The AI Divide in Executive Hiring (Most Leaders Are Behind)

Speaker A: No one's got 20 years of AI experience, right? No one has. So if you used to be an engineer or a product leader, you did have 20 years of that and you could say, well, I've done that throughout my career. Well, the race has opened up again.

Speaker B: You are a domain expert. Maybe you're in games, maybe you're a consumer, maybe you're an enterprise SaaS. And now you have the opportunity to go and build any tool, any capability that you didn't have before. Hello and welcome back everybody to Mission One, the Executive Edge to Today on this episode, we are going to be talking about AI plus recruiting. So we're going to talk about insights into how senior executives are thinking about this today. We've had a lot of conversations recently and it can share kind of some of the intel we're hearing. Uh, we'll talk about tips for executives and AI, some of the trends we're seeing, uh, some advice maybe that may be helpful. And then we'll talk about how and when to use AI in the hiring process and some of the tools and trends there as well that we're talking about or that we're seeing. So m excited to share with you all today. Gerard, how are you doing?

Speaker A: I'm doing really well, thank you, Dan. Although a little bit sad because of course we had to say goodbye to a team member. Uh, Mission One, Quite recently you mentioned in this whole chat about AI, we had an AI agent called obi. I knew them well. His time was briefly cut by the corporate machines that we are, I suppose, really in our cost benefit analysis. Tell us about the life of obi. Short but sweet. What? We've replaced OBI because I think that's a good point to talk.

Speaker B: Yeah, no, look, here at Mission One, we are building with AI every day. We were on the forefront of the trend of open claw, if you know what that is. And we built an agent to experiment and test with us. His name was Obi or Oroboros. If you watch the show Loki, uh, you get a good sense of the personality, a Persona we were going for and a fantastic show, by the way. Highly recommend. And we ended up building some capabilities around scheduling, around data intelligence, ultimately shut it down because API credits were very expensive and have now been doing more within Claude directly as, uh, new capabilities come out and they've kind of copied a lot or I don't say copy. They've built a lot of the similar capabilities as well. So we're continuing to build there. Far easier to build in a metered expense, a uh, subscription cost versus API credits that add up significantly and quickly. But OBI will be back.

Speaker A: Well, I was going to say, I mean a lot of our listeners may be AI agents, Dan. So if you're listening to this, appreciate we're sounding pretty cold here, but as Dan says, OBI will be back in a new and improved improve form.

Speaker B: Absolutely. When costs come down, OBI will absolutely back. He was instrumental in success of our work. He just costs you much money. But when costs come down, OBI will come back in a big way and our listeners will be able to interact with OB and in some form or another as well.

Speaker A: And for all the, I suppose the, the slow to technology. You know the phrase first adopter. Sadly, I think of myself sometimes as a last adopter. If you're listening to this in your car at home and you're thinking, I'm not always the first person on these technology trends, I have to say, getting into Claude, um, and the desktop Claude code is revelatory. So anyone who hasn't done it do do it. I'm sure you've heard lots of people tell you to get into it. If you haven't done it, go and do it and just say create me a. Just think of something you're passionate about, create a hobby and then go, could you create me a website for selling, I don't know, you see in fishing, selling fishing tackle or whatever, it'll do it for you. It just comes up with this and okay, you got to tweak it if you want to get alive and all the rest. But even just as a thought exercise of hey, like just something that was impossible for you to do three, four years ago, just as a person with low tech capabilities is now a few prompts away, which is uh, highlighting the just phenomenal change that all this is driving.

Speaker B: And we'll talk about this more but if you're not trying to code already, you're behind. Sorry Gerard, you're behind. But you can catch up. The good news is the tech is always changing. It's innovating every day, sometimes new. You can catch up very quickly. I personally find that I went from not even knowing what the terminal was to now using it at least five hours a day, sometimes much more weekends, coding, constantly trying to build new capabilities with myself as the customer.

Speaker A: Essentially we should say as well, we're not sponsored by Claude or anything like that. We're not kidding. We need, what do they call their little links, don't they to affiliate links. That's what we need to get on Your speech, that's pretty inspirational, Dan, I thought you were then going to say. And I learned it on Dan Hampton's code Trading for noobs course. Ah. Which is for a low price of $100 just for one week. So sign up with this code.

Speaker B: Great.

Speaker A: Uh, well that could be. Maybe that could be the next podcast. Um, I still haven't done my dating podcast, dating tips podcast yet. Uh, so maybe we could have. For listeners, that's a callback to a previous episode. So we could also do Dan's guide to coding as another ancillary. Very good, Dan. Let's get into the meat of AI then. We're talking about games and AI today as well like gaming studios and impact in games technology and building games. As our listeners will know. That's deep specialism of ours. Dan, want to start this off by thinking about, uh, we're talking to a lot of CEOs and other EVPs and SVPs in senior strategic positions. What insights are you hearing across the board from them? What could we share with our listeners about the mood and common questions occurring to top level execs?

