Ep 826: Do AI Interviews Work?

0:00Support for this podcast comes from Ribbon, the AI recruiting platform built for enterprise hiring at scale. Ribbon brings candidate sourcing, outreach, screening, and interviewing together in one workflow, helping recruiting teams find and engage talent, uncover deeper candidate insights, and identify hidden gems who might otherwise be overlooked. Ribbon takes repetitive work off recruiter's plates, giving them more time to build candidate relationships and make informed hiring decisions, while making the process faster and more accessible for everyone. Go to ribbon.ai to find out more. There's some scepticism in talent acquisition about letting an AI conduct the first conversation with a candidate.

0:48However, the enterprises that have deployed AI interviewing at scale are reporting improved candidate satisfaction, faster hiring, and better retention. Results that are becoming hard to ignore. So what are they seeing? And should it change how the industry thinks about AI and hiring? Keep listening to find out.

1:13There's been more of scientific discovery, more of technical advancement and material progress in your lifetime and mine, and in all the ages of history.

1:27Hi there, welcome to episode 826 of Recruiting Future with me, Matt Alder. AI is becoming more and more embedded across recruiting tools, but there's a meaningful difference between AI that automates workflows behind the scenes and AI that talks directly to candidates. When AI conducts a conversation, the stakes are much higher. That first interaction shapes how the candidates perceive the employer and the role. That's why many talent acquisition teams remain cautious about AI interviewing, even as they adopt AI elsewhere in the hiring process. However, a growing number of enterprises are now running AI interviews at scale, and the data coming back on candidate experience and quality of hire improvement is difficult to ignore.

2:16So what does this evidence show? And what should it mean for how the industry thinks about AI in hiring? My guest this week is Dave Vu, co-founder and COO of Ribbon. Dave spent 15 years in talent and people leadership before co-founding this AI interviewing platform. In our conversation, he shares what enterprises are reporting from deploying AI interviews across thousands of candidate interactions, how the candidates themselves are responding and what this could all mean for the future of hiring. Hi, Dave, and welcome to the podcast. Hey, man. Well, it's great to be here. A pleasure to be talking to you on the show.

2:55Just to start with, could you quickly introduce yourself and tell everyone what you do? I'm Dave Vu. I'm one of the co-founders and COO of Ribbon. And essentially, for the last 15 years, I've led talent and people team, helping companies grow from early stage startup into scaled organizations. You know, I was the first employee at Ezra where I helped build the talent function and operations there. And, you know, my experience over the last 15 years in a variety of different capacities in the talent side, you know, gave me a really deep expertise and firsthand experience just to understand how difficult it is to recruit, especially in just in day and age where you know talent movement is you know people are moving around so much.

3:41Tell us a little bit about what you're building at Ribbon. So Ribbon essentially we build out agentic AI recruiters so enables recruiters to build custom AI recruiting agents for their roles. These agents can interview candidates anytime engage with them in a two-way conversation, assess their skill, experience at the top of the funnel mainly. And we work with large enterprise customers doing high volume hiring. At the same time, you know, Ribbon also helps recruiters source and rediscover their qualified candidates in their pipeline. So it allows, you know, recruiters to save a lot of time, spend time where it's most important for them, which is really building that relationship with those candidates, you know, selling them and engaging with them about the opportunity itself.

4:30And so our tool essentially is saving recruiters a lot of unnecessary manual time in their process. What are you seeing from the enterprises that you're working with? How are they thinking about AI? How is that changing? What does the landscape look like out there at the moment? I think things are changing quite a bit. If you were to ask me the same question one year ago, I would say enterprise companies weren't really ready. They were thinking about it, but they were really necessarily ready to adopt. But that shift has rapidly changed over the last year, year and a half. The biggest shift that we see with enterprise customers is that they've moved beyond the experimentation phase.

