If you’ve not listened to Round Up before, it’s a short review of the episodes that I’ve published in the last month to make sure you don’t miss out on the valuable insights that my guests are sharing.
This month Round Up returns to its live format, and this is a recording of my live conversation with my guest co-host Rhona Pierce from Workfluencer Media, about six of the episodes published during July and August 2026
Episodes featured in this Round Up:
Ep 803: AI Native Recruiting
Ep 807: Trust, Transparency And The AI Interview
Ep 809: The Data Foundation For AI In Hiring
Ep 812: Who Trains The Human In The Loop?
Ep 816: Hiring For Judgment In The AI Era
Ep 821: Why Every Employer Brand Sounds The Same
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Transcript
Matt Alder: Hi everyone, and welcome to this month’s edition of Roundup. Once more, we are back live, which is always the way that I love to do these. We didn’t have a Roundup last month, so this Roundup we’re going to be looking at episodes on the podcast from July and August, and there are lots of interesting episodes to cover. If you’ve not watched Roundup before, it’s basically a summary of the most interesting episodes that have been on the Recruiting Future podcast in the last couple of months, in this case looking at the kind of insights that we can learn from the guests and really giving you a little bit of a cheat sheet to understand which episodes you might want to dig into and listen to in full. I’m not only delighted to be back live, I’m delighted to have Rhona back as my co-host. Rhona, how are you?
Rhona Pierce: I am doing great. I’m so happy to be back doing this. We haven’t co-hosted in a while, so I was excited when you asked.
Matt Alder: Yeah, absolutely. Well, it’s always brilliant to share the mic with you. We’ve got two different mics, and you’ve inspired me to get some colour on my microphone. For those of you listening in audio, I now have a green microphone cover to match the Recruiting Future branding, as well as a new light box at the back there. So it’s all good. For people who might not have come across you and your work, and I can’t believe there are any, but if there are, could you just give a quick intro to what you do?
Rhona Pierce: Yeah, sure. I am Rhona Pierce. I am a former recruiter, and I now host the Workfluencer podcast. Every week, my guest and I explore how the creator economy is reshaping workplaces, how we build professional authority, and how companies connect with their audiences. That’s what I do all day, every day. I also have a content agency called Workfluencer Media, where I help companies produce employee-generated content campaigns.
Matt Alder: Absolutely, and I can highly recommend your podcast. People should definitely check it out and listen to it. So let’s get into Roundup. We’re looking at six episodes, as I say, that published during July and August, and there are some really interesting things here that I can’t wait to discuss. First up, episode 803, which is called AI Native Recruiting, and is an interview with Tracy St. Dic, who is Global Head of Talent at Zapier. Really interesting company, always interesting to talk to them. They have a really proactive approach when it comes to AI and how that works in terms of recruiting and organisational development, so it’s always a leading-edge conversation to learn from them and what they’re doing. So Rhona, dive straight in. Tell us what you thought of this interview. What stood out for you?
Rhona Pierce: Zapier continues to really lead the charge in AI adoption within their organisation, in their product, of course, but also in their hiring. What really stood out to me was the distinction they were making between using AI to make the same hiring process faster and actually questioning whether the process still makes sense. We all know that automating the same broken interview process is really not transformational, and it’s actually what most companies are doing. I really loved the idea of moving from interviews to auditions, and how that could produce much stronger signals as long as you’re not having people do a bunch of unpaid projects or adding unnecessary work for candidates. Really, it was how they’re thinking about using AI and how they’re using it in their process. Again, Zapier has been leading the charge on this, and I think they will continue to be the company to look at and learn from when it comes to AI and hiring.
