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Peter Dalton on How AI Can Fix a Broken Hiring Process
5 Plays5 days ago
Hiring is broken for both candidates and employers.
In this episode of MustardHub Voices: Behind the Build, Curtis Forbes sits down with Peter Dalton, Co-Founder and CRO of Veton, an AI-powered hiring platform that automates resume screening and early interviews while giving every candidate a fair shot.
Peter shares what pulled him into HR tech after years of sales leadership, why application volume and fake candidates have become a serious problem, and how AI can help hiring teams focus on what actually matters: human connection, quality of hire, and better decision-making. The conversation explores recruiter anxiety around AI, leadership’s role in change management, and why the goal isn’t replacing recruiters — it’s freeing them from administrative overload.
This episode is a must-watch for HR leaders and operators who want to use AI responsibly to improve hiring outcomes without losing trust or humanity.
About Peter:
Peter Dalton is Co-Founder and CRO of Veton, an AI hiring platform that automates resume screening and first-round interviews so every candidate gets a fair shot and companies reach the right people faster. Before Veton, he spent nearly two decades leading high-performing sales teams at both startups and global enterprises, known for building new revenue streams, coaching teams through rapid growth, and consistently outperforming targets. He combines deep sales leadership experience with a practical view of what it takes to scale teams today.
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Transcript
Introduction to Curtis Forbes and Peter Dalton
00:00:07
Speaker
Welcome back, everyone. This is another installment of Mustard Hub Voices Behind the Build. In these episodes, I sit down with the people building, backing, and running better workplaces. I'm your host, Curtis Forbes, and my guest today is Peter Dalton. Peter is co-founder and CRO of Vettin,
00:00:25
Speaker
an AI hiring platform built to automate resume screening and first round interviews so every candidate gets a fair shot and companies get to the right people faster. ah Before
From Rugby to Tech: Peter's Journey
00:00:36
Speaker
Vatan, he spent nearly two decades leading high performing sales teams at both startups and global enterprises. known for building new revenue streams, coaching teams through rapid growth, and consistently topping performance charts. He combines deep sales leadership experience with practical view of what it takes to scale teams today. Welcome to Behind the Build. Thanks so much for joining me, Peter. Yeah. Hey, Curtis. It's a looking forward to the conversation. Great to be here.
00:01:03
Speaker
Yeah. So, um For anybody who doesn't know, i should first ask, how long have you been out of rugby? um Long enough.
00:01:16
Speaker
By 10 years, when my yeah when my kids were born, it didn't really allow for time. I'd been coaching.
The Birth of Vettin: Revolutionizing Hiring Practices
00:01:22
Speaker
I was playing, and then I started coaching locally, and the kids just took over over my time. So my focus is now on things like underage soccer and dance and things like that.
00:01:30
Speaker
I don't dance, but my kids do. Fun. Well, you have a ah relatively long and impressive career in in tech, but but most of that experience, I guess, hasn't been in the ah HR tech space. So what brought you to the world of of human resources?
00:01:48
Speaker
Yeah, it's interesting. My co-founder reached out to me. I was kind of merrily ticking along on my life in a previous organization. That's actually a med device quality management system company. And, you know, he reached out and mentioned, this is what we're doing in terms of the product I'm looking at building. And I think it's something you'd be really good fit for to help me kind of build it and come in for the go-to-market side of things. And my first thought was like HR tech. Okay, you know.
00:02:15
Speaker
tell me a little bit more about it. And when we walked through what it was, it really excited me because you know I've been on both sides of the equation. Being a hiring manager, um I've hired at organizations, and I've been the candidate applying for roles.
00:02:29
Speaker
And you know even as little as a couple of years ago, the the system was kind of broken. you know applicants were flying people weren't hearing back um you know people who were doing the interviewing were kind of facing this overwhelming mountain of candidates applying you hundreds and hundreds there was no way of getting through them all and and so as a result you know people are getting missed and issues are being faced and so it was just a really big problem i i just felt really excited to solve um you know because i've been in it and i felt it so that's kind of what led me to take the leap and and join in for veton I love that. I love that story. what you know you um
00:03:03
Speaker
so you know You came from this other organization. You saw this incredibly enormous problem to solve, right? um Is this your first jump into entrepreneurship? What excited you most about that? Because I love learning about what drives you know founders and co-founders to kind of start their own businesses or be part of that journey.
AI's Role in Fair and Efficient Hiring
00:03:22
Speaker
Yeah, for sure. I mean, if you'd have told me a few years back, hey, you're going to start a tech startup, I'd probably have laughed at you. You're crazy. That's not my thing. um i have always enjoyed solving problems.
00:03:32
Speaker
yeah I like thinking outside the box. I like looking at problems and seeing about innovative ways to solve it. um And as you say, this is this is a large problem. It's something that organizations are really challenged with. Candidates are feeling the pain. And so I really felt that it was somewhere that my skills could really bring something valuable to bear.