Speaker B: I just want to point out something I saw on Twitter or X, I guess last night was Marc Andreessen was retweeting someone's comment about non AI work being considered traditional work. Now, trad work is the term. Um, and I can see it, I can agree with it, right? I think there's different categories here. There's the AI native exec, there's the exec that starting to get into it, and then there's the wait and see exact. So there's these categories of leaders out there who have, maybe they don't have time to get into it or they're just starting to get into it, but at some point you're going to see this divide between kind of the old model and the AI enabled model. Um, and I think that's important to be thinking about. Uh, and we'll talk about later, I think how to potentially build or these execs that are building new capabilities and they're building kind of new products for themselves as well. What's your thought, Gerard? Like is this trend that isn't going away, is this the fad in some ways like traditional work? What's your take on that term today?

Speaker A: Well, I think on AI more broadly, I, uh, think. I mean I compare it to the invention of the Steam engine and I appreciate it might sound really sort of banal sort of saying that and obvious. However, in the last five, six years we've had Web3 and the innovation that that was going to promise and the Metaverse both as touted as these transformational huge opportunities, vast amounts of money going in, et cetera. I was skeptical on of both of those ventures. Um, a lot of people obviously claim that hindsight, but I didn't feel even as going on, it was kind of one of those like, I can't quite believe all of this and I'm curious about it, but it didn't feel real to say AI is big. Again, everyone's saying it, but again we should remember that sometimes everyone gets it wrong or there's a snowball or whatever effect where just because Meta vested 50 billion in it, as they did in the Metaverse, didn't mean it was that real. Right. You can sort of assume that they know what they're doing or whatever it is. There is some skepticism about the sort of the impact of AI and it might take a while to flow through in its full. And AI as a term is sort of unhelpful in itself because what does that mean? Right. Like there's all sorts of sub genres of applications, all the rest. But I think when we're talking about CEOs and the insights we're hearing, certainly it's clearly on their mind. We hear that both in the conversations and quite clearly in the headlines that everyone's reading about layoffs. Again, sometimes these things are used as slight covers. You know, you're going to lay off people anyway and you can blame it on AI and you look good to shareholders. But we would say that's backed up by real concerns what we're hearing, albeit I think that sort of the key difference is it doesn't necessarily impact every function in the same way or depending on your product, impacts you differently. So we turn to our specialties with games, for example, when we talk to aaa. So AAA is these kind of very sort of involved, high budget, high quality, long lifespan type games. They've invested heavily in it. They're not yet seeing the real sort of the triple A value add across the board, certainly around like narrative, for example. That's an area if you want to create really deep, compelling, original narratives. AI can't really do that. Right. Or if you want to create really innovative or like highly advanced combat systems or something like that, which is going to change the needle. It can't do that very well. So you're still relying on high level, specialized, uh, technical people within those fields. If we look at the other end of the market to say mobile casual games or hyper casual Actually Dan, I think you spoke to a CEO recently, Didier, of a small hypercalt. Tell us about their insights and their experience there.

Speaker B: Yeah, so I spoke with an early stage CEO, I think it was last week or maybe earlier this week and she was saying that they're using AI, uh, tools now as a way to rapidly prototype, test and iterate. It's not replacing their art, it's not replacing the human component of the design aspect of it. But it is giving from my view them and other companies like this more of a need or more value placed on design thinking. Right. Because the uh, production aspect of it, uh, the testing aspect of product making is becoming easier and automated. The design value is the limiting uh, factor, the differentiator. So that they were seeing that. Similarly they were seeing that having leadership that understands design and creative thinking is becoming more valuable than before. Not that it wasn't valuable before because it was absolutely valuable, but becoming more of interest to them. So yeah, seeing that. Absolutely. Does that resonate with you on uh, some of your conversations?

Speaker A: I think it mirrors what we're saying about the aaa. It's just a different application.

Speaker B: Right.

Speaker A: It's still that creativity, the vision, the ability to do something different, find the fun is also an element I think that AI struggles with. Right. Again, it's very good at repeating and spaghettizing something there and even on uh, some areas where you'd think it's very good at. And I appreciate this will be a controversial topic. We appreciate in games AI usage is controversial. We call that, I think I'm happy to say the horse has bolted a little bit. If I'm honest in my views that there's a little bit of resistance of oh, players don't want AI in their games. And we've seen was it craft on or somebody else had to apologize recently that her assets uh, were being used in games. My instincts, it's fighting a rear guard action and that uh, progressively we will just get more and more normalized to a point that it won't matter. So I don't think in 15, 20 years time there's any CEO, uh that's going to be apologizing for the use of AI assets.

Speaker B: Right.