Matt Alder: Yeah, I completely agree. It was a great conversation because she was also really open about their plans for the future. This is a journey that they’re on, and she talked about how they’re developing. A couple of things really stood out for me. In a lot of the interview we were talking about AI screening, and how they were actually pretty sceptical about it to start with. What they found was that they were talking to more people. They were finding applications that they would probably have missed or probably wouldn’t have seen had they not used the AI screener, and I think that’s a really interesting thread of conversation that comes up later with some of the other episodes we’re looking at. I thought that was really interesting. The other thing is that she talks about their AI fluency model and the type of skills that they assess people for when it comes to AI. A lot of employers are talking about wanting AI skills and AI-ready people and AI-native people and all this sort of stuff, but there’s very little about what that actually means beyond technical skills for people in technical roles. Here Tracy lays out the things that they look for that are not technical when it comes to AI fluency, and I just think that’s an area lots of people can learn from, because there aren’t really very many good descriptions of what AI skills are, are there?
Rhona Pierce: Yeah, no, we’re all learning this. We’re all making it up as we go, and I love how they have laid it out. The thing that I really, really love about them is that they’re not judging people’s current AI knowledge, because let’s face it, what you know today is obsolete tomorrow with how quickly this is going. It’s actually someone’s ability to learn, and I think that’s where a lot more companies should be focusing, because that’s really what you need in order to keep up with AI: the ability to learn and to know what to do as far as moving forward with AI. A lot of companies are focusing on the current, and that’s not where they need to be focusing.
Matt Alder: Yeah, I mean, the tools go out of date so quickly. I’m in there all day, every day, and I struggle to keep up. I find that something else has come out that I’ve not heard of, with more capabilities. It’s just insane. Those core skills, that ability to learn, particularly around the way that you think, are just so important. So I think there’s a huge amount that people can take from listening to that episode.
Matt Alder: I’m going to move on to episode 807 because, again, it’s a talent acquisition team implementing AI. There’s some interesting commonality between the two, and some other things that this really unearthed. This one’s called Trust, Transparency and the AI Interview. It’s a discussion with JB and Anneliese from the global talent acquisition team at Mirakl, and again, we’re talking about their implementation of AI screening, a voice agent in this particular case. Again, they were sceptical about doing this, and I think that’s another important point, but they have been really, really pleased with what’s come out of it. The thing that really stands out about this for me is how they build trust with candidates. I think one of the biggest issues that we’re facing at the moment is that candidates do not trust the recruiting process, and they certainly don’t trust AI in the recruiting process, and there are lots of good reasons for that. Actually, what we’re seeing with these companies who’ve got these great AI strategies is that it improves the candidate experience. It’s been a really positive thing. They get great feedback from candidates, and how you build that trust is really important. In Mirakl’s case, what they do is make transparency the foundation of all this. They publish AI guidelines, they tell candidates how they’d like them to use AI, they talk about how they use AI, and they’re very, very clear about the framing and what this is and what this isn’t. I think that’s just such a fundamentally important thing. What do you think?
Rhona Pierce: Yeah, I absolutely loved this one. Again, it’s something that I’ve been talking about. I wrote a pretty long article, considering what I usually write, about how, if done the right way, and I think Mirakl is doing it the right way, AI can actually help improve the candidate experience. For so many years, candidates have been complaining that we spend all this time applying and we never even get a chance to be heard. With the way they’re using AI, yes, you have more volume of applications. We all know this is an issue, right? Most recruiters don’t want to hand over that first conversation, so I understand how they were uncomfortable, because when I first heard about it, so was I. Thinking about it, though, if you do it correctly, if you lay things out, if you tell people what to expect and how you’re using it, and, more importantly, if you keep humans responsible for making the decisions, that’s really how you build that trust. I think they’re doing an amazing job, and there’s so much to learn from companies who were sceptical. This is a pretty great case study on how AI is actually improving candidate experience. Contrary to what most people are saying, that it’s making it worse, it actually, if done correctly, can improve it.
Matt Alder: I think you make an interesting point there, because in both of these cases there is such a strong role for human recruiters in this, which is different from the role that they may have done in the past. Actually, it means higher quality conversations, talking to candidates they probably wouldn’t have spoken to, and having time to really have those proper interactions and build that engagement. So a really interesting couple of case studies. Two different setups, but very similar results coming out of them, and I’m seeing that a lot from the stories that are appearing on the podcast. There’s a lot of commonality about the companies that are doing this well and what they find, so I think there are lots of lessons that people can learn there.