00:03:50
Speaker
And it just really genuinely excited me. You know, it's one of those things that solving that problem for people, we're taking on so many different elements, so many different roles when you're forming a startup. It's just really exciting. And that kind of constant change, that constant need to to think outside the box is something that just really always appealed to me from my time working at startups in previous lives.
00:04:12
Speaker
um Peter, your company is um is doing some very, very cool stuff with AI in the world of applicant tracking. So tell me a little bit about Vetson. What does it do? What exactly is it for for those listening?
00:04:30
Speaker
Yeah, the the the quick answer is we're really alleviating a lot of the stress at the top end of the hiring funnel. um So ultimately, you know organizations are facing an influx of candidates applying for roles, sometimes in the thousands. And a lot of those candidates are fake. Some of them, they're not even human beings. They're just robots applying. Some of them are just grossly underqualified. you know People hitting easy apply on 500 jobs and you know Ultimately, they're faced with this mountain of people to try and get through. And so to be respectful of the candidates experience, you know how do we get through that noise and get to the really good fit candidates faster? So our platform actually does that through screening resumes automatically and then sending them through to an AI interactive two way dynamic AI conversation to really screen and understand the real fit candidates and then forward those on to the hiring team so they can get to those candidates faster.
00:05:22
Speaker
I see that a lot. In fact, I hear about that a lot where, you know, there's countless applicants that actually look amazing on paper, um but they're not real. where where are they Where are they coming from? and and why are we actually seeing that? Like, just out of curiosity, what what does, you know, what do these bad actors have to get out of it?
00:05:43
Speaker
Yeah, I mean, there's there's different elements. Some of them aren't bad actors. Some people are just desperate for jobs, you know, and so they're inflating their CVs and resumes to try and fit the position better than they're actually qualified for. I see. So they're real people, just not real skills. Sometimes, yeah. and then But then the bots and things, it's really about, you know, data probing, trying to capture information, get information from the organization. um Sometimes it's just about getting, you know, equipment or paychecks,
00:06:11
Speaker
the initial paycheck for a month before then so anyone figures it out and you know there's actually been documented cases of this happening you know people actually hiring fake candidates and looking at paychecks and then there being nothing on the other end of it think there's actually been arrests made and things so you know it's it's a problem that's actually becoming very
Challenges and Adoption of AI in Hiring
00:06:28
Speaker
very real and Remote work is making it more prevalent. It's not because of remote work, but you know the fact that people aren't on site and can't be seen some of these times, it makes it much harder to detect. So having something that kind of helps screen that out at the early stages becoming more and more vital.
00:06:44
Speaker
That's unbelievable. And then on the on the flip side, you know you hear so much about... um tools, technology, sometimes weeding out folks who don't have an opportunity to to get seen, whose whose resume, right, or application doesn't get surfaced because of the overwhelming influx of of how many are are coming through. Hiring managers simply don't have the time the tools, the bandwidth to go through all 500, 5,000 applicants that come through, um you know which can be demoralizing, I think, for a lot of folks who are in the job search, who have been doing it for a long time and feel like they're not really getting a fair shake. And so it sounds like this is ah a solution to make sure that everybody has an opportunity to get seen.
00:07:28
Speaker
Yeah, and that's and that's really our mantra, right, is to give everybody that chance and that opportunity. So it benefits both sides. So the organizations get to see the really great fit candidates that they might otherwise miss. And the candidates get a chance to have their voice heard and just have an opportunity to share their skills and experience. You know, a lot of systems out there, they filter out based on keywords. um our Our resume screening doesn't do that. It actually reads the content of the resume and understands their skills and achievements. But you know if it's filtering out in keywords, you can miss a really great candidate just because they missed one word from their resume. It's kind of ridiculous situation. So how do we make sure that that doesn't happen? And like I say, this is to benefit both sides of it. There's a little bit of ah a them and us that's going on right now. you know Candidates aren't trusting organizations and organizations are saying all the candidates are fake. And and it shouldn't be that way, you know, and and I think by producing something that helps cut through all of that and get the real candidates in front of the organizations faster and cleaner, I think that's where the the real value comes through.
00:08:29
Speaker
Tell me about the organizations that come that come to you, or or we don't have to name any names, but what kinds of organizations come you? What are the challenges that they're experiencing? Is it just the volume? Is it the quality? um yeah I'm kind of curious, or or or the solutions that they're actually looking for you know when they come your way.