Speaker A: Like there might be people who do things specifically for some audience they say like indie films, right. They might say like we're going to use candle lighting for whatever this film, right? Because we're not going to use big lights or whatever, you know, everything on set. There'll still be places for, for people who want a different feel and all the rest but my honest view is we are seeing, quite understandably, a lot of anger. I hear that anger and I understand anger from artists or writers who feel like that their whole job and worth is being threatened by AI because as you say, Dan, it can't be replicated at a finesse level. And I urge execs to see that finesse level. But at a base level, at a simple, uh, ideation or concept art or something like that, it's going to have a place, even if it's just the starting point, to help iterate or ideate or if something's not working, you need to move on and you can do that very quickly or you can test multiple things with AI. So to your point, Dan, I think that value on the creativity is huge and the X level of creativity that add on, but it has to go on top of being able to drive rapid iteration, rapid pace, whatever it is. With AI, if you're doing both, I think that's a great place to be in. If you're doing one, that's okay, but if you're doing neither, then I think that's going to be potentially a more threatening place for you to look at from AI.

Speaker B: Yeah, I think it's fantastic from an ideation standpoint. But for, you know, this is what the CEO is saying as well. But for world class animation or world class art, or world class design thinking or user experience, player experience, it can't do that. Right. So but it can help you figure out where your product should exist, where your product market fit maybe could be and go and attack that. Right. And put your company resources, your human employees after that. Right. Like, okay, let's go and attack that.

Speaker A: And of course internal tooling as well, Dan. Right. Like again, the ability to build an agent to sort of answer questions about the build or the tech or, or whatever you're doing or the law. I mean, I've heard of that of people using an AI bot to, you know, when they had a complex franchise to train the bot on the law. So anyone who's putting a design concept in, they're like, well, what's that character's relationship? Or like have we ever had a character come from this part of the country before or this part of the world in our game? And rather than having to somebody have to look that up or talk to Joe, who's like an uh, obsessive nerd about, you know, like about the law, you can get it, you get it to much quicker responses. So there's a lot of like really innovative stuff that can go on. That's either very obvious or I think creatively used to just speed up production or to enhance or close loops. And this is such a broad topic. I uh, think we should, as a caveat, we're not going to cover everything right in one podcast. But again you have some of the coding and bug catching and things like that as well. I think that's going to get better. I uh, think it's still not quite there on catching all the bugs. It's clearly an area where I think it will continue to be impactful.

Speaker B: My advice here would be if you're in trad work, if you're not in A.I. thinking, uh, about how to build it, do that. But my advice would be, even if you are, is you are a domain expert, you know, whatever domain, maybe you're in games, maybe you're in consumer, maybe you're an enterprise SaaS, you are a domain expert of your space. And now you have the opportunity to go and build any tool, any capability that you didn't have before. If you're listening to this, you know, mission one, we're building a recruiting intelligence platform. And this platform is going to be able to get data from different sources and give us new insights we didn't have before. It'll give us new capabilities to use the data that we already have in new ways and different insights, think about recruiting differently even in the executive level. And so we're building these capabilities today that help us differentiate ourselves, move forward right before, hopefully before other people have it. But this, I expect other firms will continue at some point. These capabilities will be, will just be out there. But if we can innovate on it first, that's great. But the data now, the capability like you as an executive out there can go and build. Think about your role again from first principles and think about what will help you do your job better. I don't think AI is going to replace massive human jobs, but every job is going to evolve in my opinion. And so how can you think about your role in a different way? How can you become AI enabled again? We could talk about this forever, but there is this kind of divide. But I do expect everyone will be coming online. This is like the Internet coming online in some ways. Steam engine. Right. And so how is that going to. There'll be waves across as we think

Speaker A: Target of executives looking at this space again, I'm sure a lot of them are experimenting. I think, uh, we've said this on before, playing around with ChatGPT doesn't cut it. Your odds like how using AI is. Well, you know, I, I regularly go on ChatGPT and just like mess around with it. That is unfortunately, a year ago that was reasonable answer. Uh, we'd say to you today that's not a good enough answer. Right. Like you've got to have some tangible ways you are, uh, building stuff with it. You've got your team to build with it. And we see out of top execs right there. Yeah. Again, turn to games. We talked exactly like, I built a game over Christmas using AI. These are either people who haven't coded for 15, 20 years or have never coded, but they're like, yeah, I did this. And then they go to the team and say like, hey, I was able to do this. That's cool. Like, are you doing this? And like, you can overcome. I think that's always a key thing of any senior. I think in any C level exec is always the ability to sort of be able to challenge the team. And I think, you know, again, if you're thinking about how to do interviews or preparing for, to segue into that kind of advice, being able to show that is really valuable to say, like, hey, the team gave me this answer and I went back to them and said, that's not right. Here's some reasons, like we go nuance or be able to offer the challenge to get to. Because there's always objections, right. Of why we can't do things. But I think it's classically that knowledge. And again, because no one's got 20 or very few people have got 20 years of AI experience. No one has. So again, if you used to be, uh, an engineer or a product leader, you did have 20 years of that. And you can say, well, I've done that throughout my career. The race has opened up again. So you haven't got 20 years of AI, so you've got to build that knowledge to be able to challenge the users, because we're all slightly infants in this space and your team might be as well. And I think that sort of comes on to probably segues nice way into our next topic, which is Dan thinking about tips for execs in an AI world. So this is going to be a world potentially with smaller teams for some functions particularly, or leveraging AI more certainly. It's a world where if you've got smaller teams, you might have more execs on the market looking for jobs. Right. Because there's been downsizing, it feels like there's a shift in tech generally and games as well across this Dan, um, what are your tips for an exec thinking about their career pathway again, people coming up through the ranks so thinking, hey, I want to be a C level exec one day. I'm a director now, like how am I going to get there and how is AI helping me?

