Why AI Won't Fix Broken Hiring Habits

Joel Quintela (left) and Andy Goram (right) discuss why A.I. isn't a magic fix for broken recruitment practices.

Let's cut to the chase—your hiring problems aren't going to disappear just because you've thrown AI into the mix. Don't get me wrong, AI can automate, streamline, and even improve certain hiring processes. But, as Joel Quintela explains in our latest Sticky From The Inside episode, technology alone is not the solution.

Here's the deal: AI excels at quickly screening out unsuitable candidates. But selecting the right person? That's human territory. Joel, a seasoned HR tech innovator with a deep psychology background, insists hiring is fundamentally a human decision-making process.

Joel breaks hiring into two clear phases: "screening out" and "selecting in." AI is excellent at handling the repetitive tasks in the screening phase, but falls flat when evaluating nuanced factors like cultural fit and managerial compatibility—factors critical for long-term employee success.

The problem arises when businesses mistakenly hand over crucial decision-making responsibilities to AI, assuming it can accurately judge complex human dynamics. The reality? Without a clear strategy and strong leadership involvement, you're just automating poor practices.

Joel's advice is clear:

• Commit to making intentional, high-quality hires.

• Define clear job profiles covering competencies, culture, and team fit.

• Use tailored assessments to enhance—not replace—human judgment.

Your challenge today? Reflect on how your hiring practices align with Joel’s approach. Are you using AI wisely, or are you just speeding up a broken process?

You can listen to the full conversation below, to discover how your organisation can make better hires, not just faster ones, or read the following full transcript if you'd prefer.

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A.I. is Everywhere, But Is It Fixing Recruitment?

[Andy Goram] (0:10 - 4:55)

Hello and welcome to Sticky from the Inside, the employee engagement podcast that looks at how to build stickier, competition-smashing, consistently successful organisations from the inside out. I'm your host Andy Goram and I'm on a mission to help more businesses turn the lights on behind the eyes of their employees, light the fires within them and create tonnes more success for everyone. This podcast is for all those who believe that's something worth going after and would like a little help and guidance in achieving that.

Each episode we dive into the topics that can help create what I call stickier businesses, the sort of businesses where people thrive and love to work and where more customers stay with you and recommend you to others because they love what you do and why you do it. So if you want to take the tricky out of being sticky, listen on. Okay then, now unless you've been living under a rock you'll know and it will certainly feel like AI is practically everywhere at the moment.

It's also having an impact on many of the things that we talk about on this podcast but especially the area of recruitment. AI is everywhere in hiring, it's screening resumes, it's automating assessments, it's even predicting which candidates will succeed and that all sounds great right? But I'm not so sure.

If your hiring process is broken in the first place, if your leadership doesn't understand what actually makes a great hire and who you're looking for and if your culture actually repels top talent, I don't think AI is going to save you. It's just going to make bad hiring decisions faster. AI alone won't, I don't think, fix broken hiring.

And we've talked about recruitment being broken before, there has to be a better way and that's exactly what we're digging into today. My guest is Joel Quintela, an HR tech innovator with over 25 years of experience in making recruitment smarter, faster and fairer. But what I think makes Joel different is his background in psychology.

He doesn't just think about the tech, he thinks and tries to understand the people. He understands how humans interact with systems and how leadership, culture and bias all influence the way we hire. Because here's what I believe, AI is a tool in recruitment, I don't think it's a strategy.

What it is, great at I think, is increasing the likelihood of you making a great hire. But it cannot and I don't think will ever guarantee that on its own. I think the real game changer comes when you combine it with really strong, great leadership and a sound cultural strategy.

It's about building a culture that attracts the right people for your organisation and then using technology to help you find them more effectively, ensuring that that automation doesn't just mean dehumanisation of the experience, it enhances it. And then the whole thing has to reflect your values, not just park them for speed and efficiency. So if you're a leader or anyone who's ever wondered how do we make hiring more effective, not just quicker, or how do we use AI without losing that human touch, then maybe this episode is for you.

Stick with it, because I think this one may challenge how we think about hiring. Hey Joel, welcome to the show. Hey, thank you Andy, it's a pleasure to be here.

That's a great intro. Oh, well, that's very kind of you, my friend. I'm really interested in this conversation.

I'm mucking about like most people on the planet with AI. These topics, anything associated with culture, leadership, employee engagement, all that stuff I love. And we have talked about recruitment on this channel a number of times.