00:08:47
Speaker
Yeah, and I mean, a lot of times it's the the volume element, but volume can mean a couple of different things. you You've got the obvious volume with enterprises that that we work with. They've got tens of thousands of applicants on a monthly basis. you know That's the kind of volume that people think of when they think of high volume. But we do work with you know startups and scale ups who are trying to hire. They've got one recruitment person hiring for 15 roles. That's just an impossible level of volume. So to those large enterprises, they wouldn't think it's anything, but to that recruiter, it's it's everything. you know So we work with all different sizes of organizations here, just finding a way to streamline that process and get to the good candidates faster. And then you did mention it, you that quality of hire is important. Having consistency throughout the interviews. You know you get three different people doing you know the interviews and they can ask three different questions in three different ways, and depending on their you know their own personal bias or whatever else. The outcome can be different each time. So providing that consistency and that quality of hire is something that's really important too. So any organization that's looking for that tends to think and come to us and have those conversations. But it's no one specific industry or sector. It's across everything from blue collar work, manufacturing, healthcare, you know tech, software. you know' it's ah It's a problem that faces every organization.
00:10:05
Speaker
It really does. Do you have an ICP? Or I'm curious, like where did you where did you start? Was it with enterprise level? Was it typically for white collar? Or was it in the you know super high turnover, um you know more small business ah big verticals?
00:10:22
Speaker
I think, you know, staffing and recruiting firms jumped at it straight away. You know, their whole business is built around, you know, hiring with efficiency and quality and protecting their brand. So that's kind of, they were the first ones to kind of dip their toes in because corporates still have this ah concern about, well, AI, do we really want AI to be our candidate's first experience? I have my own thoughts on that. That's better. a separate conversation. um But ultimately, as those organizations started to warm to it, you know we've started to see the corporates come in more and more. um And we see it you know a lot of times, things like you know software engineers, things like that, there's really, really high application volumes in those sorts of roles. So tech companies are really leaning on this as a way of streamlining that sort of thing.
Future of Work: AI's Impact on Roles and Skills
00:11:03
Speaker
But yeah, we've we've worked with healthcare organizations, tech companies, you know there's no one specific org.
00:11:10
Speaker
So Veton is all about ai um are Are there companies you work with or organizations in general that are sort of eager to embrace this? Because you mentioned, right, corporate. I think at the corporate level, some of them are really ah concerned, right? I think that was a pretty good word. Concerned that that was going to be the first the first touch for um for applicants. Do you see a lot of reluctance just in general to use AI tools or are folks starting to invite it more into their regular workflows?
00:11:41
Speaker
No, it's really... It's really broad. I don't think there's, and there's not too many people are kind of in the middle. You know, there's a lot of people that jumped at it. They're embracing it. They realize that this is the future and the way things are going.
00:11:53
Speaker
um And so they're really jumping in. We want to be at the forefront of that wave. if We want to get this in. We want to make sure that we're doing it right. And so they're jumping at it. And then there's no one really in the middle, but then at the other end, it's like, yeah, there's no way we're going to do this. You know, AI, we don't want to implement that. We don't think it's human enough for the hiring process. And, you know, no matter what you say, they won't really embrace it.
00:12:14
Speaker
I feel that at some point they're going to have to, you know, the way the world is going. i think it's going to happen whether they like it or not. But ultimately, that's kind of the view of some. um And I don't think there's not that many people who are sitting in the middle. It seems quite a polarizing subject. Yeah.
00:12:28
Speaker
Yeah, no, that's fair. I mean, I kind of see the same thing, right? it's it's you're You're either in a crowd of people who use it every day or people who haven't even tried and try and try and using ai at all in their life. um So I know that not everybody's embracing it with open arms. And in the workforce, I think some still have a lot of anxiety about how it's going to impact them.
00:12:52
Speaker
and You know, both, you know, the people sitting in the side of the table that's you know, doing the interviewing, the HR teams, and then some on the other side of the of the table, right? The the workers will feel like they might get replaced from it or they might not be able to get jobs or hired because their skills can be replicated by some agents.
00:13:12
Speaker
Yeah. You know, so they fear it's going to take their jobs, you know, and ah and a huge portion, I think, of entry level and maybe less skilled workers are are where they're going to end up unemployable. Um,
00:13:23
Speaker
Curious your take on that. I mean, is that a legitimate fear? What do you see with regard to how people are using your technology and the roles that they're looking for? And how can business leaders, I think, you know, if it's not a ah legitimate fear, how do they aswash that kind of worry?
00:13:40
Speaker
Yeah, and that's it's a great question. I think it's it's definitely legitimate fear. um Whether it's as bad as some people think or not, I don't i don't know you know. Certainly from my own experience on the the hiring team side, you know the way I always discuss this is we're not removing recruiters from the process. We are freeing recruiters up to focus on what they signed up to do in the first place. Recruiters didn't sign up to read hundreds of documents and do a bunch of admin. They signed up to form human connections and understand who's going to be the best fit for their organizations and then manage them through the lifecycle with that organization. So the way we see this is ah it's a tool, right? It's
00:14:16
Speaker
you know you' You're going to drive in a nail. You could use a shoe or you could use a nail gun. Both will get the job done, but one of them is going to take a lot longer and one of them is going to be much more efficient, but they still need somebody to either swing that shoe or use that nail gun to kind of make it work. So I think in certain areas, it's not so much that the jobs will be removed. It's more just that the jobs will change and it will look very different. And I think that's a really big piece for you know the leadership as they're bringing in ai is making sure they clearly communicate with their teams. This is what we're doing.