Speaker B: So the current trend we're seeing and have been seeing for the last year, maybe two years is that executives are becoming more tactical. Right. There's more of this player coach mentality. I think large team leadership roles have been going away, although they're not ever going to go away. But what's happening in startups today, what's happening in at least mid size orgs is that large team leadership roles are becoming smaller, executives are coming more tactical, there's fewer layers in between. So uh, things are moving faster.

Speaker A: Just to clarify on that, when you say tactical, do you mean that in the sense of tactical versus strategic in your opinion or do you mean that just in terms of tactical as in is less about management of people and more about sort of driving towards a uh, particular result. How do you think about that word tactical?

Speaker B: They're closer to the product, they're closer to the data, they're thinking about spending less time doing people management performance reviews, kind of leading through layers and more time maybe leading fewer layers and being closer to what's happening day to day. I think seeing it like it's the ability to see what's happening in a product is becoming maybe easier to do and then figuring out how to be more advanced on top of that. I think like my personal opinion is this is a trend that's going to reverse. So today we're AI, uh enabled, teams are a thing and will continue to be. But people see it as hey, we can do more with less. My view is that it'll come back the other way and you'll do more with more at some point and that'll be AI enabled teams probably base layer of agents, led by human managers, led by the executives at the top. So doing more with more from that respect. So I do think, I think the skill set of leading through layers is on a downtrend, but it's going to come back up, right? And that's a valuable skill set to have where these big team leaders know how to navigate an entire org, know how to turn a ship, so to speak, right. While they're becoming more tactful today because they're learning about AI and how to incorporate that though, these teams are going to come back leading through layers, leading massive orgs. That's My prediction. What do you think? What do you say to that, Gerard?

Speaker A: Interesting. I think you're right in terms of again, I think history teaches about sort of creative destruction of technology. And you always see that technology destroys jobs, it creates new jobs. And we are in that transition certainly of the destruction. I'm confident history teaches us there will be the creation piece as well. And there's countless examples of tech that you say let's control the jobs and then you find out people end up employing even more people than they were before but be able to add more value, right. And leverage more of ah, a better model or whatever it is through it. So it will be interesting. One counterpoint to your idea is I think some industries may just downsize what a uh, big enough team is, right? So some industries might be okay, we've got to be like a 5000 person org to be a big company in this space. That might move down to like a 3,000 person org or two and a half. I don't know. One thing that I think is interesting and unproven is the entrepreneurial spirit that will be unlocked by AI whether uh, intentionally or otherwise. People will be forced to, people just won't have a job. So they will force to be entrepreneurial.

Speaker B: Right?