5:11And so they're no longer asking, should we be using AI? I think it's kind of a given. Most companies are already thinking about how do we adopt this? You know, how do we successfully roll this out? And how do our recruiting team use this in order to improve their workflows? And so their mindset has shifted from that perspective into more practical sense of using the AI. So we're seeing it move away from simple automation tools into more, how does this fit into their current recruiting workflows? So things that are really important for them is really speed. So they see like this solution speeding up their process.

5:54They're also just making sure that it's creating the outcomes that they're looking for and the experience for the candidate to maintain their employer brand. It's kind of interesting how things are evolving. And I think sometimes we sort of talk about AI and recruiting and kind of lump it into one big thing. But there's a real difference here between software that people might be buying for automation and efficiency and AI software that is going to be talking directly to candidates. What are the differences and what should employers be thinking about when they're looking at that type of application?

6:28When the AI interacts directly with the candidates, I would say the standard is much higher because it becomes an extension of the company's brand and employer brand specifically. So the experience needs to feel very real. It needs to be smooth, right? And so those are things that we optimize for to make sure that it is as closely simulated to a top recruiting conversation that one of your recruiters would have. So the AI must be able to listen, must be able to pause naturally, must be able to continue to probe and ask relevant follow-up questions, for example, accurately answer what candidates want to know about the role, about the company, about the culture as best as possible.

7:15and that creates a great experience for the candidate. It also needs to be able to have deep role-specific knowledge and context, right? And that's where the recruiting team is able to provide that additional information and context for the recruiter so that it can ask really meaningful questions specifically about the role. So for example, we have a customer, a large automotive company where there's very specific questions about engineering and the inner workings of an automobile. And so it has to be able to ask those very specific questions in order to ensure that they're qualifying those candidates as best as possible.

7:59I think one of the interesting things is I've spoken to this type of AI interviewer before, and I think that there are a lot of people out there who haven't, who still perhaps are under the impression that this is like an old school chatbot, but just with a voice. I mean, this is something very different, isn't it? Absolutely. It is very different. It is very, it's very conversational. It's very natural. And you'll see that it is not a one-way conversation where the AI is asking a question, the candidate is just responding. It's really engaging and it's able to probe. So, for example, if it was to ask a very specific question and a candidate answered, it's not going to just jump to the next question.

8:41It's going to be able to go deeper specifically to ask the relevant question to what the answer was provided by the candidate, specifically pertaining to the role. So, its aim and its goal is constantly to be able to dig deeper and deeper, just like a really good recruiter on your team would. Switching to the candidate side of things, there's a sort of a huge narrative out there that candidates don't like AI in their recruitment process. There's a lot of mistrust and it's kind of a very difficult situation. What's the reality from your perspective with the candidates that your system's dealing with?

9:19How do they feel about it? What are you seeing happen? So candidates, you know, we're seeing very positive feedback from the candidates. It's getting more positive on a day-to-day basis because what we're seeing, the main thing we're seeing is basically candidates, it's not that they don't like AI. They dislike slow processes, right? Unclear expectations, applying for a job and never hearing back and not having an opportunity to present themselves in the best light possible. Well, usually when you're applying for a job, you're just putting up a resume. So you're not really sharing who you are.

9:55Somebody has to make that determination on a piece of paper. And in this day and age, everybody's using GPT and other tools to be able to maximize their resume. This is an opportunity to present themselves. How are they like in person? And how are they like when they communicate and provide additional context? candidates love that because it gives them an opportunity to present themselves in another light but also it gives them immediate access to an interview and also a consistent opportunity to you know tell their story so the the rating that we typically see coming out of candidates these days is it's above 4.5 to 5 when we ask the feedback from each candidate after their interview One of the most interesting signals that we're seeing candidates choose AI interviews is that 25 % of the ribbon interviews typically happens between 10 p.m.

10:52and 2 a.m. And they make sense, right? If you think about specific jobs where you're on the floor constantly or you don't have the ability to step away for an interview for 45 minutes, this gives you that access. And so everybody has that equal access where they can interview at any point that makes it most convenient for them. It's kind of really interesting. And obviously when people use the system, they're having a great experience. How do you advise employers in sort of building up that trust in the first place to get people to want to do this? How can they sort of tackle that lack of trust or that lack of information that's out there because people haven't experienced this before?