00:14:45
Speaker
This is why we're doing it. And this is what it means for you. Managing those expectations that it's not to replace you. It's to change your role from this, you know, more sort of admin kind of day-to-day type role to this more strategic, you know, revenue generating or whatever kind of role that's sitting on the other side of that work that you don't get to normally because you're too busy with the admin stuff.
00:15:08
Speaker
ah First of all, like I can see why you're such a high performing salesperson. um that it's a really It's a really good visual. um And I think that it kind of um hammers home why this is such a ah great tool. That was pun intended. um So I hope that landed well.
00:15:30
Speaker
But You know, it makes me curious because you just mentioned something about leadership and and bringing in tools like this. Do you find... So with...
00:15:41
Speaker
you know with those With those companies that have brought this in, with those you know the corporate where corporate has brought this in and wanting to implement this tool, do you find that it's mostly at the request of the ah HR leaders or the folks in that ah HR space who are doing the hiring, who are making the request for tools like these to improve their lives?
00:15:59
Speaker
Or do you see this as leadership bringing this to the to the table and saying, here's something new, I want you to use it? Yeah, i think I think it's driven a lot of times by the leadership.
00:16:11
Speaker
um Where are we see the most success though is when the leadership get buy-in from their teams. So we have seen situations where there's been a lot of friction because the leaders decided that this is gonna streamline the things they care about, you know the quality of hire, the speed to hire, all that kind of stuff.
00:16:28
Speaker
but they haven't communicated to their team. you know This is why it's going to be valuable to you as well. um And so that ah kind of friction comes up because then to your earlier point, well, this is going to replace me. I'm going to out of a job. you know We've actually seen recruiters test the platform and give the feedback to the leaders. Oh, no, it was terrible. It was rubbish. And we've listened back to their interviews and been, yeah know that was really good.
Leadership and Communication in AI Adoption
00:16:50
Speaker
i You know, there's there's that suspicion that it's like they're just nervous about this. of That is really good. Do they need me if this works? And so I think that's the really key element, like I say, is just managing that change and that perception of this is what we're doing and this is why we're doing it. You're not losing your job. We're just making sure that when you do your job, it's the more efficient, more strategic type tasks.
00:17:11
Speaker
Yeah. So I'm curious how often you find yourself or, or, you know, somebody in, in, in, in your organization in the middle of that conversation, right? Because we're so early in AI, right? And the adoption is, well, well, obviously technology is moving faster than the speed of light, right? There's some slow to adopt, there's some fast to adopt, right? But throughout the organization, there's going to be some quicksand.
00:17:36
Speaker
And I'm kind of curious, just in your position, how often do you find yourself in the middle of that conversation where you're actually working with the hr you know, person to help them understand how to use it and why it's going to augment their role um rather than the leadership actually having that conversation with them?
00:17:57
Speaker
i I, try and encourage it as much as I can, you know, because I think,
00:18:03
Speaker
Like I say, the fear, it may not be as much as bad as people think it is, but it's it's definitely valid, the concern that people have. And I think a quick conversation, yeah nine times out of 10, a quick conversation about what it is and what it means.
00:18:17
Speaker
And everybody's like, oh, this is great. Yeah, much rather do that than what I'm doing right now. yeah um And, you know, so i try and I try and get involved in those conversations because I think being able to answer their questions about, well, how does this work? How does that work? What happens if this happens? and Takes that fear away a little bit and they realize, oh, okay, this isn't what I thought it was. This is actually a good thing.
00:18:36
Speaker
And so I try and get inserted in that as much as possible. But we do see it all the time regardless. You know, we'll see the leadership. It's almost like they're going to their own teams for approval, um which is an interesting sort of reversal from, you know, days in the past where it's like,
00:18:50
Speaker
that The team had to go to the leaders for approval. yeah It's very much a case of I want to make sure my team are comfortable with this, which is great to see, right? The leaders are caring about their team and how they feel in their jobs. And that's why I want to try and help as much as I can on that.
00:19:04
Speaker
So this is kind of a good topic to into today. jump into bias, I think, in the hiring process, right? Because we talk about how it can augment, you know, some people's jobs, help them do it better, faster, you know, be more productive. um But there's a lot of, there's there's there's some controversy, right, in using AI in the hiring process. I think there's a lot of fear about it bringing bias um into that into that process. There have been situations, you know, where AI has been
00:19:38
Speaker
I think, or at least perceived to have been discriminating based on a variety of different things, right? Race, age, gender, you know, whatnot. um How can those things be avoided, right? what What steps do companies take to prevent AI from becoming biased? Is it inherent in the technology? Can you use it a different way to make sure you're avoiding any sort of problematic situations? Yeah.