Speaker A: Like you create that sort of negatively through a negative experience, being laid off or something like that. And actually you look at a lot of innovations in history, the Great Depression, all the rest. Sometimes these people come through, right, because they have bad experience, they get laid off or whatever and they're forced to then become entrepreneur. They grew up in very poor surroundings where certain avenues of careers aren't open to them. So they're forced to become entrepreneurs. And I think so tying that in some advice I'd certainly say I would encourage everyone, including senior execs, but especially csx, to think about being more entrepreneurial and being entrepreneurs within whatever era they have. Because the AI tooling has unlocked so much. Whatever it is that was uh, unlocked to you before, it's given you a foot in the door to say, well, why can't we do this, why can't we do that? That should be fixed. And my experience working in a bigger organization was a lot of demarcation around different areas. So that was the marketing team's job, it was the tech team's job. You felt a bit parallel. You're like, well you write to the tech team, say why does this work? And they've got a hundred people moaning at them about stuff, right? With now you can sort of say like, hey, tech Team I built something. What do you think? Ah, hey, they might still push back or whatever I'll tell you. But my point is if you show that level of entrepreneurialism, ability to solve the problems and do that directly, that's definitely I think valuable skill. Another tip I'd say to execs in this age is make sure your team is being upskilled as well around AI and really be pushing them. And that actually involves a lot of softer skills here again going back to that point, what are knowledge? A lot of people feel threatened by AI. A lot of people don't like AI. I'll be honest, I was in a meeting for my completely unrelated to work. I was talking to my kids school about getting messages out there and uh, one of the parents said hey, I don't like the use of AI. I was like hey, we can maybe get AI to automate updates about what's going on in the school. And they're like I don't like that. I was like oh, people just have object and I think it's very legitimate and I want to talk about that and find out about that. But it's you know again a lot of people are suspicious or they have question marks at different levels. Be aware of that, be conscious why people aren't um, necessarily going to be on board with this excitement why they might be and legitimately so right there might be drawbacks. So I think upskilling the team but I think where you can really show that softer leadership skill will also be really valuable because you don't want to lose certain people who or put people off is the right way to bring them to the altar and get into the drink as it were. And I think that's a big part of will be a big part of leadership is not just the uh, hey, you've all got to use this which is like in any tech. Dan, I'm sure you've been there. I mean Salesforce was my tech. I just call it a tech. I used to hate using Salesforce. You can tell we're not sponsored by Salesforce and probably never will be now. But Claude, you can still call us anthropic. It was just this drag of like always there's always this pressure from the top. Like you need to use Salesforce without ever really clear leadership or explanation or like incentivization of like why. And I was busy doing my job and had very little time to go do it and no real consequence of me not doing it as well. So it was just a kind of a Bit of a, it was a meaningless sort of corporate mandate that the people who do these things just because they mandated would do them and m, like most people ignore them. So I think that's a real lesson in just thinking about how you're going to bring people with you and acknowledge that all without just taking a top down attitude. Anything else said Dan, that I haven't covered or anything else you'd add to that?

Speaker B: I ah, do also want to say that the AI coding ability, it's not as good as your world class engineers. Right? It's still not to that level. You still, you'd absolutely need these people to make your products run fast and with great performance and you need them for all sorts of things.

Speaker A: And uh, as we said for anything to do with regulation as well, there's just like a level of accuracy that you can't sometimes rely on like 80% or 90% good enough. Right. For certain things at all.

Speaker B: Exactly. Like there's still corners AI can't see around. It's not going to design it in the um, world class way. You still need to spend a lot of time with it. And this is why I think the large team leadership will come back. Because you're talking like, look, your time, everyone's time is finite. You get only so much every day, one to one AI usage is not the most effective use of your time. And so it's going to be leading teams of AI, teams of humans, leading teams of AI to get to the right results and to move as fast as possible. Right. If you're just one to one with it, not nearly as effective as uh, having a team uh, building together. So thinking about that as well, Jordan, we should chat about kind of AI meets recruiting, the trends we're seeing with it in the hiring process. Maybe give the audience kind of a snapshot of what we've seen to this point. There's some context around this and we can talk about maybe the trends we're expecting.

Speaker A: I mean the first thing is I think it's evolving fast is good to note. Right. There's tools that were uh, revolutionary a year and a half ago or you paying money for, whether it's sorting through your emails, correcting like helping you write emails, better uh, recording, meeting technology, things like this which very quickly become standard and actually I think commoditized. Right. Again, ah, we've seen things go from premium to commodity there. So that's number one. And again I don't necessarily know what's the next thing that sort of is coming. Anything you think is coming is potentially going to be some more table stakes tomorrow and less sort of innovative and exciting. But I think we've seen there's sort of layers to this again there's layers of how AI is used. I've just mentioned a number of them. Right. I think and it's different at the more mass level of recruitment so people more that sort of talent who are doing anything from ice, individual contributors up to managers, something like that. I think we're seeing AI being very heavily leveraged and we've talked to because we talk to senior ah, Italian partners who sometimes overseeing the exec and the sort of more talent piece as well and they are using AI a lot in just sort of checking the work, making sure the outreaches that are going out to candidates are good. Now I, I would personally say the approach is good for mass volume and you'll get some results from that. If your process is to grind and it doesn't really matter, you've got 10,000 people to go at, you only need one, you're going to get some good candidates through just going uh, from a brute force kind of way I would use the AI. I have heard from people saying hey the AI says this is good but we're getting really low out response rates. That doesn't surprise me either because I think the quality is poor still. I think if you're using AI and heavily relying on it to do this outreach then it's still not there and I would again hybridize it again sort of stick it up for the human in this rather than get rid of your talent managers because the bot can send 10,000 messages or whatever, train them to become the auditors of quality and being able to catch that level of user bots to identify the really good candidates in which the case you're going to handwrite the top candidates you might like, we're going to handwrite a message. Not handwrite but compose personally by a human to make it much more effective at ah, the exact level. I think we're seeing less of this again because I think that's better understood again you just can't take a brute force approach because there are 10,000 candidates, there's maybe 50 or 20 and the leverage point doesn't really get you there and you're just using low quality work for no real benefit. So I think that's some of the tech we're seeing at the moment. So again I think you should be using if you want to use uh, recording software AI yeah like email composing, campaigning for lower end Recruitment, that's fine I think for the higher end again perhaps more hybridize what's in the background. But you're really putting the human effort in at the money. What else do you think? What about some trends you're seeing? Because I know you're talking about sentiment analysis to me the other day and areas there where the AI is getting a little bit smarter.