Matt Alder: I want to move on to the next one. We’re looking at episode 809, The Data Foundation for AI in Hiring. It’s a conversation with Lia Manafova, who leads talent technology strategy at Sanofi. Now, this is really interesting because this is the second, if not the third, conversation I’ve had like this with a large enterprise when it comes to AI and agentic. It’s a conversation I’m not hearing from anyone else. I’m not hearing it from vendors, and I’m not hearing it at conferences, but it really is the truth about what’s going on. What this is about is data. It’s saying that if you want to have proper agentic AI agents running across your employee lifecycle, you need to understand how your data is structured and where your data sits if you’re going to get the real full advantages of these tools. That is not an easy or a straightforward process. Now, it’s large enterprises that we’re talking about here, so for smaller companies this might be different. The conversation gets into the whole nuance around this: do you have one tool or do you have multiple tools, and how does the tech stack work in this new agentic AI world? If you’ve not come across this concept before or not heard people talking about it, this is definitely worth checking out, because I think that all large enterprises are either having this issue, solving this issue, or will come across this issue very soon. Rhona, what’s your take on it?
Rhona Pierce: You know, data is my love language. I’m one of the few people that really geeks out and focuses on these things. That’s from my former life as a recruiter. I did a lot of rec ops and things like that. So yes, a hundred million percent agree on this. Most people aren’t talking about this because it isn’t the sexy part of AI transformation, and it’s also the hardest part to clean up in most organisations, because we have a ton of legacy data scattered all over. Most of it lives on someone’s computer, not centralised, no matter the size of the organisation. This is something we definitely have to pay attention to, because for any type of AI adoption in your process to be successful, you really have to think about the data. You have to know where it is, what you use it for, where it’s coming from, and what the source of truth is. Without those conversations, and that real work that you have to do first, anything you put on top of it is not going to be successful. This is a really, really important conversation, and anyone who’s starting the process, or is already in the process of adding AI into their hiring and recruiting, really needs to listen to this episode, have these conversations internally, and start looking at the data before going and talking to any vendors. I also think vendors really need to be more mindful of this when it comes to the implementations that they’re selling. It’s just a win-win for everyone if this is paid attention to before we get to the sexy parts of the products.
Matt Alder: Yeah, I agree. I think there are two other things that came out of this conversation that are probably worth flagging up. First of all, we also talk about implementation, so she talks about how she’s taken the recruiters along on that journey. Then there’s her view of the future. This is a common theme that I’m seeing more and more: we’re moving to a world where there is no user interface on the software, because the software comes to you in your AI window, or whatever that is. There have been some big moves in tech. I think it was Salesforce last week who were acknowledging that this is going to be the case. I think we’re going to see some really significant landscape shifts in enterprise tech. It probably won’t happen as quickly as people think it will, because this conversation about having to get all the data in the right place, and that taking time, holds things back. I think the entire business software landscape is going to look very different in a couple of years’ time, definitely.
Matt Alder: Cool. Okay, so three really interesting case studies there. Moving on to the next three, there’s a slight change of gear here, but these are some topics that I know are very dear to your heart, Rhona, because we’ve talked about them at great length, so I was really interested in getting your views on this one. The next one we’re looking at is episode 812, Who Trains the Human in the Loop?, which is a really, really important question. Let me explain the context, then you can tell me what you think. It’s an interview with Johan Roos, who is a business school professor. He’s recently written a book called Human Magic, all about the role of humans in an AI world, what aspects of humans complement AI, and what the future looks like. Really, what we were talking about in this conversation is judgment, and judgment being built through experience. In a world where people are now cutting entry-level jobs because AI can do that work, how do people build up judgment? We get into that and we talk about it. It’s not a concept that people won’t recognise, but it’s something that just isn’t being discussed. What does the leadership pipeline look like in a few years’ time if you’ve not hired people at entry level, or people don’t have the chance to build up judgment by making mistakes and by working on the kind of work that you see at entry level? Is judgment only gained by experience? There’s some really interesting stuff around this that I think is important to talk about. So, judgment. What do you think?