And the conclusion we've normally started with is that recruitment is broken. And I'm just hoping for some solutions going forward. I wonder whether at the start of this AI journey, things have got a little, a little too impersonal and a little too automated.

But I'm sure you're going to put me right and all that. But before we dive into it, buddy, why don't you just give us a bit of a better introduction to you, what you're up to, and where your focus is today?

Meet Joel Quintela: HR Tech Innovator with a Psychology Twist

[Joel Quintela] (4:56 - 7:43)

Yeah, thank you. So yeah, I'm a, I guess by education, I'm a business psychologist. I think in the UK, you guys are calling it an organizational psychologist.

I think I started my undergraduate career as a computer systems engineer and actually started programming in, you know, high school. But when I noticed that computer scientists were really smart, excuse me. So those classes were kind of difficult.

Then I took a psychology course, and I just, I just took off. But ever since then, I just been keeping the two, you know, the two passions close together, the people side of it, and then the technology side of it, and how do you merge those two things. And there's a third piece that I don't necessarily talk about, but it's, it's a, you have to sort of understand that you're not the smartest person in the room, when you're putting these things together for your companies.

Because what works best for the company is what works best for them. You can't look outside and, you know, Verizon is doing this, Walmart is doing this. So you have to, you have to be very clear about what that is.

So you have to be honest with yourself, where you really are. And, and that's correct. Hiring is broken, to some extent, it's mainly because, because companies don't necessarily understand that they don't really, they don't really know how to hire great people.

So awareness is half the battle, I guess they say. So, you know, there are a lot of, a lot of things we can do to, to make hiring better. But you have to understand, number one, it is a prediction game.

It's a probability game, hiring is, and people don't think about it that way. But you're sitting here today, interviewing a candidate, you're trying to figure out if they're going to do well in three months, or six months, or nine months. So whatever you do now is gonna either help you make a good prediction, or make you make a bad prediction.

So you have to understand that, number one. Number two is you do have to be pretty serious about, about how you do that. And how do you, what do you need to do to increase your probability of making a good hire?

So yeah, it's broken. But it's not, it's not because we don't know what to do. Because we do.

It's more of the, you just don't do it, right? It's sort of weird. But anyway, that's job security for us, I guess.

[Andy Goram] (7:44 - 7:50)

Well, yes, listen, people doing things wrong, and you having solutions is always a good business model, I think.

[Joel Quintela] (7:50 - 10:52)

Yeah, it's always good that people want to buy what you're selling, right? That's kind of the number one criteria. So, yeah, you know, we've been doing this for a long time.

Organizational ecologists have been, you know, perfecting or trying to, you know, increase probability of success. So we actually do know how to do that. And then now, you know, you throw AI into the mix.

And it's sort of, it sort of disrupts or, you know, the process. But the reality is, you still do the same thing. It's, it's not something new.

We've been doing this for 100 years. It's the same concept. Now we just have another tool.

But people are going nuts with this tool. AI, I think we talked about earlier about the biggest misconceptions about AI and hiring or recruiting. Yeah, I would love to know your views on that.

I think there are two. One is what you're saying is that it can actually make a good hire for you. That's, that's what, you know, because mainly because we have a lot of vendors that have a lot of funding, that will tell you that, right.

And, you know, don't worry, my AIs can predict 99% of the time. And it's not biased. And, you know, they have very flashy sales reps and marketing, and you tend to believe it, but it can't, it cannot make good hires for you.

Yeah. The other one, which is a big one, is that it's easy to implement into your system. That's a huge misconception.

Especially if you're dealing with huge companies. You know, it's a huge management project, change management project. So most companies are not ready for that big wave of change.

But everybody thinks it's so easy to implement, why not just do chat GBT, and you know, we're off and running. It's not that easy. You know, and on all sides, you know, yeah, the recruiters, or the talent acquisition teams, but the hiring managers, I mean, that's, they're the ones that are making this prediction.

So, you know, it's, it's, it's the hiring managers you have to be focusing on. And they're not hiring every day. Maybe right.

So you start throwing in some, some extra, you know, steps that they have to do, that's going to be difficult for them. So you have to be really honest with what it's going to take to implement this, this project. So two things.

One, it's people think it's going to make a good hire for you, because that's what they're being told. Number two is, it's really easy to implement. And it is not easy to implement.

The Reality of Recruitment: Why it Feels Like Rolling Dice

[Andy Goram] (10:53 - 11:46)

I think recruitment is tough, regardless, right? And you forget about just the technology stuff. If I think back in my career, you know, I've worked in organizations where I am the hiring manager, because I'm the guy running the department.

