3229: SmartRecruiters on Balancing Automation and Human Connection

[00:00:03] Hiring has always been about people, yet more than ever, it's driven by technology. So how do we strike the right balance between AI efficiency and the human touch? Well, my guest today is Rebecca Carr. She's the CEO of a company called Smart Recruiters. And today we're going to explore the evolving role of AI in talent acquisition and talk about everything from reducing bias to enhancing technology.

[00:00:33] Candidate Discovery and even navigating the risks and rewards of automation. So with 56% of leaders saying recruitment has become more challenging in the last five years, is AI the solution that we need or is he adding to the complexity? It's time to introduce you to Rebecca where we're going to talk about all this and much more. So thank you for joining me on the podcast today, Rebecca. Can you tell everyone listening a little about who you are and what you do?

[00:01:03] Sure. Well, it's great to be here. My name is Rebecca Carr. I'm the CEO of Smart Recruiters. Smart Recruiters is a talent acquisition platform essentially helping companies around the world hire talent through software that's embedded in their recruiting workflows. Most of my business is actually in Europe. We have offices in London, in Paris, in Berlin, in Krakow. But I myself am based on the East Coast of the United States in Boston, where our US headquarters is in New York.

[00:01:34] Fantastic. Well, thank you so much for sitting down with me today. One of the reasons I was excited to get you on the podcast was I was reading a Smart Recruiters recent report that revealed that 56% of leaders right now feel that talent acquisition has now become more challenging ever than in the last five years.

[00:01:54] So I've got to ask, I mean, what do you see as the main drivers for this complexity and how can organizations better adapt their recruitment strategies to address these challenges effectively? We've all seen the cost of a bad hire and retaining talent must be top of most people's agenda. But what's going wrong here? Yeah. Well, to be honest with you, I thought that the number was a bit lower than I expected.

[00:02:20] Based on some of the feedback that we hear from the field, a lot of talent acquisition professionals are very, very frustrated with this workflow. And really, I'd say that it's three different things from my seat. The first is that a lot of the systems that are leveraged in these back office workflows, HR is one, but accounting could be another is a good example, have become very, very complex, very, very deep, very, very difficult to use.

[00:02:50] And a lot of the workflows that historically, especially in the case of recruiting, were about connecting with people and building conversations and making deeper connections so that you could evaluate fit into your business have become overly administrative. 80% of the recruiting workflow, we estimate is filling out forms and clicking buttons and validating a specific data point and running a report.

[00:03:16] And that's not conducive to the type of role that a lot of these recruiters started in many years ago, where they were networking and building communities of talent. And I'd say the second one is really user expectations. Those technologies have not innovated very much over the last decade. You could call innovation adding another button here or there, but have not truly transformed the way that people hire.

[00:03:43] And yet, the candidates that are interacting with this technology, they are consuming amazing new B2C, consumer-led tech, everything from the innovation on their phone to sort of what they're seeing as they interact with productivity tools in the workplace, as you can imagine.

[00:04:03] And so when they go to apply to a job and go through a hiring workflow, their expectation is that it's as simple to do as ordering an Uber when it's time to go find a cab on the street. And it's not that at all. In fact, it's very, very tedious, lots of questions. You get kicked out of the workflow. No one follows up to you with you. It's a black hole.

[00:04:28] And so that frustration is then making it harder to convince folks to come into the business and even engage with candidates effectively. And I'd say the last one is much more administrative, but it's about integrations and data access.

[00:04:43] As these systems have kind of stagnated, a lot of these talent acquisition professionals have gone and integrated point solutions, best-of-breed career sites and best-of-breed interview management software and best-of-breed video interviewing. And all of those integrations are connecting into this core workflow and doing so quite poorly. So the data consistency across these platforms is not there.

[00:05:10] It's difficult to report on what's working and what's not. The user experience is broken, not just for the candidate, but also for the hirer in the workflow. And it has also created, frankly, a significant amount of cost in these talent acquisition P&Ls, which they're now being asked to go and tighten, which is creating a lot of churn in the point solution ecosystem in talent acquisition specifically.

[00:05:40] And predictably, organizations are going to demand more strategic support from their HR leaders and HR partners. But traditionally, HR technologies have had a reputation for at best falling short of delivering transformative outcomes. And at worst, a lot of those HR apps have a reputation for being just too clunky and confusing and complex.