Speaker B: So uh, first I just want to say look, if you're an executive out there, nothing is going to replace, at least it hasn't yet conversational interviews and referencing and overall track record in your career history like that. AI is not replacing that. The interview process for executives has not been disrupted by AI. Now look, there are tools that are being used now in terms of recording interviews or note takers, that kind of thing, which I think everyone is fine with. I don't think there has been any issues out there recording those things and they can be helpful and useful in the interview process. So you're eliminate some redundancy around. Okay, well how do they answer this question or how do they answer this question? So your subsequent interviews aren't asking the same things, which is great. Junior levels, there's been more around kind of AI assessments and is this allowed or not allowed? We're not really focused on that level. So tbd, I think in terms of what shakes out there overall, but I think there will be more data coming. My prediction, there'll be more data coming around products and impact at the executive level. There'll be more tooling around specific years and growth of a product at ah, specific timeframes and then matching candidates to that. And so seeing the impact is helpful but again back channel referencing or referencing will only validate your impact really. Like hey, was this person a passenger on the rocket ship or were they the fuel really? You know in some ways. So good news for executives is your interview process really hasn't changed. I think it's going to help you a lot more from a networking standpoint from a ah, data and impact perspective. If you were the fuel of the rocket ship, but from a Virginia roles I think it's we're seeing a lot of kind of innovation maybe in the space. Maybe it's counterproductive around kind of AIs and ATS matching things. I've seen a lot of just like comments out there on Twitter on LinkedIn about um, candidates applying for hundreds of jobs and not getting an interview. And so that clearly is broken. But for senior levels it's still the same in many ways, maybe more powerful from a networking Standpoint, what do you

Speaker A: think its impact is on case studies? Han? Because when we did our series on talking about the process. Yeah, good hiring process. We talked about the importance of using m a case study. Now, particularly with written case studies or even presentations, right. It used to be a case of okay, got this presentation that's going to take somebody a weekend.

Speaker B: Right.

Speaker A: It's quite an involved area nowadays. A lot of smart people were saying, how can I, it's okay if I use the AI to help me with this and generate it, but then it can feel a little bit, just not very revealing from the other side. Right. Of uh, what the person says. Because you're thinking, was this the AI churned out or is this actually what they really think? So what do you think about case studies? Should AI be encouraged? Should it be banned? What's your list of intex?

Speaker B: Look, it's a great question. I think there are pros and cons and someone could argue one way or the other and be persuasive about it. My present thinking on it is that look, if you're asking someone to do a case study, they're going to spend, supposed to only spend two or three hours on it. We've seen people spend a lot more time on those things than they shouldn't because that, that part of the interview shouldn't be a full time job for somebody. So I would say if you're expecting them to use AI in their job, you should allow them to use a, in their how they're presenting or a case study they're working on and you judge it accordingly. Right. Like if they use the AI and still and it's not great, then that should tell you something as well. If they're not using AI, maybe that tells you something as well. If you're a, if you're an AI culture, right, like within your org, or you're trying to bring in somebody who is going to build a culture of AI, uh, usage in their organization. Right? So you're getting data, I think you're getting data points either way.

Speaker A: And it shouldn't be a test, I don't think in itself. I think you should be clear with candidates. I'd put that in nowadays as advice saying like, hey, we're happy for you to use ar, we expect it or please don't if you don't want it. Because I think it shouldn't be a catch out because it's one of those sort of gray areas, a bit like dress code. I'm going to make that analogy. I used to get asked that like, what should I wear a tie for that interview? Nobody wears ties nowadays or some people do. And if you're wearing a tie right now, make a comment on, uh, the YouTube channel, whatever. It used to be a question. I get lots. I think the modern question is like, is it okay if I use AI Now? The warning sign sound should be. Also make sure it doesn't look like 100% AI. If you've done something right, like you've got to. It's a balance where I think again, showing the hybridization, showing the ability to leverage it but not be dependent on it or have no character. Because we've seen that people writing a really, uh, detailed response to set of questions. But it just looked like, okay, you didn't put much effort into the tool and let the AI do all the work. Right. So it's a balance of you want to use it smartly but also really go out of your way to make sure your own ideas or your own personality shine through. And I think, you know, draw a largely we can all see of this is a LinkedIn post, right? Like we say, or posts on Twitter or whatever. Right. Like we can all spot the. It's so easy to spot now that just the auto generated stuff, I think it is anyway, maybe some of the auto generated stuff is getting slipping past me, but it shines through versus somebody who's like maybe again I think if you've maybe started there and then um, brought in your own color, your own voice, that's the stuff that often lands and you see people more commenting and engaging with. So I think it's same ideas behind a case study of you've got to impact it with your personality. And uh, the extreme end of this of just being so in love with the possibility of AI you might do yourself some damage by doing something you think is smart M or clever. Or even if you think the AI has written something better than you do, still show your own personality because it will still be more interesting than just use the bot.

