We’re at a fork in the road for how companies adopt AI. Some are taking shortcuts, slashing entry-level roles and chasing efficiency savings. Others are slowing down to ask a harder question: how does this technology actually create new value? The data suggests that many companies are choosing the wrong path, using AI as a scapegoat for cost-cutting that is really caused by other business challenges. The consequences for their talent pipelines, skills development, and long-term competitiveness could be severe.
So what separates organisations that get AI right from those that don’t, and what does this mean for talent acquisition?
My guest this week is Kelly Monahan, founder of Beyond the Desk. and a highly experienced labour economist who advises organisations on building genuine AI capability. In our conversation, she explains what most companies are getting wrong, the skills that actually matter, and the implications for talent acquisition.
In the interview, we discuss:
• How are skills evolving?
• Why AI is being used as a scapegoat
• The real cost of cutting entry-level roles
• Three skills that define AI readiness
• Protecting high-value human touchpoints
• Buy or build? Using technology strategically
• AI for organizational value, not efficiency shortcuts
• Data privacy and compliance risks
• Developing the skills and mindset needed to future-proof your career
• What does the future look like?
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00:00
Matt Alder
Many organizations are treating AI as an efficiency play, cutting roles and reducing costs without a clear strategy. The real opportunity is using AI to create entirely new value. The companies that get this wrong risk losing their talent pipelines, their institutional knowledge and their competitive edge. So what does getting it right actually look like? Keep listening to find out. Support for this podcast comes from Workable. Workable is known for its award winning applicant tracking and HR platform. Used by more than 30,000 companies worldwide to hire and manage talent more efficiently, they’ve recently rolled out two major product updates. First, they’ve completely rebuilt their reporting suite from the ground up. Workable now delivers enterprise ready data and reporting, giving teams the ability to create custom dashboards, tables, charts and pivot views using any hiring or HR data in the system.
01:05
Matt Alder
It makes it much easier to track hiring performance, workforce trends and ROI without juggling spreadsheets or external BI tools. They’ve also introduced something really interesting called Workable Agent, a new AI recruiting teammate built directly into the ats. I actually had the chance to see this in action at a recent event and it’s pretty impressive. You start by having a conversation about the role and the agent drafts the job brief, searches through a database of more than 400 million candidate profiles, engages candidates, screens them against your requirements, and delivers a short list of qualified interview ready candidates. It essentially gives your team full recruiting agency level capabilities directly inside your ats. If you’re looking to optimize your recruiting and HR processes and improve your ROI along the way, I definitely recommend checking out Workable.
02:03
Matt Alder
You can learn more at workable.com or by visiting their LinkedIn page.
02:26
Matt Alder
Hi there. Welcome to episode 777 of Recruiting Future with me, Matt Alder. We’re at a fork in the road for how companies are adopting AI. Some are taking shortcuts, slashing entry level jobs and chasing efficiency savings. Others are slowing down to ask a harder question. How does this technology actually create new value? The data is suggesting that many companies are choosing the wrong path, using AI as a scapegoat for cuts to fix other business challenges. The consequences for their talent pipelines, skills development and long term competitiveness could be severe. So what separates organizations that get AI right from those that don’t? And what does this all mean for talent acquisition? My guest this week is Kelly Monahan founder of Beyond the Desk and a highly experienced labor economist who advises organizations on building genuine AI Capability.
03:28
Matt Alder
In our conversation, she explains what most companies are getting wrong about AI, the skills that actually matter, and the implications for talent acquisition. Hi Kelly and welcome to the podcast.
03:41
Kelly Monahan
Thank you so much for having me today.
03:43
Matt Alder
An absolute pleasure to have you on the show. Please could you introduce yourself and tell everyone what you do?
03:49
Kelly Monahan
Yes. So I’m Kelly Monahan and I have spent the last 20 years in corporate America working at some of the most interesting companies. I would argue so spent my career in consulting Deloitte and Accenture, really running their first Future of Work research program. I’m a researcher at heart. I have my PhD in organizational behavior. But then for the last five years I started working in tech and so got a front row seat working at places like Meta and Upwork and really beginning to see this AI revolution take place in real time. And so right now I’ve started my own company called beyond the Desk where I am doing both future work research, advisory and keynote speaking. Really helping companies outside the tech industry begin to understand how to take advantage of AI today.
04:32
Matt Alder
So let’s start with the way that work and skills are evolving. I know that you look very carefully at labor data in terms of what’s going on and the skills that are in demand, that are being hired for what’s changed most dramatically in the last sort of 12 to 18 months about how skills and work are panning out.