[00:06:02] What role do you see things like AI playing in enabling HR to shift from transactional to a more strategic function, a function that drives greater business impact? Yeah, well, I really see AI providing three different outcomes to end users in the TA workflow. The first is really around improved discovery, especially with the amount of individuals looking for work these days.

[00:06:31] There's a significant amount of candidates applying to jobs. So the volume of applications is much, much higher than what has been in years previous. And further to that, these recruiting teams have been reduced in many ways. There's been organizations that have really cut back on their HR functions and have laid off some of these individuals in order to find more efficiency. I mean, if you're not hiring as much, you theoretically wouldn't need as many recruiters.

[00:06:59] So there's fewer people doing the screening and there's more applications coming in. And AI offers an opportunity to provide better discovery of who is a good match for that job. So scoring, matching, advanced screening capabilities are certainly a category of AI technology that's cropped up. It's one that we've even invested in.

[00:07:21] It also, for what it's worth, is a bit riskier and that obviously we're leveraging algorithms to decide on your behalf who you should look at first. This is where I think a lot of regulatory work will be done. But it does help to speed up the pace to hiring someone into your workflow. The second is really around efficiency.

[00:07:45] I said 80% of the hiring workflows are administrative, and that means that 80% of what a recruiter does, clicking a button and filling out a form and getting an approval, could theoretically be automated by an agent. And there's a lot of Gen AI products that are helping do just that. They're writing emails. They're writing campaigns. They're writing job descriptions.

[00:08:10] They're taking action, workflow action, on behalf of users based on certain things that they do in the system. So this efficiency, I think, is really low-hanging fruit for organizations and an easy place to get started, in my opinion. And then the last one is really around insight. A lot of people, because of that data problem that I described up front, don't really know what's working and what is not working in their workflow.

[00:08:35] And agents can look at a map of data and say, hey, we've noticed that this isn't working. Why don't you try to do this? Do you want us to do this? Yes or no? Yes. Great. We'll go do that. So connecting insight back to efficiency is, I think, probably one of the more exciting areas for me around investment. The people analytics workflow in TA is very robust, and there's a lot that we can learn from it.

[00:09:03] It's also wildly underutilized by most end users in this workflow. And I think agents are going to make us smarter by just informing us of what could be changed. And that could be anything from you don't have enough candidates here to, you know, this compliance workflow is out of date. And based on these regulatory requirements, you should make this update now in order to keep yourself in compliance with what's to come.

[00:09:29] So discovery, efficiency, insight, sort of big buckets of outcome that I anticipate AI doing for talent acquisition. And I think one of the key challenges in recruitment is mitigating bias. And as humans, we're often almost pre-programmed to unwittingly hire people that we may see similar to ourselves. And AI is often accused of favoring keywords over talent or hidden strengths.

[00:09:54] So how do you see AI technologies helping organizations make those fairer and more equitable hiring decisions? And do you have any examples of how smart recruiters you might be addressing unconscious bias in that entire hiring process? Because it is a notoriously tricky balance. And I'd love to bring that to life with a few real world examples if you have one. Yeah. So you're absolutely right. There's a lot of subconscious bias.

[00:10:21] And I could talk for a bit about actually the complexities that AI brings around amplifying that subconscious bias, if not implemented the correct way. But theoretically, an agent doesn't have this. And thus, they are looking at the information that's provided to them. At the moment, it's provided even the skills or the assessments that are happening in the application workflow. And they're saying, hey, you should look at these 10 people first.

[00:10:49] And smart recruiters is doing that right now. So essentially, when you go post a job and it's distributed and applications come through the workflow, we are actually, when the hirer logs in to look at their job, saying that these 10 people we would recommend reviewing first. When you open that profile, we're then telling you exactly why we said that. So it could be their tenure in a specific role.

[00:11:17] It could be the compatibility of that company versus your own. It could be a specific assessment or skill that's been validated in the workflow. But we're leading with a lot of explainability to build trust with that individual so that when they look at that score that says high match or a 90% match, then they can actually understand how we got there. And then we're actually building in tools that says, did we get it right?

[00:11:46] Would you like us to weight a different skill more than the next? So the end users have the ability to say, this is all great, but you're missing this particular attribute that I'd love to find in people. And they can add that and weight it a bit more aggressively than maybe we would in our default algorithms.

[00:12:08] So as they continue to use the match score, it's getting better and better and better, which is fantastic. Fantastic. We're also implementing a lot of different tools on the front end of the process when you post a job to actually remove bias from job descriptions so that the right people are applying to a role without necessarily presuming that your organization is only going to fit this type of person.