00:20:04
Speaker
Yeah, absolutely. And this is something that's really, really important to us, right? is Part of the reason we built this is to ensure everyone gets a fair shot in the process. you know So you hear a lot in hiring about, oh, my gut says that this person isn't the right fit. And a lot of times that really just means my own unconscious bias says I don't like this person for some reason. you know and So organizations hire people who are like them. And so that kind of crushes innovation, it crushes diversity, and that's that's not the best way to drive an organization. So we're really passionate about this. So I can't speak for all organizations out because there have been certain situations, but there's things that we've been very mindful of in terms of building layers within our platform to ensure you know, it's programmed to make sure it cannot ask illegal questions. Um, it was interesting. We actually had a client who we chose not to work with, who was trying to ask illegal questions and they were saying, you know, we wanted to ask this. and but It won't do that. Um, that's not a good question to ask. And, uh, they're like, well, you're, you're AI just keeps sending people through, even though we tell them not to ask this is like, good, it's doing its job then. And so we actually chose not to work with them because they were trying to make it ask an illegal question. Um, And so we've built those layers and those protections around it to make sure you know it redacts.
00:21:13
Speaker
yeah It doesn't care about the person's name. It redacts their personal information. if they have their date of birth on the resume, it ignores it. you know We've programmed it to ignore all of these things. It's literally me just looking at the job description.
00:21:25
Speaker
and the person's skills and experience, do they line up? Doesn't care about anything else. All the other parts of the hiring process then are left to the humans at the other end. This is just screening out those initial stages to say, can this person do this job? Yes or no. And we've built a lot of safeguards into that. Things like lie detection. you know We know there's ones out there that use facial recognition patterns for lie detection. you i feel there's a risk in that. A nervous person can come across as lying. And it's not they're just nervous or you know perhaps they have some disability that that creates something in their facial expression that means you know it comes across as as a lie.
00:22:00
Speaker
That's not how we build our cheat detection. We build it on speech patterns and things instead. So we're very, very mindful of making sure we put barriers around that. But it's something you have to be really, really aware of, because if you just let AI do its thing and go out into the whole internet, it can look at all sorts of crazy sources for its information, and that can lead to problems. So it's something we've built really strongly around is making sure it can't do that with our platform. You you mentioned skills and experience. What about education?
00:22:25
Speaker
Where does that fall? It depends on how important it is. you know It's like, have they got the certifications they need to be a successful doctor or things like that? Then, okay, that's fair and that's valid. um you know We did have one organization ask us, can we rank people based on the school they went to?
00:22:41
Speaker
And we said, no, we we can't do that. our so from our point of view, it doesn't matter. Do they have the skills, do the job, yes or no? It doesn't matter what institution they went to to get the skills to do that. So, you know, there's there's a line on that where you have to be very careful in terms of how you how you look at it because there's certain situations where education is required. know, you can't just be a doctor. You have to go to medical school and pass it to the law. Well, I hope so anyway. um You know, but at the same time, we want to make sure it's not, you know,
00:23:10
Speaker
Looking at the things that don't matter, you know, I've got a degree in physics. Does that make me better a job than someone else? No, it doesn't. Do I have the skills to do that job? Yes or no. So let's look at that.
00:23:21
Speaker
You know, i think that, so i it's it's really clear and it's obvious, right? AI can be super beneficial in this hiring process. You know, i would argue across the entire employee lifecycle, right?
00:23:34
Speaker
You know, from your perspective, what are some of the benefits HR teams are seeing from adopting AI tools across human resources and people ops, right? Maybe not necessarily just in the in the recruiting. I mean, there's obviously benefits starting with recruiting.
00:23:49
Speaker
um Not easy for for humans to give proper attention to hundreds of applications for a single role, right? We sort of covered that part. And we just talked about bias. You know, I think humans are probably worse at it than than machines. But talk to me about the whole sort of employee lifecycle in human resources and people ops.
00:24:09
Speaker
yeah I think... It's anywhere where it takes away administrative tasks and lets the HR team focus on what they signed up to do. you know People get into HR because they care about the people in their employee. you know They want to make sure that they're treated well or treated right, and they're rewarded fairly, that they're happy in their roles, that they're being productive for the organization, that the organization is getting their best out of their team, all of those kinds of things.
00:24:32
Speaker
And if they're focused on mundane day-to-day tasks then they maybe don't have enough time to do that in the in the way that they should. So that's the first thing is kind of removing that side. The other thing I think is AI is incredibly good at pattern detection. So things that humans might miss you know within employment, once the candidate has been employed and they're working at the organization, you know their behaviors, their traits, their results, all of these things, AI can look at patterns and maybe predict, you know okay, just keep an eye on this person. Things are dropping in a way that maybe you don't notice, but I do. So you might want to have a conversation with them. Stuff like that where... It can sort of lend a little bit of an extra eye to the analysis that humans might sometimes miss.