Speaker B: Well, you bring up a good point, Gerard, around not using AI 100% for part of your interview process. I think that's happening out there. I think we've seen stories out there of kind of candidates going through an interview at the IC level and using AI to help them with their responses. I think if you're interviewing a senior executive and you're using A.I. uh, on their case study, the emphasis really is on the interviewers at that point to dig into the case study, make sure there's substance behind Their answers there, make sure they know actually and they're not just copying a ChatGPT response and with no clue about what's behind it as well. Right, so the interview becomes more important then. Right. Like understanding substance becomes more important under making sure you're bringing somebody in that really understands the role they're in and thinks about it through multiple levels. I think that's imperative. Right.

Speaker A: So, and I think it'll be interesting, think about future trends that we might see. I think one area of interest is sort of in the assessment area itself, right. Like using AI to review, uh, an interview and gain insights. I don't confidently know how good the technology is, right. Because again, it's very hard to prove. Right. It's like saying like, I'm really good at understanding like the quality of the candidate. Like, well, how do you prove that you need somebody else who needs a slightly subjective comments or they're hard to prove unless you want somebody over five years whether you're right or not. But I think there are a lot of technologies now. They're looking at taking what psychologists have done or these, what do they call? Not psychometric tests, but things like that. People used to put people through psychometric testing and have them interview with psychologists and they put them on a graph and a map and all the rest, which I think, uh, that is a proven science and that is interesting. And uh, can yield insights to a candidate like how autonomous they're going to be, how difficult they're going to be with direction, all these things. And you can put that into your mesh and your executive board and thinking, okay, well what's the mix of personalities here going to be? I think that might be the next area for AI which is a bit more sophisticated to start being able to say, okay, well, hey, it's really interesting. They use these words a lot which might indicate a more aggressive style of working or these words which might appear that they don't like confrontation, but they're good at this. So I think we might, um, and we will start to see a rise in that, albeit again it'll be then interesting to see, I think the differentiator there would be the knowledge when to push back on the machine. Just like we're saying the AI might say, your outreach to uh, a candidate might look good. You've got to have confidence to sometimes say no. And I get it sometimes from my Google, I use Google Mail and it's always trying to suggest sentences to me. And sometimes I go, yeah, that actually is an improvement. Sometimes it's really insistent.

Speaker B: Right.

Speaker A: It really wants to change something. I'm like, no, that's not a better way of phrasing this. Right? Like you don't have all the context or I don't think you're right. And I was a slightly bit off piece. I think there is a societal question which is quite interesting about if a lot of the junior jobs are being replaced by AI and there's fewer entry level jobs out there of substance. If people grow up almost like their job is to almost manage the bots, they might lose that ability to push back or know when the machine is wrong. Weird. A lot of dystopian novels are like when the machine tells us we can't do things, they're like sorry, Halloween, you can't do that.

Speaker B: Right.

Speaker A: Another dystopia might be we lose the ability to say to the machine, no, you're wrong if you lose a big tell the opposite. I do encourage again, uh, uh, it's probably less relevant to our audience who's a bit more senior. But I think again if a lot of them might be parents thinking about their kids coming through or got junior staff members, I think that's got to be a part of the conversation because otherwise we will be beholden to imperfect machines and you'll lose out against people who are.

Speaker B: AI is not going to be replace human experience and be able to make a judgment based off of 20 years of experience on a hire, which is we don't need it to replace or want it to replace. I think I really liked your point around um, AI being able to maybe look at some words you're using or look at your personality set and figuring out how that may mesh with the executive uh, team you have today. Right. And kind of takes, that takes those kind of personality um, assessments up a level. Right. In terms of being able to still that out. I think with the prevalence of AI video capture and note taking software, probably going to see some new signals coming out of this around one benchmarking uh, responses or pattern matching or giving some new signals around analysis as well. Being able to take all the interviewers notes and put them together and figure uh, out maybe where the remaining gaps are uh, as well. Or just being able to kind of just give you some new data around potential hires. Right. Not to say these are things you have to hone in on specifically but additional data points can hurt around being able to see that especially at the kind of IC level where there's probably mass amounts of these. At the more senior level maybe there's only Five people in the world who could do the role you need today. Right. So you can't necessarily afford that. But at the IC to manager level there's probably going to be a lot more data and maybe org building where personality maybe just riffing off your idea where they fit in a more cohesive way. Right. Or they more complementary way as well. I think that's interesting if that's not a feature today out there on some of these note taking softwares or uh, pulling data and probably will be tomorrow, you know, kind of thing.