[00:12:37] So being a little bit more transparent on the front end about exactly what is required so that the right candidates come through the workflow. This is something that a lot of applicant tracking systems are doing and I think has resulted in some excellent outcomes for end users.

[00:12:55] And delivering on everything that we're talking about today is a notoriously tricky and fine balancing app because while AI can improve efficiency, there is concerns in some quarters about an over-reliance on automation and how we could end up depersonalizing recruitment.

[00:13:12] So from your point of view here, how can HR leaders strike that right balance between automation and maintaining a meaningful human connection during that entire hiring and onboarding process? Yeah, I'd say a couple of things. One is there's really, in my opinion, four major, I guess you could call them human-centric decision points in a recruitment workflow. The first is what am I looking for?

[00:13:42] Who do I actually need? Yes, there's some objective inputs that would say this is the type of person that you're replacing or the role that you're filling, but what specifically am I, the hiring manager, looking for? And how do I craft the right external description or ad to be representative of that? That's an important moment. The second is who, of all the people I'm seeing, who do I actually want to meet?

[00:14:08] Yes, agents can provide me inputs and scores and say this is the right person to meet with first, but I need to be able to weigh in and say, yes, that's the one. No, that's not the one. So that selection and then interview decision point. So once I meet that person, do I actually want them to work with me is a very human-centric decision point. The third is I'm making an offer.

[00:14:33] So I now know I'm going to hire Neil and I need to have a conversation with Neil to sell him on this opportunity, to share the offer details, to get him excited about what's to come. And then I'd say the fourth is now that Neil has accepted, what do I actually need to do to make this person successful? Not just objectively, but also subjectively within the organization in terms of building relationships with the people around him.

[00:15:02] AI is going to offer the ability to do little bits and pieces of all of that. But I think what's most important for organizations is that they protect those four decision points as best they can. They can experiment with everything in between. And experimentation is a big piece of advice I give a lot of my customers. AI is one of those technologies where first impressions really, really, really matter.

[00:15:28] So just deciding you're going to roll out a fully agentic hiring workflow is quite bold. Some companies will surely do this. But the reality is that if one person has a really bad experience or that decision makes one bad or that agent makes one bad decision, then the workflow is rejected and quite aggressively. Bad news travels fast, so to speak.

[00:15:52] And so it's really important that as TA leaders start to experiment across their ecosystem, that they're protecting those decision points and they're leaning into everything in between just to make sure that they keep that human connection to the workflow. Finding a job is very personal and hiring someone is very personal.

[00:16:16] And I think it would be amiss if agents automated the workflow so exceptionally that that connection to your place of employment and the person you work for was lost in that evaluation process. And, of course, we're now entering the third year since generative AI and all the hype that surrounded it arrived. And many businesses, though, are still trying to understand how they can leverage this technology within their teams in the right way.

[00:16:45] And, of course, generative AI, it presents both opportunities and risks, especially in recruitment. So what would you say are some of the most exciting applications of Gen AI in talent acquisition? And what should organizations be maybe cautious about when integrating the tech into their hiring workflows? Yeah, I'd say that probably some of the best ones are the ability for agents to change tone based on who they're talking to.

[00:17:14] So, obviously, there's a lot of Gen AI applications in the workflow from job descriptions to interview templates to scorecards to emails to sourcing campaigns. But a good example being some of our chat products, as you're setting them up and you're dropping them into different experiences.

[00:17:34] One could be maybe an intern hiring workflow and the other could be more of a corporate recruiting workflow that you, as the admin of that chat feature, can actually set a tone and a personality that is appealing and conducive to the role that's being recruited for and the audience that is being spoken to in that moment.

[00:17:58] And, of course, it's lending itself to a level of personalization that's solving for that first gap that I actually shared at the earlier part of our conversation around user expectations. Consumer applications are wildly personal. It feels like they know you. And to bring that same level of tonality into the hiring workflow, I think, has been very attractive, especially to the next generation of our workforce.

[00:18:25] And I think some of those applications have been very unique. I will say, though, I wouldn't just set it and forget it. You want to be watching how people engage in that conversation and react, be measuring a lot of the outcomes of those conversations to make sure they're trending in the right direction. Gen AI will obviously put forth a first outcome. And then as people engage or reject it, it will change.