04:53
Kelly Monahan
Yes. You know, right now I’m calling this the great actually AI paradox when it comes to skills. Because here’s I think one of the most profound change I’ve seen in the data is still following a skills bias technology change. Meaning that if you have high tech skills and you’re able to do high value work, you’re still commanding a higher wage and you’re staying employed. And likewise, if you’re doing, and I say lower value, not in terms of any sort of dignity that’s to the role, but just more value of the task itself. If you’re doing more low value, more transactional work, you’re obviously starting to see some of those effects of automation. However, what I think is so interesting from the skills perspective that we have not seen before with the technology is let’s take software engineers and coders as an example.
05:34
Kelly Monahan
Those are highly technical jobs and skills. Over the last 12 months, programs like Claude at OpenAI have really excelled in the coding sphere. Those jobs are actually requiring more human skills that we traditionally haven’t seen in those professions. Likewise, if you’re in a very human job, whether that’s even that you’re in nursing or retail, on the front lines or in the marketing space, or, you know, in this case, we’re talking about talent acquisition. Those are very human jobs. And yet we’re seeing the need for more technology skills ever before. And so it’s a list of this paradox where if you’re in a tech role, you’ve got to start leaning in on the human side, and if you’re in a human role, you’ve got to really start leaning in on the tech side. And we haven’t seen that before with the technology.
06:15
Matt Alder
I mean, how are employers coping with that? Because things are moving very quickly and they kind of have workforces that don’t necessarily have the right skills. How can they close that gap? What are you seeing happening in that?
06:28
Kelly Monahan
I think what’s unfortunate, Matt, I look at the data, only 40% of the executives today even have an awareness of the AI skills within their organization. So if we’re going to be honest, I think a lot of leaders today, quite frankly, are flying quite blind when it comes to what are the AI skills needed, first of all. And then second of all, who within my organization possesses those? We don’t have great visibility into that. And I think what I find somewhat ironic is if we look at the number one skill that’s being posted right now on LinkedIn across the globe is the term AI skills. And so everyone wants it, but no one quite knows what it is and how much they have their organization. And so, again, I see this is another paradox of our times.
07:07
Kelly Monahan
That talent acquisition, I think, is going to probably be the forefront of helping define when we say AI skills, what exactly does that mean? It’s going to change depending on the role that you’re hiring for. It’s obviously very different. You’re hiring for a software engineer versus a product manager versus a marketer. You need AI skills across all of those domains. But they’re going to look very differently. And so I think there’s a lot of rewriting the playbook that’s required right now, both for leaders and talent acquisition, to figure out what are the skills, how do we start defining them, and then how do we start measuring that? I think that’s going to be really interesting, coming to focus in the next year or so.
07:41
Matt Alder
Drilling into that and reflecting back on.
07:43
Matt Alder
What you said earlier, AI skills, we’re not just talking about tech skills, are we? There’s lots of other things going on there.
07:50
Kelly Monahan
I think that is so profound, and I think you’re spot on with that. I think, you know, as we talk About AI skills, I, I, I define it in this way. Okay, so hopefully this is helpful for your audience, but this is how I’m making sense of it right now with my clients. Is the very first skill you need, if we’re going to talk about AI skills, is strong domain knowledge. You have to have, whether that’s industry expertise, role expertise. You know, I think I get worried about everyone saying, oh, these are great, we’re going to democratize all this intelligence. Yes and no. You know, I’m not trained to be a lawyer and yes, I’m using AI to help review some legal documents, but that by no means is a substitute for actual legal expertise.
08:26
Kelly Monahan
And I’m not going to know if AI is hallucinating, which by the way still does 10 to 12% of the time. And so without having that domain expertise, I think we’re really, you’re actually entering risk in your organization. So number one, skill is strong domain expertise. Number two, I think every person today, all the way up as a CEO down your front lines, has to start understanding data analytics in basic statistics. That is how this AI world runs today. And understanding just basic probabilities is going to help people understand the outcome of what AI is giving and how to better work with that. So data skills are no longer just for the data science team or it. I do think those have to spread across your entire workforce. And then the third thing skill is really understanding when do you buy AI?
09:13
Kelly Monahan
Would you build AI and having that fluency of the AI ecosystem, God, there’s like a thousand tools that are coming out every day. And so really making sure as part of your AI skill set that you understand what is at the forefront of these new tools. And then instead where maybe because appliance reasons, regulation, do you actually go need to actually build your own AI bot system, whatever that might look like. So those are the three ways that I’m thinking and helping clients really begin to define. You talk about AI skills, these three things have to be present.