00:25:11
Speaker
You know, in order to sort of best embrace all of these tools, you know, these these AI tools and platforms, i mean, what kind of advice would you give to HR leaders that they, what they need to learn or what they should prepare, right? Just to remain competitive in their respective roles.
00:25:28
Speaker
Yeah, I think the first thing I always say is, like, look at where you really need it. So AI is cool. The people who want to embrace AI are going to embrace AI. It's like, let's put AI in place. Where? Everywhere. You know, why? Yeah, exactly. AI.
00:25:40
Speaker
ah You know, they don't even know why they're doing it, you know. And i think it's really important. It's like, what problem are we trying to solve? You know, what are we trying to do here? What you know issue are we having as a business that we need to fix?
00:25:52
Speaker
okay, that this AI can fix that or this AI is not actually going to do anything for that. and so that's where we see AI implementations fail a lot of times is they've implemented it because it's something they want to do without really understanding well what's the outcome here? What does we want the end result to look like?
00:26:06
Speaker
So that's the first thing is really understand, you know, where where are you using it? Why are you using it? What do you expect in terms of those outcomes? um And then the other element, like I say, is just communication. you know, with the team, with their their own leaders, just making sure everyone understands this is what we're doing, you know, that that kind of assessment I talk about, this is what we've done, this is why we're doing it, and this is what we're going to get out of it. So it's both doing that analysis and then communicating it clearly across the organization. And then the last part is kind of start small. you know, is don't just jump in and change everything. It's like pick something, start small, show the value and then grow it from there. And I think that seems to be the where we see most of our implementations have the most success is kind of branching and kind of scaling out from a successful initial implementation.
00:26:50
Speaker
That's smart. And I think that's really good advice. Um, you know, you talked about it generally coming down from leadership, right? Implementing all these, these new tools.
00:27:01
Speaker
And I'm kind of curious, you know, In order for leadership, in order for their workforce, I guess, to be more AI ready or to prepare for the new tech that's coming kind of down the the pipeline, how does leadership set appropriate expectations for their workforce? So you started off with a really, really great, you know, some great advice, right, to start with outcomes, I guess, right?
00:27:30
Speaker
um How do we set good expectations, though, for this workforce with regard to the expectation expectation with regard to the outcomes that we want, right? I guess, you know, because there's going to be some people slower to adopt it, faster to adopt it. ah Adoption might not even look like what leadership expected it to be.
00:27:47
Speaker
Right. senate yeah yeah I think that's an age old challenge. And I remember being on sales teams when leadership said, right, we're going to use this new tool. And the sales team are like, you know i' I've done things my way for the last two years. I'm not changing. That sounds terrible. um And it's not that the tool wouldn't have made them more efficient. It's just people don't like change a lot of the time.
00:28:07
Speaker
um And so I think you know those expectations, getting them clearly bought in as part of the process of that, well, okay, what outcomes do you need? you know from your point of view as a recruiter, from our software point of view, you know what challenges are you facing? What do you want the outcomes to look like? Okay, my outcomes need to be this, yours need to be that, and they're actually aligned in terms of the solution. It's actually going to solve both.
00:28:28
Speaker
So getting them to see what their own personal outcomes are going to be from it, getting them emotionally involved in in the success of it because of what they're going to get from it too is going to be key. So I think it's really important that they understand their team, the challenges they're facing, and and will this platform also help them? um And if it doesn't, then, okay, there's there's a misalignment there. You know, I want this and you want this.
00:28:51
Speaker
Okay, why is there a misalignment? That's a bigger conversation, bigger thing solve. So I think it's really worth making sure that those two things align, but understanding that with a bit of empathy for the team in terms of what they're facing, it really helps.
00:29:02
Speaker
You know, you're in an interesting position given what you do and the clients that you speak with. And I'm kind of curious, do you see, you know, a lot of, do you see organizations that are hiring for jobs whose, you know, roles just are really not quite even fully defined yet simply because they have something to do with AI or some new technologies and implementations, you know, and I'm just kind of curious, like, or or even, you know,
00:29:31
Speaker
I'm curious how in some organizations there may be roles that have to change or that simply don't even exist yet. like how do you What do you see? Yeah, I mean, it's it's just moving so fast. I think where the mindset needs to be, I believe, is hiring on skills, certain types of skills, hiring on an appetite for change and uncertainty.
00:29:55
Speaker
you know I think making sure people are comfortable with change because it's going to change. You said yourself, it's moving at the speed of light. you know, the one certainty is it's going to be different in a year than it is now.
00:30:06
Speaker
yeah You know, how is this person going to handle that? You know, what base skills do they have versus hiring for a job title as such? Because that job title might change because the role will change. But what skills do they have in terms of how they work with people, in terms of how they communicate, in terms of how they you know solve problems, in terms of their knowledge of the specific skills and qualifications for for your particular organization. Instead of hiring for a job title, hire for those skills, hire for appetite for change. And I think that's kind of the way we need to look at it because yeah, it's going to going to different.