And I've got, it's all on me. And I've worked in organizations where I've got specialists who are going to do the, run the hiring process. In all instances, if I wasn't involved or clear about what I was after, why I was after it, what sort of complementary and opposite skills I needed in the team, you know, if I was, if I didn't have a really clear view about where I was headed, and how and what I needed to meet that journey, it didn't really matter who I saw, it still felt like I was rolling dice the whole time.

You know, that's, that's, that's, that's the thing.

[Joel Quintela] (11:46 - 12:00)

That's exactly what we say, you know, it, you know, if you're not going to take hiring seriously, it's not rocket science, there are a few things you can do to increase that probability. But if you're not going to do that, then just flip a coin. Yeah.

And it's quick, it's quicker.

[Andy Goram] (12:01 - 12:23)

It's a lot quicker. But when you don't have that thought in there, and you haven't got that plan, and perhaps you haven't got an overriding strategy behind it, you're constantly in recruitment mode. And not because you've got loads of vacancies is because you keep getting the same vacancy, and you keep plugging it with the wrong individual.

And that that has to be the game that we're looking at here, I think.

[Joel Quintela] (12:24 - 13:41)

Yeah, I think it's I think it's even worse with AI. Because just you know, following that number one point, it's not gonna make a good decision for you. People are letting it do a lot of things in there, because it's easy.

I had a friend of mine, he's a colleague from grad school now at HireVue, you know, one of the big firms basically said, well, you can automate stupid. Pardon my language. But yeah, I could, you know, I could, I can, you know, set up something that makes you, you know, make, make bad hires faster.

Like you're saying, because you set those up, and then it's easy to just let the system do it for you. Makes decisions for you. And AI is not, is not intended to do that.

But if you're going to set it up, I mean, it's just natural for people to, you know, let's let it do everything for you. And then hiring managers, just imagine if you just let your AI make those decisions for you, it interviews for you, it tells you how to score interviews. That's, that's nuts.

I don't, you know, but that's what's happening.

[Andy Goram] (13:41 - 14:46)

Well, that's the thing I worry about. So in that in the introduction, I sort of said, I'd like to think I asked the question is this, because I'm an AI optimist, right? I think, I think it's in the long run, if we are smart enough in how we use it, I think it can enhance our lives, our jobs, all that sort of stuff.

And that's what I really, really, really hope. And in this particular topic today, somewhere in a part of business in recruitment, which I personally feel like we said before, is broken, this has to be a powerful tool somewhere in here to help us make it better. But if we use it incorrectly, it's just gonna make bad decisions faster for us.

And from your perspective, as somebody who is, I think, from what I've researched, trying to unpick this, and trying to make the hiring world better, what do you see, maybe as maybe as hopeful like I do, but what do you see the real benefits of using AI properly in this area of business?

AI in Recruitment: Strengths, Weaknesses, and Common Misconceptions

[Joel Quintela] (14:47 - 18:27)

Yeah, I think it's, I think it's, you know, we sort of operate from a tough love perspective, clients. So it's going to sound like that, as I'm talking it through. You have to understand that AI, at the moment, AI is really good at helping you increase your efficiency.

That means it can, it can help you schedule your candidates. And according with your, your hire managers, much quicker, which is huge. If you're hiring 100,000 people, that's a lot of interviews, and a lot of schedules, you have to coordinate.

AI is really good at that. It's also really good at, which is extremely important for candidate experience, the communication. So for a long time, companies had just treated applicants terribly.

So, you know, you're thinking you're the company, and we have to do what you want them to do. But that's not that's not true. And now it's sort of flipped a little bit where it's kind of the candidate is, is the one that's ghosting the company, because true number one thing is communication.

If you are not communicating at every step of the process with your candidates, they're going to drop out, they're going to ghost you, they're going to accept the position, just not show up, you got to go to the first day of training, just leave, because you didn't treat them with respect. And number one is communication. So it does those two things really, really well.

automating, especially the scheduling, and then also the communication through the entire process. That's what it does well. What it doesn't do well is make decisions for you, like we're talking about for and, you know, in the recruitment space or the hiring space, you sort of have to think about it in two ways.

It's a, there's a screen out phase of the recruitment process, where everything you're doing is essentially trying to screen out the bottom 30% of your applicants. And then there's a select in phase of the process, where now you have five or so candidates that you think are pretty good fits, and then everything you're doing from that point is selecting the right person. So there's a difference between screening out phase and selecting in phase.