09:41
Matt Alder
I think that is so applicable to what is going on in talent acquisition itself at the moment. And I kind of want to dive into that. Before I do though, I just thought an interesting piece around the domain expertise that you were talking about there. Because there’s obviously this trend or this belief or this strategy even that entry level roles are disappearing because AI can do entry level roles, but on that basis then in the future we have people with no domain expertise and that surely can’t be a good thing.
10:14
Kelly Monahan
I think it’s a big gamble. Organizations are Making right now, unfortunately we get an opportunity to work with a lot of labor economists. We’re starting to see some small effects that are directly tied to AI with beginning to eliminate entry level roles in many organizations. And I think this is very shortsighted because I think these people are playing checkers in not chess. And talent acquisition leaders are going to know this better than anyone. If you do not have a strong talent pipeline, that talent is going to become much more expensive when you’re ready to start bringing them in at mid senior levels. So one, I think this is just actually a very inefficient play because that talent’s going to actually become more expensive as they get experience.
10:52
Kelly Monahan
And two, I do worry we are taking a shortcut here and we’re a little bit mystified by AI and it’s really at the end of the day for many leaders at Black Box giving output and we’re starting to incorporate that into really, you know, strong decision making processes. And my fear is, to your point, if we do not have that implicit knowledge that only comes by growing up in a role or a function organization, we are putting people behind. And quite frankly you’re putting your organization at risk because you’re not going to necessarily have that future talent as number one. And then number two, you’re losing some of that implicit knowledge. Bingo. Boomers are starting to retire at mass.
11:29
Kelly Monahan
There’s going to be huge knowledge loss and AI is not going to be able to capture all that knowledge that takes place within your organization that’s not necessarily captured in slack channels and team meetings and so forth. And so think about all that knowledge that exists that’s not digital exhaust. All of our young people are losing that by not being able to take part in entry level roles today.
11:48
Matt Alder
And I think there’s a lot there also about how companies are responding to AI. And it kind of just reminds me of lots of other sort of tech revolutions that we’ve seen in the past. It’s still a very immature response that people are kind of having in that, you know, I that means we can get rid of a load of jobs or we didn’t get the productivity that were looking for. Therefore AI is to blame. And it’s just kind of, it becomes like a thing that encompasses everything rather than, you know, the strategies and all the kind of individual pieces of work and thinking that needed round it as people understand it better.
12:28
Kelly Monahan
I think that’s right. I think what we’re seeing a lot quite frankly is that AI is being used as a Scapegoat coming out of the pandemic. I know no one wants to talk about COVID anymore, but still coming out of the pandemic, organizations were operating in many ways in low to no growth environments and have been set. Demand has profoundly shifted to many industries. And so instead of doing the harder, messier work, which is right, sizing our business, redesigning roles, really trying to figure out what is the new innovation risk you should be taking to capture better customer value, we’re trying to take the shortcut with AI and starting to plug it and play it in ways that I actually do not think are going to help organizational value in the long term.
13:05
Kelly Monahan
And to your point, these shortcuts I think actually have tremendous cost in the long run. And I think time’s going to tell organizations that are taking their time, slowing down to figure out what is AI actually solving for, what is the friction point and not just necessarily executing it and handing out all these OpenAI license to the workforce to go figure out how to save money and cut costs.
13:28
Matt Alder
Let’s dive into the talent acquisition part of this because obviously recruiting it’s being disrupted. TA teams are perhaps fearful about their future. We’re looking at automation. All kinds of things are going on there. I mean, how should TA professionals, individually and as a profession as a whole be responding to AI and the threats and opportunities that it brings?
13:52
Kelly Monahan
I have two pieces of advice right now for talent acquisition because I do think as you look at all of the jobs right now, I think of coding, marketing and talent acquisition as probably being the most disrupted or at least spurring disruptors of this technology. And so the very first thing that I encourage talent acquisition experts and leaders to do is figure out every job is a collection of tasks. And we know AI is going to come in and automate a lot of those low value, low transaction cost tasks. So that includes a lot of, you know, writing anything that can be done what I call one shot prompts with AI where if you can give it one instruction. As an illustrate talent acquisition example, I need to find a thousand candidates that pass this various criteria that are located in here.
14:38
Kelly Monahan
AI is probably able to go conduct that search much faster through APIs and being able to look into LinkedIn profiles and someone manually going through and having to do that as a human. And so that to me is a perfect task that takes a lot of time but maybe provides low value in many ways. So that is going to be those lowest value tasks that you want to start using AI for. However, on the flip side Are those high value, high human touch points. And I think, you know, as a recruiter, as a talent acquisition professional, you are the very first entry point and face of the brand and the very first point of culture that this recruiter is actually behind to candidates.
