, this way more car has done literally millions and millions of miles and has never crashed. So statistically it's just, you're just a lot better off. I know I don't want to, I don't mean to go on a tangent here, but a couple of decades, many decades ago, elevators used to be manual. Right, you have an elevator operator actually standing in the elevator with you and moving you to the floor. But it's pretty hard to imagine that world today. It would feel almost unsafe. And so for us it's about skating to where the puck is going to be, and we think that where that puck is going to be is going to be an autonomous agent for hiring.
Speaker 3:And how are you going to work with the recruiters? I'm sure taxi drivers going with your analogy aren't excited about Waymo, and some of them in this case, some of them may be buyers for the technology. So I'm curious how you see recruiters adopting the technology. Lots of their time is spent doing screening calls. Recruiters adopting the technology lots of their time is spent doing screening calls and they're even struggling, I think, sometimes to want to adopt either a note taker or BrightHire, one of these interview intelligence tools. Yeah, how do you see that going, at least for the recruiters who are currently using your product and, in the future, How's it going to help them and what's their relationship with it?
Speaker 2:Yeah, so in the short term, I still believe that a recruiter is more likely to be replaced by another recruiter. You shouldn't be scared of AI taking your job tomorrow. You still are going to need a recruiter to facilitate a lot of those interactions. For example, hey, I talked to the hiring manager and I had an intake meeting with him or her and these are the interview questions and these are the things that they care about. Here's the rubric. Then the interview agent can go off and go do that interview, and so I think that recruiters will still be replaced by recruiters.
Speaker 2:Maybe a recruiter that's using AI will be replaced by those other recruiters, and I think that's the place of technology and I think recruits today still have a very valuable skill set and we want them to focus on the more human aspects of recruiting going to career events and focusing on employer branding things that are really hard to automate and candidly. They probably want to focus more on that anyways, because it's just more branding right Things that are really hard to automate and candidly. They probably want to focus more on that anyways, because it's just more human right. There's nothing human about going on eight to 10 screening calls a day, right, or trying to chat with someone that you don't know much about that domain, right? A lot of that just can and we believe should be automated so that you can focus on doing the tasks that you'd love doing as a recruiter.
Speaker 1:I agree Honestly. I own an RPO company, embedded Recruiting Agency and we've worked with over 200 customers in the past decade A lot of companies, a lot of startups, growth stage companies, a handful of enterprises, primarily in the tech industry, but not only and I honestly feel like if you're a good recruiter, you should be screening out 80% of the people in your phone screen and that's if you're doing a great job sourcing. It should be more if you have a junior to mid-level sourcer, if you have a great senior level sourcer, a lot of our customers. We're passing on 80% of the people on first round. The reason why I think that a lot of recruiters they do see their role as sales, but when you really put on that business owner executive hat, you got to remember it's not just about filling roles, it's about building value and building a team that's going to scale a successful company and add value to the customer. That's a lot harder than just getting somebody in the seat and the role of recruiter should be one hand you're beckoning, you're pulling people in, the other one you're pushing away, right, you're putting up the barriers, right, and so it just like again for our senior recruiters.
Speaker 1:They had to get really good at evaluating quickly and they spent a lot of their time jumping on the phone with a candidate saying all right, look, I'm happy to answer your questions. I ask my questions in order, starting with a high level fit, and we only get into the details if it actually makes sense, because I don't want to ask you all these details. It doesn't make sense to go into that and we'll just do it in order to make sure it makes sense for both of us to continue the conversation and I don't know 20 to 30 percent of the time off the phone in the first five minutes and then you got another 20, 30 percent of the time that you're off the phone at 15. And then you got probably less, around 20 percent of the time. You're hopefully trying to scramble to get everything in before the call and you're building that relationship by the end of the call, talking about the process and next steps and everything like that.
Speaker 1:But I'm just thinking, yeah, as a senior recruiter, somebody who knows what you're doing, if you can in a meaningful way increase your conversion rate from phone screen or from your first interview. If the product is doing the screen, it eliminates and collapses the process. But from that initial human interview to the next round. If you can increase that conversion rate, that's huge. If you're doing it in the appropriate way, like I think. A lot of times conversion rates are like people think about them the wrong way in a recruiting funnel, I think like more is better.
Speaker 3:No honestly, a lot of times like west is better there's a balancing act.
Speaker 1:If it's too low, it's like are you setting up the right people? If it's too high, like are you just people through? Oh, it's nuanced, but but yeah, anyways, like it just would save a lot of the time and you want particularly you're saving the time as your senior level resources, which is like your senior level recruiter or your hiring team, and there's like metrics that daniel tape put together and like growth companies hiring and a lot of times hiring managers are spending 50% or more of their time interviewing On average. I was talking with Matt Caldwell. I don't know if you guys know Matt, but he scaled a company called Rocket Power, an RPO firm, from a few people to over 400 people and he sold a historic amount of money to Kelly Services and yeah, anyway, same thing.