AI is decent at helping you screen out the bottom 30%. It's pretty good at that, which means, you know, it can help, you know, it's the it's the initial screen interview for recruiters, or, you know, the one way video is pretty, is pretty popular where, I don't know if candidates love this, but you know, your company sends you a link, you record your responses to some questions, and then send it back to the company. And those are screen out processes.

And it's, it's decent at that, that to the bottom half of the or the bottom third of the applicant pool. But when you start looking at the top third of the applicant pool, it can't do those things. It can't distinguish what an eight candidate is versus a nine candidate.

It can tell you what a three versus a two or two versus a five, it can't do anything at the top end of it.

[Andy Goram] (18:27 - 18:29)

Is that because it's more nuanced at that point? What is it struggling with?

[Joel Quintela] (18.30 – 20:04)

That's correct. Yeah, it's, you know, you as a hiring manager, you you're thinking about a lot of things when you're interviewing, you know, your, your candidate, you're thinking about your management style, what you prefer, you're thinking about your team members, what they prefer, you're thinking about what you not necessarily, you know, what, what skills you want to replicate, like you already have. But you're also thinking about, wait a minute, I need skills that I don't have.

So, you know, you're, you're thinking about a lot of things. At the same time, an AI cannot do that for you. You just can't.

The other piece of it is that it can't, it can't, it can't measure what you need it to measure. So, you know, in the, in the selection world, there's such a thing as a person job fit, which, which just means that, that there's certain requirements of the job that you have to do is, is a, you know, an employee. And those are fairly straightforward when you're, when you're, you know, when you try to try to hire somebody, and we'll talk about that a little bit later.

But there's also a person, person culture fit, that is really important. Because, you know, if, if you have a horrible culture, you, you know, doesn't matter what you do in selection, you know, you're gonna, you're gonna lose them, right? And I always tell some clients, well, you know, I can get you really good candidates.

But it's up to you to keep them.

[Andy Goram] (20:05 - 21:08)

It's really that I mean, that that point alone is really interesting, because I had someone on the podcast from a recruitment company, who had rebranded themselves as a recruitment and retention company for that exact point, really, in trying to have commercially have a longer relationship with the with their clients. But actually, from an intention perspective, was to really try and understand fit. And that's a dangerous word, I think, when it comes to people and culture and jobs in business, but trying to think more long term.

And, and I guess this is exactly why you're saying, look, from a sifting perspective, and from a, you know, a process perspective, AI, yeah, shoot the lights out, no, no, no question. But from that nuanced space of really trying to weigh up all these different factors, which I'm guessing, the binary things are quite easy for AI to understand. But the nuanced cultural things, that's not where it's at right now.

Right?

Human Nuance: Why AI Struggles with Culture and Management Fit

[Joel Quintela] (21:09 - 23:16)

That's correct. So that, you know, the big part of the select in, you know, phase are the interviews. Yeah.

Which, which are, you know, fairly, it's, it's a, it's a pretty wide open conversation between a hire manager and a candidate, you know, but when you start allowing AI to listen in on your conversation, start transcribing that conversation, summarizing that conversation, offering you advice or judgments about that conversation. That's where it fails. The transcription summary that that's okay.

But we're now starting to get into with AI that it's now doing, I guess what people call interview intelligence is kind of the buzzword here in the US. Okay. It's that idea that the interview is broken.

It kind of is a little bit so AI can come in and do a lot of stuff for you. At some point, we were going to get to the point where, where AI was actually scanning your face for micro expressions. It was checking your tone.

It's, you know, it's making decisions, right. You know, based on, you know, Joel's, whatever his personality is, you know, introvert or whatever, right. It starts making decisions for you.

And then from a hiring perspective, you know, if you're a hiring manager, you might just let it do everything for you. And it's not going to know what you know, your management style, your team that the person's going to have to be involved with the customers, actually the environment itself, the culture, the reward system, you know, you're thinking about six, seven things that are going to impact, you know, this person in three months or six months, AI doesn't know that. It can't even learn that, you know, because that's too, you know, you know, the same situation for you is different than the similar situation for somebody else.

It just can't do that. It can't, it can't distinguish the two for now, I think.

[Andy Goram] (23:16 - 24:29)

I was going to say, I think it's for now, isn't it? Because I am, I'm nowhere near an AI expert at all. But my basic, basic understanding of LLM models is they're looking at large amounts of data and finding common patterns that they think this is probability that this pattern is going to work here.

