00:25:39 · Daniel Chait
[00:25:39] S0: Yeah. Well, I mean, let's take the example that we already started talking about with voice. Like, one of the big problems in hiring has always been resume review, always. The idea that you send in resumes, whether it's in envelopes in the old days or in a website recently, you submit your resume, and then you hope you get an interview. And why do have to hope so hard to get an interview? It's because giving an interview is expensive. A company has to take an employee and put them on the phone with a candidate for a half hour or an hour. Companies are only going to do a few dozen of those for each job. But when hundreds or thousands of people are hiring, that means almost everyone who applies to a job isn't getting a look. And so by questioning that assumption, saying, Why do we have to do a resume review before you get an interview? It's because interviews traditionally are manual and time consuming and expensive. But if we can do them automated in a way that's transparent, that feels good, we can give them to everyone. And so our customers using Voice AI are now saying, Everybody who applies gets a conversation. And so Voice AI will automatically open up the funnel to anyone who applies. And that's great for job seekers who are willing to spend a half an hour answering some questions, improving their skills, and a chance to get ahead. It's great for companies who can now find diamonds in the rough, not care about resume keywords and everything. But from a systematic standpoint, and why do I say we can make things radically better, is because resume review is one of the most biased parts of hiring, always has been. There was a study done in 2003 that showed a 50% racial bias in who gets a resume callback, who gets an interview callback based on the name at the top of their resume. If your name sounds stereotypically black, you have a 50% less chance of getting an interview than the same resume with a name that sounds stereotypically white. And that was twenty five years ago. And so if we're gonna skip a resume review altogether, and anybody who applies can have a conversation, we eliminate completely. We just define that 50% out of existence altogether, and we skip that whole thing. And so that's what I mean by there's real opportunities here to say, we're not just gonna minimize the harm, we're actually gonna make things radically better.
00:27:45 · Guillaume Moubeche
[00:27:45] S1: And do you feel like some people or like some candidates are gonna not truly like the process of being interviewed by an AI? Or like, what's your view on it? Like, do you feel like overall it's taken, like, pretty positively by candidates? Or
00:27:59 · Daniel Chait
[00:27:59] S0: Well, yes. I mean, look, if you're doing anything in the world, you're gonna have people who don't like it. So let's start there. Like, yes, there will be people who don't like it. I think opinions about AI and opinions about AI interviewing are pretty mixed. I mean, there's a lot of negativity, and there's a lot of concern about the role of AI in society. Forget hiring. Think about the conversations around data centers. Think about the conversations around intellectual property. There's tons of concern around AI in all aspects of the world, and a lot of it very understandable. And in interviewing, there was a wave of AI interviewing that came out over the last few years that candidates really didn't like at all. It was not very transparent. So shockingly, as we learned when we were looking at this market, there were a lot of those early products that would not tell the candidate it was gonna be an AI. They would say, hey, Guillaume. Congratulations. We'd like to interview you. Show up on this date and time. Click this link. You're gonna get an interview. You're like, oh, cool. And then you get on there, and it's not a human. It's an AI. That's deceptive. Right? So people are just turned off by that. I think a lot of the voice mode of those early conversational products were not very good, and so they were stilted. They would interrupt you. They often had an uncanny valley cartoon character trying to talk to you. There's a lot of just the experience wasn't great. And then the decision making wasn't very defensible, so they would conduct these automated interviews, but then in some obscure black box way, like render judgment on you with no explanation as to why. And so when we went out to find our solution and research the market, we had those three things in mind. And we specifically wanted something that was gonna feel good to the candidate and sort of handle those questions about the experience itself. It was gonna be very transparent and candidate centric, give the candidate the opportunity to ask their own questions, to interrupt, to know ahead of time what they were dealing with, to opt out, all of that. And then that was built on a foundation of structured hiring with a clear rubric and a sense of structured fair hiring where we're gonna ask every candidate the same questions. And so that was the solution that we brought to market.
00:30:02 · Daniel Chait, Guillaume Moubeche
And so what we see is when a candidate goes through our process with Greenhouse Voice AI, they give it very favorable marks. They give it four out of five stars 90% of the time. And our basic idea is if the candidates aren't gonna like it and use it, our customers aren't gonna buy it. So simply, have to make it something that candidates are gonna like. [00:30:21] S1: And also, it's gonna get better over time. Like, if you look at every voice models, like, we're gonna pass the Turing test for conversation, so you wouldn't be able to notice whether it's a human or a or a Voice AI. So it's it's only gonna get better. [00:30:34] S0: I think that's right. And look, I think, you know, as much as, again, mean, I empathize, like, many of us haven't sat on the phone with the airline shouting representative, you know, to try to get to someone like, b. Right? It's like, b. Like, I get that. But I think also [00:30:47] S1: Imagine when you have a French accent.
00:30:47 · Guillaume Moubeche, Daniel Chait
[00:30:47] S1: Imagine when you have a French accent. [00:30:49] S0: Exactly. I can imagine it's not great. But at the same time, like, the technology does improve, and I think societal attitudes about AI in hiring have already evolved very rapidly. Like, what's okay to use AI to do in a job process has changed and in a lot of ways opened up, and I think that's becoming more and more acceptable. And I think we're going to start to see more and more acceptance and realization of the benefits and of the upsides as we go. I think it's on us you know, to deliver that that promise. And I think when people see that, yes, they're getting a fair shot. Yes. They're... The experience is is is pleasant. There's transparency. Then I think, you know, the... You know, we we have the ability to drive those attitudes. If we build crap products that people don't like, yeah, they're gonna hate them.
00:30:49 · Daniel Chait, Guillaume Moubeche
[00:30:49] S0: Exactly. I can imagine it's not great. But at the same time, like, the technology does improve, and I think societal attitudes about AI in hiring have already evolved very rapidly. Like, what's okay to use AI to do in a job process has changed and in a lot of ways opened up, and I think that's becoming more and more acceptable. And I think we're going to start to see more and more acceptance and realization of the benefits and of the upsides as we go. I think it's on us you know, to deliver that that promise. And I think when people see that, yes, they're getting a fair shot. Yes. They're... The experience is is is pleasant. There's transparency. Then I think, you know, the... You know, we we have the ability to drive those attitudes. If we build crap products that people don't like, yeah, they're gonna hate them. [00:31:35] S1: Yeah. I mean, you're at the forefront of something that's, like, very new, and that's also, a societal, like, change. So obviously, as you said, you know, like, some people are gonna dislike it, but if people realize that they have better shots at finding jobs, then, you know, it becomes something obvious and people will recommend it. When you look at your business model, because you went from being a pure SaaS player to leveraging AI a lot more. So we're talking about, like, token cost, etcetera. Like, what's your vision about the price of token with AI? Do you think that we're gonna have, like, similar margin to to SaaS in the coming years and the price is going down? Or what... What's your, like, perception of it?