00:30:38
Speaker
It's going to change in a world so fast. Does VITAN provide any kind of consultation like that to help organizations hire better or things to consider to make their own process? um I don't know, you have better outcomes.
00:30:56
Speaker
we're We're a little bit mindful of advising organizations and like like, listen, you need to hire people like this. We can help them as they're going through the hiring process for particular roles in terms of working with them and communicating with them of, well, what do you expect in terms of what makes someone good for this role versus doesn't?
00:31:13
Speaker
Okay, are you articulating that clearly? Do you understand that clearly? Because that's the big thing with with any interview, even human interviews. If you don't really know what you're trying to hire for, you're going to ask disjointed questions. You're going to be looking for the wrong things and you're going to make a bad hire.
00:31:27
Speaker
yeah um And there's lots of organizations and people out there that do really good jobs of helping organizations understand but what are we hiring for, why, and how. um Once they have that defined, we work with them a little bit in refining, well, okay, how do you get to that? you know What are the sorts of things you need to look for at this early stage of an interview did to see, does this person have those skills and qualifications or do they not?
00:31:50
Speaker
i'm i'm curious a little bit about the platform. um Is it like typical B2B SaaS software where I can actually just sign up and put in the things that I need to and and get going? Does it require some consultation or to work with an account manager to kind of help me put it together? What's the process to get started?
00:32:10
Speaker
Yeah, I mean, it is something that you can set up and just get rolling with really easily. And we have seen organizations do that. A lot of times they'll sign up, I'll offer an onboarding call. You know, my team will get on the onboarding call and like, right, well we're already running interviews. So can you help us? It's more Q&A. So it's more of that consultancy. okay Now, that said, i think there's a huge value in having conversations with myself for the team because ultimately it's more about that change management around what you're trying to do. The solution itself is incredibly easy to use.
00:32:39
Speaker
Okay. What are you trying to achieve from this? What outcomes you want to achieve? So that whole assessment thing I spoke about earlier, you know what are we trying to solve for? What do we want the outcomes to look like? We can help with that part and the articulation of that. And I think you know getting that right before you purchase the software means that your implementation is going to be much more successful.
AI's Influence on the Gig Economy and Work Classification
00:32:57
Speaker
So Technically, very easy to set up. You could absolutely do it. And we've got some really small organizations that use it. yeah They don't need us. you know They know there's four or five people in the organization, and they're like, let's just do this. um That's fine. But for those large organizations, I think there's a ah lot of value in terms of setting up those goals first.
00:33:13
Speaker
Yeah, for sure. So keeping an eye towards the future, kind of getting back to that, tell me some predictions for the future of work. What what do you think is going to change? whats What's going to be the most dramatic change that you see coming down the pike?
00:33:25
Speaker
Wow. I think it's just that. It's just change. I think people are going to have to be more comfortable with uncertainty um in the workforce. I think it's just that roles are going to change and shift so quickly. The idea of I'm ah you know i'm an account executive.
00:33:41
Speaker
that might disappear because, well, what does that mean? So what does an account executive look like in one year, two year, three year, four year time, you know, in terms of how much is being done by AI? Am I an AI manager who's actually selling or am i you know, managing an AI that's doing the selling for me? Those kinds of conversations. So I think that just being able to handle that kind of uncertainty is something I really, really see. um But I think over time, people are going to embrace it more and more.
00:34:05
Speaker
They're going to embrace AI more and more. And so it's only going to spread throughout the organization. So for me, it's going to be a major increase in in AI being a requirement for people in terms of their roles, you know, must be able to do X, Y, Z with AI. I think that's going to be more more of a requirement in the in the future workforce.
00:34:24
Speaker
You know, there are statistics, you know, that that show how much, you how much of a shift, right, is is that the that the, at least in the U.S., that the workforce is moving towards, you know, the gig economy, right? That there's, you expectation that greater than 60, maybe even closer to 70% the entire U.S. workforce in the next five years is going to be involved with it somehow.
00:34:50
Speaker
It doesn't necessarily mean that, you know, it'll be there full time. It could even be in some tangential way, right? Yeah. I'm kind of curious on your end, what do you see in terms of though how the hiring landscape is changing for the diversity of worker classifications? Do you see a lot more contractors? Are things moving towards towards more part-time? Is it typically, you know, salaried, full-time work? How do you see that changing at all?
00:35:19
Speaker
i you know I think it's already changed significantly over the last year or two. I've certainly seen a lot more of you know the the fractional type roles coming through. you know I've seen ah a huge increase in that even just in the last year or so.
00:35:32
Speaker
I don't think that's going to change anytime soon. um But I think a lot of the core workforce will remain largely the same for for the foreseeable future. ah But Again, who knows, you know, with, with, you know, I could be completely wrong. And I think, again, that's back to my earlier point of, you know, I've got to be comfortable with that, that as we sort of look at those trends over the coming six months, you know, what does that look like? What could that be? How do we best prepare for that? And then when we get to that six month point, you know, well, where are we now? does the next six months look like? I think if you're trying to plan two or three years out, you're in a, you're in a risky position because of the way things are going.