Speaker 1:He's looking at it essentially the same way. They basically calculated and, believe it or not, there was around 75 hours on average companies were taking per hire, and those are the later stage companies, right, ones that you would have heard of, which is an insane amount of time. So think about that much time on payroll of executives. And that's not even covering the cost of working with an RPO agency job postings, whatever you're doing to fuel that growth? That's insanity. So if you can leverage a technology to improve the quality of your pipeline for every human touchpoint, that is. This is a seven to eight figure problem for businesses and they don't even realize it.
Speaker 2:Yeah, I can just speak from my own experience, because we are hiring and when I post a job, I'm going to get hundreds and hundreds of applications and resource them and try to get them to apply and I make an effort to meet the candidates that I like. But there's just no way that I'm going to be spending or any of our employees are going to be spending hours and hours looking through every single resume and making the right call on every single one. That takes a lot of time. So if I could just have, in the click of a button, have my recruiting agent hop on a Zoom call to every one of the hundreds of people and then just hey, out of 100, these are the great ones. These guys scored over 90. They've got. They're really smart. I think you should talk with them. That's great. I'm just going to speak with those guys. I'm going to give them a fantastic experience because I think we're going to have a really great relationship, and so I think you're spot on there, james. It's a really exciting time.
Speaker 1:Yeah, for sure. And I have one other question. It's a burning question that I have before we jump off the next few minutes. I'm totally blanking on it right now. Dang it, it was a good one too. It was a really good one, I'm telling you, aaron.
Speaker 3:Well, elijah, what other questions do you have? No, no other questions right now. I have a fairly different opinion on the way I do like phone screens and stuff, but that's probably for a different episode, because I could, ok, I remember my question, so let's just do that All right.
Speaker 1:So for what about? So what do you think about automation and AI product driven interviews for late stage interviews, so like we're seeing this initial application and screening calls, but like technical tests, seems like a clear one to me, to the extent that companies are using third party testings or just doing homegrown evaluation. Like why wouldn't we like a technical interview, basically incorporate an agent and then basically just package that evaluation for a hiring team? So getting like beyond screening but really getting into like code assessment and these types of things. I'm curious. I'm sure you guys have thought about that.
Speaker 2:Yeah, and again, I know we've talked a bit about this already, but it all comes back down to value. There's a lot more value to drive when you go from 100 candidates to 10, that's the screening process than in 10 to one, and so it's very intuitive that the companies being built today are starting with a larger problem. I think over time you're going to see automation start to trickle in and take over that portion of the funnel as well, but it may even be the case that the funnel in a way collapses, because at that point why not just do?
Speaker 2:that technical assessment at the start, right, it's not like the thing that's bandwidthing you. The reason you can't do that today is because you mentioned those senior level resources, those engineers and those hiring managers. They just don't have time. And the recruiters don't have a lot more of that bandwidth, but they don't have time. The recruiters don't have a lot more of that bandwidth, but they don't have the knowledge, the experience there. Ai has all of that, and so you might even just see a collapsing of the funnel where technicals again bubble up, and it's just part of the screening process.
Speaker 1:Yeah, exactly, I think maybe this concept of segmented stages might start to collapse. As you said, there's going to need to be a way that we organize the data to be in a presentable fashion where it's segmented but like this traditional interview process with these, the way that it's done, it's definitely going to shift where maybe there isn't the need to schedule like five separate interviews at segmented times for the candidate to do that over a period of weeks and maybe you still segment out the data but a lot of it can be done in one workflow right, Like show pipeline stages and stuff like that. It'll just be different.
Speaker 2:The difference in cost between, let's say, like a recruiter and, as I know, we're staying on this technical interview topic. So the difference in cost between a recruiter and an engineer is going to be pretty high. But the difference between a model that is like super bare bones and one that can understand engineering, the cost there's a couple cents, if not none, and so there, and you've already got them on the phone call in that screening interview. So you might as well throw a couple technical screen screens in there as well.
Speaker 1:So are you like, in terms of your evaluation, where's that data being pulled from? Is it being pulled from the job description? Like, are you doing the customer questions? Like, where are you generating customer questions and where are you pulling that evaluation data from your customer?
Speaker 2:Yeah, so the evaluation, so there's the interview questions and essentially the rubric or the scoring criteria out of each one is like out of 100, for example, so you can have things like communication or experience or other, even things like English proficiency or discipline, so that'd be things like behavioral questions, and those can be automatically generated by your recruiting agent.
Speaker 2:All you have to do is give it the job description and it already understands things about your company during the onboarding process and it'll generate those interview questions in the group for you. Or you can just upload the scoring rubric yourself, for example, based on intake notes. What the hiring manager cares about.
Speaker 1:Got it and you guys, are you integrate with applicant tracking systems and whatnot?
Speaker 2:Yeah, we agree with a bunch of them Always. We're always trying to integrate with more of them. We yeah? So the answer is yes.
Speaker 1:Cool, awesome. We're coming up on time here. Last chance, elijah.
Speaker 3:Awesome, we're coming up on time here. Last chance, elijah no-transcript.
Speaker 2:Um looking forward to catching up again.
Speaker 1:This was super fun yeah, of course we're looking forward to having you back on the show and for everybody tuning in. Thank you so much for joining us and we'll talk to you next time. Take care.