Rhona Pierce: It’s something that worries me, because when we’re talking about succession planning, which everyone likes to talk about, we’re talking about it at the middle of the career. We’re looking at the middle and asking, okay, what happens, what are we doing, how are we building these leaders? Now, with AI taking, like you said, the entry-level jobs and the things that helped you build that judgment and know how to make that jump from middle to leadership, this is a real problem that we have to fix, and we really have to fix it now. That’s why I love that you are having these conversations. Eliminating junior roles raises the question you asked: is experience the only way that you build judgment? Do we need to reimagine it? Do we need to think of new ways for people to build this judgment? I don’t think we know that yet, so I think we need to have this balance. We can’t fully eliminate every junior role just because AI can do it. We need to be thinking more about the future than we are, and we really cannot be sleeping on those apprenticeships, those internships, and just growing people in your organisation. It’s not just the learning of a specific skill and judgment, but also of your specific organisation, that is being lost by not having that growth from entry level to leadership in your company.
Matt Alder: We also touched on the education system, in terms of it having to be much more vocational, really getting people ready for the world of work as it exists now, as opposed to as it existed 50 years ago. That echoes a conversation I had with a business school last week where we were talking about the same thing. If entry-level jobs are being cut or they’re changing, and AI is changing things, how does the education system respond to that? I know that again is a topic that we’ve talked about a lot. What is it that people are learning about work to prepare them for this very crazy, uncertain world that we now find ourselves in?
Rhona Pierce: I think we as a society have really underestimated how important it is to, one, rethink education, and two, rethink these entry-level roles, because it’s going to happen a lot quicker than we think. We’re talking about this as if it’s in the future, and we’re not going to have the people prepared. The future is here, because it’s going to happen a lot faster than we think, and we really need to make those changes. So I’m excited to see more people talk about this and, more importantly, to see what people are going to do.
Matt Alder: I want to move on to the next one, 816, because again it’s about judgment, and it’s almost a continuation of the previous conversation. This one’s called Hiring for Judgment in the AI Era. It’s a conversation with Craig Friedman, who is the Skills and Talent Transformation Leader at St. Charles Consulting Group. He’s written a great book called Enterprise Skills Unlocked. I think it’s the third time I’ve had him on the podcast, actually, because there’s really interesting thinking there around skills and what actually works in enterprises. Very practical, very pragmatic. A lot of this conversation covers the same area as the previous one, so entry-level hiring and all that kind of stuff, but it also goes a little bit deeper, because it’s saying that if people are using AI to do things, not just at the entry level, then human judgment is potentially being eroded, because we don’t have the opportunity to exercise it, as it were. What he talks about here are the practicalities around that: looking at judgment as a skill, how that can sit within a skills infrastructure within an organisation, and how it should be prioritised. In some ways it’s the solution to some of the issues in the previous episode, although it doesn’t talk about entry-level hiring, but again it puts that real big emphasis on judgment. What do you think of this one?
Rhona Pierce: I really like the idea of identifying the critical judgments within each role and building assessments and development opportunities around that. I think that’s a really good step towards what we were speaking about before. Maybe everyone isn’t going to get that hands-on experience, but when we understand what is needed for the judgment, and you’re building your hiring around that, you’re assessing it, and not only assessing it during hiring but then developing the people you hire based on these things, I think that’s a really good step in where we need to be going.