[00:18:54] You might get the wrong level of engagement from the wrong types of candidates based on the way that it's structured. And so just keeping a good pulse check on the results of the applications that are using it is, I think, very important to just making sure it's aligning to your expectations long term. And over the last five years, we've seen a rise in distributed global workforces, hybrid work models and increased competition for talent.

[00:19:21] And as a result, recruitment has become a much more highly complex process in many ways. So how can companies leverage AI to maybe optimize their hiring strategies and navigate these challenges more effectively? Because so much has happened over the last few years, hasn't it? Yeah, I'd say that the insight outcome of AI and talent acquisition is probably the one that's going to drive the most impact here, specific to hiring strategies.

[00:19:48] A lot of these agents see enough of what is happening across your ecosystem, as well as what's happening outside of that recruitment workflow. So you obviously hire a lot of folks. They are onboarded into your organization. They're either successful or not.

[00:20:05] And as agents speak to each other across platforms, it can actually be very predictive in the types of skills that you should be bringing into your business, where those skills are most prevalent, where those skills have seen the most success in terms of development, which managers have fostered that skill successfully within your ecosystem.

[00:20:31] There's a lot of data and insightful and thoughtful outputs that these agents can provide that could actually drive where, who, and when you hire and can make you smarter in that strategic planning moment before you even open a job, start spending money, bringing people into the business, investing your time in interviewing. These agents can help guide you on what's going to drive the most impact the quickest.

[00:21:02] And I recently read a stat, I think it was in Gartner's 2025 HR top priorities report, and they highlighted that the importance of optimizing HR technology was a huge trend. And yeah, on the flip side of that, there's a huge disconnect. Only 55% of HR leaders reported that their current systems don't meet business needs.

[00:21:24] So what steps should organizations take to ensure that their HR technologies can better align with and support their strategic goals moving forward? Yeah, I would say that the disconnect stems from the level of stagnation in the innovation space in HR technology in general and recruiting too. It also, I think, comes from a bit of fear. I don't think a lot of HR tech leaders know where to start when it comes with AI.

[00:21:53] They're frustrated by what they have, but they're also overwhelmed with the pace that technology is moving around them and the expectations their users, and that's not just their candidates, their hires are having of them and their technology. In some cases, these systems are so ingrained in their ecosystem, so integrated, that replacing them is a very high-cost activity that comes with a lot of risk, a lot of change.

[00:22:21] And so I think that one of the things I would probably encourage is experimentation and proof of concept. You inevitably have one business unit, one region of the world, one country that likes to push the envelope a little bit, so to speak.

[00:22:41] And a lot of the vendors in the AI space are actually very open and actually excited about the potential of taking a smaller group of users, learning from how they integrate their technology, iterating really quickly to maximize the results, so that as you roll it out more broadly across your organization, there's much, much higher levels of adoption.

[00:23:07] This is lower risk to the vendor, it's lower risk to you, and it's lower cost if for some reason you end up picking the wrong vendor or one that isn't successful in achieving your needs. So I've been sort of saying define your problem space. Like what's the one thing you want to solve the most? And then it could be interview management, it could be job posting, it could be screening and matching in the workflow.

[00:23:32] Pick that one thing that is the most painful to you, and then start small and build from there and have a conversation with your vendors and give them feedback quickly, because they're going to take that feedback and incorporate it much faster than they have in the past, and make it easier for you to build the business case to expand it much larger across your organization. And as the CEO of Smart Recruiters, you are right in the eye of the storm, so to speak.

[00:24:01] And I know it can be incredibly challenging to try and predict the future, but if I was to ask you to, I don't know, look into a virtual crystal ball here, how do you envision the future of AI and recruitment continuously evolving? And any advice that you'd give to any HR or recruitment leaders that could be listening today? Maybe they're navigating the rapid advancements in AI, while any advice on how they can ensure that the human elements of recruitment also are preserved?

[00:24:27] Because as I said earlier in our conversation, it is a very delicate balancing act, I would imagine. Yeah. Well, so I think the future of AI and the recruiting workflow is that the systems that you're training all of your hirers and interviewers and coordinators to log into and manage, I don't think you will need them to log in the future.

[00:24:50] I think one of the things that agents are going to do is they're going to make those big applicant tracking systems and HCMs almost like operating systems for your HR data set. And all the activities and inputs that those users have historically been logging in to provide you will be found in the flow of work. Your hiring manager will have a conversation in Teams or Slack with an agent about what they're looking for. That agent will produce a job description that will bring it back.