So when we're looking at that kind of like sifting of data and all the rest of it, probably dead good at that, because there's, there's an algorithm that is making sense of, well, yeah, in this case, that's probably right. And that fits in here. And that fits in there.

And this, that's nice, that works. But when we're into, I guess, the combination of interpretation of maybe even nonverbal responses, and even that, even that sense of intuition, yeah, you know, that, that feels like a very different level of development. I know in my own base use of AI, how, if I really want to get a great result out of it, I have to feed it constantly, tiny pieces of nuanced information, and it gets it wrong.

And you've got to reeducate because it's learning. That's the whole, that's the whole point. In this scenario, we don't want it to learn.

We need it to know, which is, I guess, where it falls over.

[Joel Quintela] (24:30 - 25:30)

Yeah, exactly. Yeah, I'm just surprised and concerned that, you know, companies are just, just sort of adopting this or trying to adopt this kind of a decision making from an AI perspective in the select in stage, in that stage where, where you have to, you do have to be fairly careful with trying to figure out these five individuals who are going to move forward. And it's the most important part of that recruitment process.

If you ask 1000 recruiters, what's the most important part, they're going to say the interview, which is correct. But now we're saying AI is going to do the interview for you. And great managers like you are going to go, no, it isn't.

Yeah. I'm going to make the decision because I know, you know, what's best, you know, for me and my team.

[Andy Goram] (25:31 - 26:19)

And I think, but I even think that's the kind of interesting thing about people in business. Yeah. Because I think there will, there will be plenty of people that will go, yeah, I'm too busy.

You do it. You do it. And in the same in like, do you want to have the redundancy conversation?

Or would you like to give it to AI? You know, there's going to be a whole proportion of people that go, let's give it to the AI. But there'll be a large proportion of the those human caring leaders that go down.

This is this is important that I engage with this individual, I've got to make a connection, I've got a relationship, I want to be the one to tell them, you know, that's, that's just part of it. I mean, this, this thing, I think you've mentioned before this, this part of harmonizing the AI and leadership and culture and strategy all together, that that's, that's where this all can start to have real benefit.

[Joel Quintela] (26:21 - 27:33)

Exactly. And, you know, it does start from the top. And you do, you do have to, you have to be serious that everybody talks the talk, like, hey, my people are my best assets.

And everybody says that they're starting to believe it a little bit more. But you really have to believe it when you're talking about hiring. Because that, if you don't do that correctly, who's going to do the you know, who's going to do the work, you know, if you're not taking it seriously, the company's doing it well, actually commit to making sure they're making great hires.

This sounds, this sounds crazy. But it's very rare that, that these huge companies are, you know, you know, you're, you're, again, you're just rolling the dice, you know, for most of your positions, but it's, it's not that difficult to increase the probability, but it does start from the top. You have to decide this is what we're going to do.

We as a company are going to make better hiring decisions, because that means a lot more money for us, period. That doesn't happen all the time. It's amazing, actually.

Leadership's Role in Fixing Broken Hiring Practices

[Andy Goram] (27:34 - 27:45)

What do you, what do you think is behind that, Joel, in your experience of trying to help these companies? And you must see the good, the bad and the ugly, I'm sure. But what, what's behind that?

[Joel Quintela] (27:46 - 30:00)

Yeah, I think, I think it's a couple of, you know, sometimes I see like an arrogance, okay, you know, about, no, no, no, I know what to do. I know, you know, how to, you know, I know exactly what, you know, what we need to do as a company and oh, here's AI, I think, you know, because the heavily funded, you know, startups, you know, are probably golfing with your board of directors. And they're saying, hey, why don't you use AI?

And a lot of executive teams are going, yeah, absolutely, we got to use AI. But they don't understand, you know, when the, I guess, when the boots hit the ground, or they don't understand what's happening for real at the bottom, right? How are we, you know, in the trenches?

Because they just don't understand. They're not necessarily, you know, thinking about, you know, this is something I really have to be deliberate about and strategic about. But the companies that do realize, hey, look, my people are my best asset.

So I probably should do some things to get better people into the, into the organization, that it doesn't happen all the time. It's just, it's just amazing what, you know, what, what companies are doing. You know, it's because it's not that the leadership is saying, this is what we get to do.

And town acquisitions saying, No, we're not. No, we don't want to do that. We're just going to roll the dice.

It's not that. It's because the leadership is not driving it. You know, if your EVP says, you better make good hires, guess what, recruiting is going to do whatever they can to make better hires.