Speaker A: And interesting as well. Another application could be to use it to analyze your own interviewing style and get feedback because I think it's so uh, rare. And the whole point of this podcast is partly to help people become better hirers. Right. Like so there are so many resources out there, I don't think they're dedicated to this. But again I'd be curious again if people listen to this I'd be curious if people want to put they've recorded their transcripts, put that through an agent and see hey, tell me, what's your feedback on the questions I'm asking and the follow up questions? What are common traits you'll notice what improvements could suggest. Again, you don't have to take them for gospel, but it's interesting particularly if you're interviewing solo a lot. It might be really revelatory to you. Again we all think about oh it's going to help me, we find better candidates or and suddenly becomes might also be an application helping yourself that might either not be there because you're doing a lot of interview solo or you're not getting honest feedback because again people are bad at giving honest feedback. Or a lot of people are right, they like to be too direct. And your juniors might not like to come back and say you know what, you're really bad at interviewing and you've been doing this for five years. But that's not always felt like a career enhancing opportunity to tell your boss that they're wrong on something. Which is as an aside. Another aside uh, is how desperately I think actually CEOs sometimes wish they had more honest feedback. And uh, maybe we could do a whole podcast about I don't know. But it's interesting. The machine doesn't seem to care, right. OB was unaware that it was going to get fired. The bots are unaware. So they can give you feedback. They can be very sick of antic at times, but they can also give you feedback in a way that people won't there. So it's an Interesting thought.

Speaker B: OB is on a sabbatical. He will be back, I promise you. Not fired.

Speaker A: It's like, uh, the dog's gone to the farm. Like, I hope he's on holiday right now. Don't worry about where he's gone, kids. He'll be back.

Speaker B: His daily costs come down. But, uh, it will happen at some point. But I like that as well about kind of feeding your transcript back into AI for some kind of interview prep analysis or interviewer analysis. Increasing what the metric would be kind of increasing your candidate conversion. Especially if you're hiring a lot of people and you're losing out on great candidates. You can figure out why that's happening. Maybe it could be a variety of reasons, but you could eliminate kind of maybe figure that out within the transcripts.

Speaker A: We should challenge ourselves and put our podcast through the bots. We could do a little like, uh, special episode of like the AI Judges Mission one, the Executive Edge. We could be vulnerable and share maybe. That'd be fun.

Speaker B: I don't know if I'm quite ready for that. But, uh, it would be good to self reflect, dad.

Speaker A: You give me lots of feedback. Don't you worry. Uh, it can't be more brutal than working with you, dad. Uh, which is very good. Helps me grow. Anything else down there? I think we've got quite a lot there really. Between again, all these sub areas could have been a podcast and they're right. Or maybe even a whole podcast series. If you want to do all the different ways that AI is affecting the market, but it's so hot on the minds, please do let us know what you're thinking. Can we get. We have a lot of silent, uh, admirers, I'd say, or like people who don't necessarily comment, but they'll DM us every now and again or we'll reach out. Somebody say, I love your podcast. We're like, we didn't know. You can make a comment. You can subscribe. Let the people know that you're enjoying it. We were rather humbled recently. If we can have a humble brag, I think it's called. This is a brag. It's not a humble brag. So we've got an episode on, um, hiring VP products or product leaders in games sector. Our recent episode on that got 45,000 views. So thanks to anyone who was watching. But do feel free to be a more vocal, uh, listener. Let us know what you're thinking, uh, publicly as well. You gotta do it just privately. As always, please remember to subscribe and like and uh, share with all your friends and with your bots as well. I'm sure will enjoy listening to this as well.

Speaker B: I think we should do, uh, another one of these episodes in about six months, Gerard, and kind of see maybe three months and just see what has changed, like what is different what we're hearing. I think that would be important. If you want to hear about that, feel free to comment or privately message us uh, on the side and say, hey, we'd love to hear more about these trends. It's a fun episode to cover. Hope you all enjoyed and thanks for listening.

Speaker A: Take care everyone. That's another episode of Mission 1, the Executive Edge. If you found this valuable hit, subscribe and leave us a review. It helps other professionals discover the show,

Speaker B: have a question about executive hiring, or want to share your own experience? Reach out on LinkedIn or visit Michigan MissionOne IO podcast. We read everything and your stories often inspire future episodes.

Speaker A: The Executive Edge is brought to you by Mission One, where we specialize in placing senior leaders at tech, entertainment and AI companies. Learn more at, uh, Mission1io.

Speaker B: Thanks for listening and we hope to see you again soon on the Executive Edge.