00:36:07
Speaker
There's a lot of stuff people couldn't possibly have predicted, you know? Well, unfortunately, we can't train our AI to tell the future. um whoever Whoever builds that one next has really got something for all of us.
Staying Ahead: Vettin's Vision for the Future
00:36:20
Speaker
So with the new world, i think, of of tech advancements, like what should tomorrow's leaders be prepping for? We've talked a lot today about technology.
00:36:32
Speaker
today's leaders, today's, you know, hr operators, are there skills and competencies that they need to focus on, or that tomorrow's leaders need to focus on? Are there knowledge gaps that need to be filled? What do you think about that?
00:36:47
Speaker
I mean, I definitely think they need to have an eye towards their workforce understanding AI, you know, how it works, the limitations, the benefits, at the risks. um So there's definitely that element of it. I think more and more that's going to become prevalent. I think, as I mentioned, just prepping your workforce for change.
00:37:05
Speaker
How do we manage change management? How do we keep our finger in the pulse of our employees to understand where they are mentally with all of it? Because, you know, there is a lot of uncertainty and some people handle that better than others. You know, so how our team feeling about that? I think that's going to be more and more important is having ah finger on the pulse of that, to understand where they are, where they sit, how they feel about it.
00:37:25
Speaker
um And then having ways to to mitigate and manage for that as they go. So I think that's really where I see the biggest area of focus needing to be. And then obviously that sort of strategic forethought of like, hey, what's the next thing? you know How do we then apply that to what we're doing right now to make ourselves better and more efficient? And how do we use that in a safe, risk-free, ethical way?
00:37:46
Speaker
So kind of keep those things in mind. you know You talked about wanting Vedant to be on the on the forefront, right? um you know of This proliferation of of AI.
00:37:57
Speaker
um With all that advancement, I'm kind of curious, I mean, What do you think your own work is going to look like here in the next two years, three years, five years, 10 years? you see anything changing with the work that you do or that your company does?
00:38:11
Speaker
Yeah, I mean, I feel that there's going to be areas where the inbound application side is going to become less and less possibly. I don't know. I'm guessing. But, you know, as matching tools, as sourcing tools get better, the ways of finding candidates and understanding who's a fit, who's in role, the ways for candidates to put their hands up, you know, um I think it's going to evolve. And so being able to capture that and ensure that you can kind of facilitate those conversations faster and sooner,
00:38:41
Speaker
I think we'll see a huge change in how hiring is done because, like I say, that the reason we do so well right now is that the process is broken. you know Candidates have distrust, companies have distrust, you know and and this is just becoming ah a snowballing effect in terms of the issue that we're facing. So we solve for that right now. And what we're looking to see then is, okay, once we kind of solve for that and bring things back to a nice middle point, how do we keep that flowing in a nice status quo, help candidates get in touch with the roles that they're right fit for faster and help the organizations get in touch with those people faster. So kind of short circuiting a lot of that back and forth that we see right now.
00:39:16
Speaker
I love that. I'm kind of i kind of'm curious. So I always like to wrap up with this question. you know if you if you If you have this you know single piece of advice, you know whether it's a business leader, whether it's an ah h r you know leader, somebody in that space, but when it comes to adopting AI in their human resource processes, people ops, you know whatever it happens to be, um what's that one thing that you tell them, right? The the one piece of important advice that you want to leave with them if you only have, you know, you're a minute, you know, on an elevator to the top floor before they walk out the door. What's that one thing that you have an opportunity to tell them? Good question. Um, slew down to speed up, I think. So, you know, what I mean there is,
00:40:00
Speaker
do that do that thought process about what am I trying to solve for here? know Don't just implement AI for the sake of saying, I'm implemented AI, look at me, I'm super cool. Implement it to solve a problem, understand what that problem is and what the outcomes need to be. But don't Don't drag your heels on it because your competitors are going to be implementing it now.
00:40:20
Speaker
And they've already done that. And so if you're doing that a year from now, your competitors have got the jump on you. They've been more mature in it. They're more practiced at it. And they're going to be better at it than you are. So, you know, have that, think about it and then and then do it. Don't wait.
00:40:35
Speaker
I love that. Slow down to speed up. ah I think that probably needs to be framed on everybody's on everybody's wall office in their office space. I really appreciate you taking the time to join me, Peter. Thank you so much for today.
00:40:49
Speaker
Yeah, no, listen, I appreciate it I've enjoyed the conversation. it Yeah, it was a lot of fun. And of course, thank you all for joining us. This is Mustard Hub Voices Behind the Build. Be sure to subscribe so you don't miss the next episode. i also recommend visiting mustardhub.com. There you can learn more about Mustard Hub and get started for free. Discover how we help companies become destinations for workplace happiness and turn culture into a competitive edge. Until next time.