11:36Yeah, I think the messaging coming from the employer is really important. A lot of the brands, they get a lot of applicants. The brands that we work with are getting between 5 to 10 million applicants per year. So they're swamped by the sheer number of volume of applicants because of their brand and people recognize it and they're constantly applying for jobs. And so they do a great job of marketing themselves. The main thing is really to use our tool and communicate to them that this is going to speed up that process for them, gives them the accessibility that they're looking for so that they can basically skip the queue and be able to have one of the recruiting members interview them much faster.

12:21I think presenting them with also, you know, assets that we have to show them that is a natural conversation AI interview, I think is really important as well. But most of it is going to come down to the employer and how they present that message to the candidate. And what kind of results are your clients getting from this? Where is it driving value for employers? Yeah. So a great example I always like to use is one of our customers, it's the world's largest leading automaker, and they're using us at a variety of different capacity. But overall, what we're seeing the data come out is that hiring is about 35 % faster for them.

13:03So they're saving on average 22 hours of screen time for every single role per recruiter. And that's quite significant. And we're hearing that from their team. one of the recruiters that we were talking to on that team mentioned that they were able to find all the roles that they filled in the last quarter through Ribbon. And so it saved a tremendous amount of time for them to be able to focus on building that relationship with the candidate, also selling the opportunity, and managing the rest of the pipeline and using opportunities to go out there and hunt and find other candidates as well, while the recruiter is doing all the manual process.

13:49So we're also seeing that Ribbon becomes the core part of the hiring process for a lot of these enterprise customers. So like extra space storage, for example, one of our customers, approximately 85 % of the hiring flows through the Ribbon interviews at this point. Our goal is obviously to get to 100, but it shows that it is a major core component of the recruiting process for these large enterprise teams because they're seeing the result, the return to them in time savings, in efficiency, and a better conversation with the candidates. The other thing we're seeing is also at the end of the day for recruiters and hiring team, the main result is really on the ability to find great candidates.

14:30So, you know, the speed and the efficiency, we've seen that over the last 180-day employee retention has improved. roughly 10 % to 30 % depending on the role as well. So we're seeing a retention result on the backside from the candidates that end up joining those companies. What is it that's driving that? Do you think it's the quality of the candidate experience? Is it that the recruiters have got more time to build relationships? Or is the AI finding new employees who might've been kind of overlooked in the previous process? You know, the truth is, I think it's a combination of all those things.

15:06so for example the accessibility piece allows candidates that let's say they were interested they saw the posting and at that time they can't do it well you know if if their time is busy they're not gonna be able to do it and sometimes they end up not doing it at all so you lose out on opportunities from great candidates this allows the candidate to do it right away so So the ability to do it right away opens up a whole new pool of available candidates. Also the speed. So that let's say the candidate's interested, they saw the posting, they're doing the AI interview with Ribbon. The recruiter sees that interview, they can reach out to that candidate right away.

15:46Versus, you know, they would have to schedule that candidate in at their convenience. You know, typically a nine to six from Monday to Friday. Candidates calendar might be filled up. So you might not have that initial conversation three weeks from now. You lose that opportunity and that momentum. The other piece I would say is also the AI does a great job of just being able to ask all the relevant questions that you would input for that candidate so that the recruiter can observe that list of candidates and then prioritize the best candidates first. Again, going back to speed and making sure that you're reaching out to the right people faster.

16:24that by doing that and doing that across multiple roles for a recruiter a recruiter now can spend most amount of time with the best candidate and and reprioritize those those candidates on a daily weekly monthly basis are there a couple of example clients you could talk us through in terms of in terms of what they've done and what they've achieved yeah absolutely you know cartisa comes to mind so they need to hire contractors evaluators across you know roughly 20 different languages. And scheduling is a nightmare, right? Because of the time zone difference. So their hiring manager ran 43 ribbon interviews in four weeks and personally interviewed every single one of them.