Matt Alder: Yeah, and a lot of the conversation talks about how you actually hire people and assess this as a skill. He had an interesting view as well on that question of how we get judgment if we can’t get the experience. We were talking about things like AI simulations to actually teach people judgment, and looking at building talent marketplaces that were matching on judgment and development rather than other skills. So it’s a really interesting deep dive into what this means right now for organisations. Those two episodes definitely complement each other, so it’s well worth listening to both of them. It’s worth listening to all of these episodes, which is why we picked them to talk about. Moving on to our final episode for this Roundup, 821, Why Every Employer Brand Sounds the Same, an interview with the legendary James Ellis, who I’m sure many of you will be familiar with through his work and his content. Unbelievably, it was 10 years since I last had him on the podcast, so I’m not quite sure how that happened, but it was great to catch up with him and the work that he’s doing on employer branding. Tell us what you thought about this one. What’s your take on employer branding these days? I’ll talk a bit more about the conversation afterwards.
Rhona Pierce: You know, this is my jam, and James is someone that I respect, that I’ve learned from, and a friend, and all of that. We have very similar stances when it comes to content in general and employer branding. This one really strongly aligns with how I think. Safe messaging makes companies invisible. Yeah, you can say that you care about people and value innovation, blah, blah, blah, but what does that mean? There’s so much content out there, and everyone is looking exactly the same. Companies really need to lean into sharing the truth. I always say it: every single company has some BS that you don’t like, right? You have to find the people that are okay with that level of BS, and the only way you’re going to do it is if you actually share that instead of trying to sugarcoat it and make everything look nice, quote unquote. Talent attraction really needs to be targeted, it really needs to be honest, and people are seeing through your sameness. This is really a time to lean into your differentiators, whether you think they’re good or not, and talk about that in your employer branding.
Matt Alder: I think it’s really important. What James has done here is an exercise where he scraped the career sites of the Fortune 100 and basically proved that all of their employer brands and all their employer brand positioning sound identical. It’s not even an employer brand. Everything sounds identical at the moment because everything’s written by AI, and everything is all about quantity rather than quality, so standing out is very difficult. What he leans into here is finding out what’s truly different about your organisation and using that to stand out, and there are some great examples of companies that have done that and the things that they’ve found. It’s also about really being transparent and honest. No company is perfect in every single way, so this is all about transparency and about standing out. It’s a really great interview, and really worth listening to in terms of what’s going on in employer branding right now. The other thing is that he indicated that the companies at the next level down from the Fortune 100 really have an opportunity to stand out and compete for talent with those big companies, because they all sound the same, so there’s the chance to be different. In some ways it’s always been the case with employer branding, but I think it’s particularly amplified with AI at the moment, isn’t it?
Rhona Pierce: Yeah, for sure. For a long time, as someone who does this day in and day out and speaks to companies about employer branding and employee-generated content, we’ve been conditioned to hide the differences. We want to look like the rest of the companies out there, and that’s absolutely not what we should be doing, because now everyone’s just going to AI, creating content and writing the website copy, and it’s literally all sounding the same. This is a time to really kick that old habit of hiding our differentiators and lean on those. I can’t say that enough, and James is on the same mission. It’s really an opportunity for the companies that do this to beat out the big companies when it comes to talent.
Matt Alder: I’m going to put you on the spot now. Six episodes. Which one was your favourite?
Rhona Pierce: This is too hard. It would definitely be the employer branding one, because that’s my thing, but I really think people need to listen to the one about data and getting your house in order before putting AI on top of everything, because I think that’s a real problem that needs to be solved.
Matt Alder: Yeah, and as the podcast host, I’m not allowed to pick favourites, because that would just be unfair. I think that these six episodes are a really good selection. If you’re not listening to any of them, I would check them out. If you’ve not listened to the podcast for a little while, this is a great route back to it, essentially. So thank you, Rhona, for joining me again. As I say, it’s always a pleasure to have you on the show. Thank you to everyone who has been watching, and to everyone listening to the recording later. Roundup will be back next month, and I look forward to seeing you all then. In the meantime, there is loads of great content going up on Recruiting Future. Check it out by following Recruiting Future wherever you listen to your podcasts. If you want to look at the archive, head over to recruitingfuture.com, where you can find all the episodes and all the transcripts.
Matt Alder: So thank you very much, Rhona, and thank you very much everyone for listening.