But that doesn't happen all the time. Especially with these heavily funded, you know, companies are now just coming in and throwing things at these executives way at the top. And, you know, executives don't necessarily know what's true, what isn't for this thing.

So they're coming down and going, hey, town acquisition, you need to do this, you need to implement AI, you need to let it, you know, transcribe your interviews, without actually knowing what that means. Yeah. So our, you know, recruiting is scrambling.

You know, because leadership is telling them something that, you know, you know, it's not even possible to do.

[Andy Goram] (30:01 - 30:37)

It feels from what you're saying that there's still there's still a bit of a culture. And we I guess we're fed not great, detailed information about AI. And when we take it, the synopsis of it is AI is great.

It's fast. And it can save you loads of time and money. Brilliant.

Well, plug it in, and it'll be great. And we're seeing it, it feels to me like we're seeing it as a sort of short circuit of the process rather than enhancement of the process. And we should be using this stuff to enhance the process, not try and circumnavigate it and cut to the finish.

[Joel Quintela] (30:38 - 31:43)

Yeah. And, you know, we try to break things down into very simple terms. And, you know, as a talent acquisition professional, that we are, you have to, it's the simple way of thinking about your hiring process is what I just said.

There's a screen out part of the process. And there's a select in part of the process. AI will help you with the screen out part of the process.

But it cannot with a select in, because that is a bit more nuanced. Yeah. And, you know, an interview with a hiring manager is not just talking about the requirements of the job.

And that's it. That hiring manager, like you were saying, you're looking for other things. Yeah.

You know, your management style, how's that going to, you know, how are you going to fit? Because the person manager, by the way, is probably the best predictor of whether people are going to leave. Not person culture, not personal, whatever.

It's person manager is really good. So those managers, if you're serious about it, they're looking at that fit.

[Andy Goram] (31:44 – 31:46)

That's where the relationship is, right?

[Joel Quintela] (31:47 – 31:50)

Absolutely. Exactly right. AI is not going to catch that. Yeah.

[Andy Goram] (31:50 - 32:33)

I think this is what comes back to that point you made. I love the way that you talk about the person job fits and the person culture fits. And even just when you say that out loud, you know, you can pretty much have a strong guess at which one AI would be better suited to, right?

The technical alignment of the role and the candidate's experiences. When it comes to the relationship element and the, my goodness me, the incredibly nuanced world of culture, how on earth is AI going to understand culture? I mean, do you think AI understands that whole cultural piece anyway, Joel, right now?

[Joel Quintela] (32:33 - 34:33)

No, I think there are too many moving parts that don't necessarily have a yes or no answer to it. Everything is sort of a continuum, right? And just like you're doing, you're taking this seriously and you're making sure that you're asking the right questions, using the right tools to make sure you're hiring the right individual.

But that's a lot of moving parts that AI cannot do at the moment. It's still, you know, even though we don't necessarily know what it's doing, it's sort of run away, right? It's out there and it's sort of doing a lot of things that people that developed it have no idea what it's doing, right?

But it still is following a model that it was trained on. So those are basically yes and no responses. It's not a, it's a one or zero still, right, response to it.

Yeah, there's very little shades of gray in that, right? Exactly. You're managing it.

It's not a one or zero. It could be a 1.5 or a 0.7, you know, AI is not going to capture that, even if it's looking at your micro-expressions or your tone, or it's just nuts where some of these technologies are, you know, pitching to companies and companies are just eating up. It's that kind of thing, but it can't do that.

It just cannot understand that, you know, when I fold my arms like this, it means something. But when you fold your arms like this, it means something else. Yeah, I could just be cold, Joe.

I could just be cold. Exactly, right? It doesn't know that though, you know, you understand that, you know, when you do something, it means something.

And when I do the exact same thing, it means something else. It can't, it cannot understand that.

What Forward-Thinking Companies Are Doing Differently with AI

[Andy Goram] (34:34 - 35:02)

What I'm really keen to understand before we get anywhere near finishing today's conversation, because I mean, this is your job. This is what you're doing and how you're trying to help businesses move forward. So what do you see companies who I guess are more forward thinking actually doing differently and how are you helping them?

What's really moving this forward? What is starting to mend this broken recruitment vehicle?

[Joel Quintela] (35:03 - 37:36)

Yeah, and it's part of the tough love, you know, conversation that you, you know, you have to have with companies. Number one, the best companies that we see are the ones that are recognizing and truly making a commitment to increasing your probability of success. Like they understand there's some legwork that you have to do to actually improve that process.