17:06So they ended up hiring 20 people without getting into 43 live calls because they're able to then prioritize, look at those candidates and decide which ones that they want to interview first. So that's the immediate result that we saw from those guys. And that's the type of, you know, result and scale that we expect to see from our customers is that as they start implementing this, it will save them a tremendous amount of time interviewing people from all around the globe and giving the capacity back to the talent team to be able to take that next step with the best candidates possible. You know, one of the quotes that stuck with us from the hiring manager, Jonathan, is that the biggest value to us is scale.

17:48You know, I would not have it, I would not have been able to conduct 43 mini interviews, you know, even at 15 minutes in a live setting in a very rapid amount of time to be able to get the results that they needed in a short period of time. So I think, you know, for me, I love those types of stories because it shows that the team still stays in control. They make the final decision, but they're able to see results on a day-to-day basis and allow them to focus the time where it's best for them to sell and move those candidates to the next stage. The other customer that we have that I want to highlight is Rand O 'Reilly.

18:31So they hire drivers and technicians. People are mostly never sitting at their desks for those types of roles. I think for those types of roles, it's very important to be able to give them access to a fair opportunity to be able to do an interview and identify really good candidates. You know, their director, Matt O'Donnell, told us that in one stretch, nine of the 11 hires came from candidates who did their ribbon interviews outside of normal working hours. So think of like 10 p.m., 11 p.m., midnight, you know, anything beyond the normal standard business hours that a recruiter would be able to have those conversations.

19:08they were able to give that opportunity to those drivers and technicians. And so it sped up that process for them tremendously and cut the interview time that they would have typically taken months into weeks. So in his words, basically, Ribbon helped them connect with candidates outside recruiter, normal working hours. And that was a really massive difference in their hiring and recurring process. you know the main practical effect that we see is like recruiters would show up in the morning and you know four or five completed interviews already at their at their disposal and so they're able to then prioritize those candidates have a conversation with them and then jump on the next stage immediately as a final question for you how do you see this oh developing what what does their future look like what are you what are you kind of planning for in terms of what you're building?

20:06How is AI interviewing and hiring going to evolve over the next two or three years? We see the AI interviewing conversation with candidates becoming more specialized, becoming more deeply integrated with the entire hiring process end-to-end. Right now, we're specializing at the top of the funnel and we're seeing great results in between that as well from our customers using it in a variety of different stages, but we see this AI recruiting agent will be with the recruiting team every step of the way so that it can help with all the manual process, be able to surface all the key information that a recruiting team would need including contacts.

20:51So the person that would do the initial screening call and interview after the ribbon interview will have a specific context, might not be in a second interview, but now the AI is the only one that has contacts throughout the whole process, we'll be able to give the overall assessment for the candidate for every single team member that's part of that process at the end. We also see a world where we will be able to use the AI to help improve cheating and integrity, right? That's something that's going to be coming out a lot more. We've already built that as one of our features, but we're going to continue to improve that just to make sure that we avoid candidates that are trying to circumvent the interview process.

21:38Our AI is going to be able to identify certain patterns based on the interview just to be able to flag that and we're going to continue to improve that. We also see a world where recruiting, there's two stages to it. There's intake and there's outbound hunting. that's an area that we are diving right into right now we're going to continue to improve that which is be able to continue to source candidates uh rediscover them um in in a pipeline to make sure that if they're not good for another role they might be good for this particular role in real time and with the data that we have from them from a previous interview that they've conducted with ai interview i think all that data is going to be very rich that we can tap into so i see a very exciting world where the AI is going to be involved in every part of the hiring process end to end with a recruiter and a hiring team.

22:37Dave, thank you very much for talking to me. Thank you, Matt. My thanks to Dave. You can follow this podcast on Spotify, on Apple Podcasts, or wherever you listen to your podcasts. You can search all the past episodes at RecreasingFuture.com. On that site, you can also sign up for our weekly newsletter, Recruiting Future Feast, and get the inside track on everything that's coming up on the show. Thanks very much for listening. I'll be back next time, and I hope you'll join me.

23:22Bye.