[00:25:19] They will approve it right there. They'll provide them five candidates. You'll give them inputs. None of this will be happening in those back office tools. And so one of the things that I would be really prioritizing is data consistency across all my platforms. If you want to have a powerful operating system, your tools need to speak to each other very, very well. They need to have tight integrations. You need to be using the same terminology.

[00:25:49] The skills taxonomies need to be matching across all these infrastructures so that those agents can be sending the right signals out into this flow of work. And I would also be prioritizing those channels. Where are all of your hiring managers? Are they on WhatsApp? Are they on SMS? Are they on Slack? Are they on Teams? Are they in Salesforce? Are they in ServiceNow?

[00:26:12] Understanding where the lion's share of activity happens so that then you can prioritize those integrations and be testing those as part of the flow of work as a first step is going to be critical. But that data, that data piece is probably the biggest one. It's the iceberg with the underwater massive behemoth iceberg under that surface that you could accidentally run into.

[00:26:41] That in itself is a lot of work. And I would be preparing for that to be very clean, very robust, very normalized. Because those user experiences that you've historically been prioritizing are going to diminish. And all of the experiences your hiring managers and interviewers and candidates will have will actually be in the tools that they use every day and have already been optimized. So less emphasis on that user experience, more on data.

[00:27:11] Well, thank you so much for sharing your insights today around how HR leaders can navigate some of the complexities of talent acquisition using AI while also, of course, ensuring that the human elements of recruitment are preserved. But I'd like to have a little fun with you now and ask you to leave everyone listening with one final gift. We do have a Spotify playlist where I ask a guest to leave a song that means something to them. Guilty Pleasures Are Allowed.

[00:27:38] Or a book that they'd simply recommend or is important to them, too. I don't mind which, but what would you like to leave everyone listening and why? Well, I would say that one of the most impactful books that I've ever read is fairly unknown. It's called Immunity to Change. It's by Robert Keegan and Lisa Leahy from Harvard Business School.

[00:28:02] If you are any leader, any manager around the world that's received feedback, so let's just say you need to delegate more. I say that to my team all the time. What this book essentially unpacks is why it's so hard for you to delegate. It is true that the human psyche has an immunity to change, an immunity to doing something different.

[00:28:29] You see this when people tell you, oh, well, if you just ate healthier and didn't drink that wine at night and went to the gym every day, you'd be healthier. Why aren't people doing those three things? Well, the same is true in business. And this book helps to essentially unpack how you start to understand the reasons for why you don't delegate or you aren't an active listener or you always show up late.

[00:28:58] And then you run experiments to sort of create change in your world so that you can solve the problems that everyone sees. And looking at the feedback I'd received as a leader through that lens has been very, very impactful to me personally in just seeing my own personal growth and improvement accelerate. What a great choice. I'll get that added straight to our Amazon wishlist.

[00:29:25] And for anyone listening wanting to find out more information about smart recruiters, digging a little bit deeper on any of the topics we explored today, where would you like to point everyone listening? Oh, they should head on over to smartrecruiters.com for everything about our platform and our hiring methodologies and AI products that are coming to market. Awesome. I'll have links to everything there.

[00:29:49] And we've covered so much today from how AI can reduce unconscious bias through data-driven decisions and recommendations, but also the downsides of over-reliance on AI and automated screening processes and bot interactions that can depersonalize recruitment.

[00:30:07] But I think the overall message is how HR and recruitment leaders can leverage AI to address all of these challenges and more when assessing the risks and opportunities of AI-driven recruitment strategies. So many big takeaways. I would invite anyone listening to feedback on what they would like to add to today's conversation. But more than anything, just thank you for starting it today. Well, thank you for having me. AI is undoubtedly reshaping recruitment.

[00:30:33] But as we've learned today, technology alone isn't the answer. It's about leveraging AI to empower HR, not replace that human connection that makes hiring work. So a big thank you to Rebecca Carr for sharing her insights on how HR leaders can rethink AI automation and bias mitigation to build stronger and more strategic hiring processes. But what do you think? Is AI helping or hurting recruitment?

[00:31:04] Love to hear your thoughts as always. Let's keep this conversation going. Get me on LinkedIn, X, Instagram, just at Neil C. Hughes. But I've taken up far too much of your time already. I will return again tomorrow. Hopefully we can talk again then. But bye for now.