Now, it sounds elementary, but it isn't. They're, you know, it's, it's amazing how many, you know, huge companies don't do this. And frankly, amazing sometimes that how the leadership is fighting the recruiters on, you know, or, you know, cutting the recruiting staff, you know, by half, which, you know, those are the people that actually, you know, making decisions for you.

So it sounds elementary, but a lot of companies don't do that. And you know, what happens? Nothing's going to happen, right?

So number one, you have to be committed to that, to that, that strategy. Let's do whatever we can to make good hires. Number one.

Number two, the best companies that we work with, you know, understand where they are in this process. So they know exactly how to use the AI for them. Like we get a lot of clients that say, Hey, Joe, what's best practice?

You know, what is Walmart doing that, you know, so-and-so I'm going, best practice. This is Tableau. Here's what you need to do for best practice.

And it's much like a coach, you know, what are the best coaches don't, you know, start off the season by going, Hey, let's think about the championship. You know, how are we going to win the championship? They don't say that.

They say, well, you need to focus on the game we have tomorrow. And then when we get, we win that one, you need to focus on the next game. You don't talk about the championship, but that's what we've seen from our clients.

They're going, AI is the greatest thing in the world. Let's implement it. Let's do, let's let it interview for us and let's let it make decisions.

And, and I'm saying, you have, you know, we're near that, you know, by the way, you know, half of your, your employees don't have access to a phone or a computer because they're out in the field. How is it going to work for you? You can't, you know.

[Andy Goram] (37:36 - 37:45)

It's like giving someone the key to a Ferrari who hasn't quite learned how to drive just yet. That's, that's only going to, that's only going to end in carnage and something very expensive.

[Joel Quintela] (37:46 - 39:20)

But it's, you know, it's worse, you know, now, you know, even in sales conversations, we get a lot of, hey, you know, tell me what's, you know, what you're going to do, you know, with AI and, you know, give me some of the fun stuff. And I'm going, well, I guess I could, but you're, you're at square, you're at one and you're talking about 10 at the moment. So you wouldn't even have an idea what I'm talking about, you know, at 10, because you're at one.

Right. So, but we get people that are enamored by this, you know, let's let AI do a lot of things. And I'm going, you need to be realistic about where you are as a company.

You know, you know, your, your tech structure is not even, it doesn't, you know, lend itself well to recording interview notes. Right. It just, it's just crazy.

By the way, you know, a third of your, your population there is, you know, maybe have Spanish as the first language, you know, versus English. Right. And we know that, we know that AI is biased when it comes to, you know, different cultures, but, you know, that's not what your, these heavily funded companies are saying to the EVPs and EVPs don't know.

Right. But the reality is it's, it's bias, you know, because it is being trained on certain things. And that data that they're being trained on is just, it's just doing everything that you told it to do in the, in the data.

But if the data is biased, ...

[Andy Goram] (39:21 - 39:49)

You're feeding it crap from the start. Right. I wonder whether in your experience, where we're talking about what the great or the good companies, the forward-looking companies are doing, are they taking a kind of modular approach, a step-by-step?

They saw, we're going to start with this element and we're going to learn with the AI about what's happening, what successes we're having. We'll feed that back in and we'll make the engine and then we'll bolt the next bit on. Are they taking that sort of approach?

[Joel Quintela] (39:50 - 40:56)

Exactly. Yeah, exactly. Because you don't, you don't actually know, I always talk about the, you know, when you're looking around the corner, you don't know what's around the corner until you get to the corner.

Right. And then you can look around the corner, but you'd have no idea. I mean, you know, you're, it's, it's the same thing we're doing with technology.

It was, it was more of a, we sort of switched from, or trying to switch from, you know, companies or tech companies that are basically taking a year or two to come up with a platform that they wanted to sell to people when they didn't even ask the people what they wanted. Right. So these days we're kind of going, let's implement an MVP that we know is going to create value.

And then let's see what happens after we do start, we're creating value. And then we make a decision based on that. And then we make a decision based on that.

That is best practice. You, you have to do what you can right now. And then when you get better at it, you'll, you'll have an idea of what you need to do next.

Yeah.

[Andy Goram] (40:57 - 41:40)

We're just going to continue with the same old crap. If we do that, we just, we just let, we come back to the start of this conversation. We're just making bad decisions faster.

Right. We're just making bad decisions faster, which is not what we want. Yeah.

Joel, you may have, you may have even just started this piece in the last piece of this conversation, but we've got to the part of the show that I, I like to call sticky notes, which is a, an attempt to summarize and leave the audience with the absolute gems that are in your head, my friend. And in this case, what we're trying to get to here is if we want to improve the state of hiring and we want to use AI as a tool to do that, what three little bits of advice would you leave on three sticky notes today, Joel?

Joel Quintela’s Three Sticky Notes for Better Hiring with AI

[Joel Quintela] (41:41 - 44:51)

So the number one part is, is you have to make a commitment to, to making a, to increasing your probability of success, quality of hire. You have to make a commitment, true commitment to do that. Yeah.

And part of that is also understanding where AI can fit into that process for you. It's different for you and different for Walmart and Verizon, others, right? You have to understand what that is at the moment and yeah, you have to know what your culture is essentially, right?

You know, can we do this? Number two, this is, this is something that when you're dealing with selection, you have to do this one thing and people miss it all the time, but it's the cornerstone of everything you do in the hiring process. And that's, you need to come up with the job profile of, right?

You should probably know what's required of the job before you do anything about the job. So you got to sit down and go, okay, what are the requirements that, what are the competencies that are required? What are the skills that are required?

What's the culture that's required? How about the environment of the team, the manager, the coworkers? Because if you know that, then you know exactly what to do and what questions to ask to increase your probability.

If you let AI decide what that is for you, it's going to miss it. And by the way, the same AI is doing the same thing with your competitors. So if both of you are letting it do the same thing, yeah, it's, you know, it's not going to, you know, it's just going to do it, you know, whatever they, you know, whatever they're doing.

So first, you know, you have to be deliberate about making a good hire. And then with AI, you need to be very honest about where it should go into your process. Because, you know, you're in a certain part of the company, there's a company that your AI implementation is different than mine.

Number one. Number two, very simple. You need to create a profile for the job.

You know, it's a very simple thing. You got to know the competencies, you need to know the culture, you need to know the management fit, the customer fit, the employee fit. Number three is pretty simple as well.

And the best way to increase probability of success is actually use some assessments to tap into those profiles, right? You know, if I know what's required of it, I should probably know how to measure that in my recruiting process, right? And there are some tools that are really good at screening out.

And then there's some tools that are really good at selecting in. It's pretty simple. So first, you need to know what's required of the job.

And then you should understand and know what I should use to measure that stuff through the process. And the people, companies that do that make better hires. Because it's very deliberate.

I know this is required. I'm going to ask this personality, this IQ, use this kind of interview, use role plays. When they do that, they make better hires, and they make more money than you do.

[Andy Goram] (44:52 - 45:22)

And that, my friend, comes down to the game, right? That is the game at the heart of it. Joel, I have really enjoyed meeting you.

It's been fascinating to get to understand a little bit more about your world. And for a guy who is using AI, incredible honesty about what it's great at and what it isn't at. So I really thank you for that.

If people want to find out a bit more about you and what you do, where should they go? Where can they find you, my friend?

[Joel Quintela] (45:23 - 45:48)

Well, there are two parts. If you're LinkedIn, you can just search Joel Quintella, J-O-E-L-Q-U-I-N-T-E-L-A. Or I think maybe we can send a link for, you can schedule some time.

But that's the quickest way. LinkedIn, connect with me, or use the link to schedule some time. But I'm going to say the same thing.

Take it seriously.

[Andy Goram] (45:49 - 46:02)

Yeah. Well, listen, we're going to put links, all your social stuff and everything in the show notes so people can kind of find you and get hold of you. Thanks so much for coming on, Joel.

It's been great to meet you. Wonderful to chat and really appreciate you coming on.

[Joel Quintela] (46:03 - 46:07)

No, absolutely. It's great to talk to somebody who gets this.

[Andy Goram] (46:09 - 46:56)

I will take that. Listen, you take care, my friend. I look forward to our next conversation.

Great. Thank you. Okay, everyone, that was Joel Quintella.

And if you'd like to find out a bit more about him or any of the things we've talked about in today's show, please check out the show notes. So that concludes today's episode. I hope you've enjoyed it, found it interesting, and heard something maybe that will help you become a stickier, more successful business from the inside going forward.

If you have, please like, comment, and subscribe. It really helps. I'm Andy Gorham, and you've been listening to the Sticky from the Inside podcast.

Until next time, thanks for listening.

Andy Goram is the owner of Bizjuicer, an employee engagement and workplace culture consultancy that's on a mission to help people have more fulfilling work lives. He's also the host of the Sticky From The Inside Podcast, which talks to experts on these topics from around the world.