15:17
Kelly Monahan
And so the question is, how do you ensure that you protect that, you know, and how do you make sure that you have those high touch points, that you have more free time to actually do those human tasks? Which is to explain the culture, which is to be a better culture carrier for the organization, which takes time and capacity from a human perspective. And so I just encourage talent acquisition professionals to really list those tasks that they’re doing and figuring out what are those ones that have human touch points and lean in and start shifting a lot more of your work towards that direction.
15:49
Kelly Monahan
And then the second thing I encourage talent acquisition professionals to think about is what do you continue to put a fence around that no matter how good AI gets, you will choose not to use it because you know, there’s either too much risk or this is a human task. And I think, I mean we’ve seen the lawsuits, right, with Eightfold and some of the other things that have come out when we start having AI as a decision maker when it comes to talent acquisition. I do not think that’s necessarily a great idea. Humans are certainly biased, but AI is certainly biased and hallucinating as well.
16:19
Matt Alder
Yeah, absolutely. And I suppose going back to what you were saying about the AI skills as it were, and the third one you mentioned there, of understanding the kind of infrastructure of AI and knowing when to build stuff and buy stuff and all that sort of thing, I mean, what advice would you give to TA leaders around that in terms of making sure that they are utilizing the technology in the best possible, most strategic way?
16:42
Kelly Monahan
Yeah, I think the one low hanging fruit opportunity I see nearly every organization is there’s so much data within the existing organization of culture, markers of high performance, of really what good looks like working at this organization. I think there’s a lot of opportunity on the talent acquisition side to really begin to use AI to mine that data and really begin to whether that’s creating better assessments or better candidate profiles and really being at the forefront of better understanding. This is what a match in our organization looks like. We have all the intelligence, it’s just often sitting in various databases and often not clean and requires a lot of data analysis. And I grew up in the HR side, so I know how hard it is to get those data science resources dedicated to the Town acquisition function and afterwards product development.
17:29
Kelly Monahan
But I think forming that partnership with your data science team and really leaning in on what do we already know from a data perspective and how can I bring that to my recruiting Personas and profiles as I go out? I think that’s great because the number one thing that obviously leaders are looking for is how sticky talent is, how long does that talent stay? And oftentimes we see that number decreasing and I think probably because we’re having four matches in many ways that are not necessary in the age of AI. So I think that’s the first thing. I think the second thing is we have to be so careful with personal identifying information and really knowing the limitations of what you upload into these AI systems.
18:10
Kelly Monahan
Oftentimes, whether you’re using a lot of these tools, your data’s going into the cloud, if you’ve got personal identifying information in there, I just, I see a lot of risk happening right now. And so that’s why I think I’m telling you to slow down a bit and figure out is that insight actually worth the risk of what you’re putting in. And again, how do you have that level of education partnership with your compliance teams and legal teams to be able to use these tools at speed, but also slow down enough to have the right human judgment so you’re not putting the company or a candidate’s profile or even existing employee’s profile at risk. So I think those are the two things that I encourage people to think through as they think about incorporating more of AI in talent acquisition process.
18:50
Matt Alder
And you’ve touched on this already, but I just wanted to sort of dig into it a little bit deeper on a kind of an individual basis. What would your advice be to TA professionals, but really any professional in terms of what they should be doing to sort of future proof their career in what are very disruptive but potentially very scary times.
19:12
Kelly Monahan
So there’s two things that I, I try to do myself too. So practice what you preach because let me add to like the list of professions that are disruptor, you know, being disrupted early on. Research is definitely one of it as well. So my job has definitely turned upside down in the last 18 months. So two things that I’m doing that I encourage others to think about. Number one, it’s more than just signing on to a ChatGPT or copilot. It’s really taking the next step and digging deeper. And so Coursera, LinkedIn, learning, finding mentors online, really figuring out and experimenting with these tools.
19:48
Kelly Monahan
There are so much capabilities now that agent mode has been unlocked in a lot of these tools of actually moving beyond just using large language models as a point of insight or output, but actually starting to move it so it’s executing on your behalf. And so I think that’s the shift that we really need to start making right now. I don’t say everyone, but many people can go and use a ChatGPT and create a marketing brochure at this point, but very few are then able to actually execute it. So then it’s personalizing and sending emails out on their behalf and really freeing up that time. So I think there’s a huge learning curve to make that pivot. But those that are making the pivot I think are going to continue to improve their careers.
20:29
Kelly Monahan
And then I think the second thing is, which is a harder part, and I’m saying this to myself as much as I’m saying it to your audience, is we have to really rethink what the job looks like. I loved my job three years ago, what I was doing. I love the task. I love being able to do qualitative research and quantitative research and have these insights. And now I’m realizing that world no longer exists. I mean, in my world we’re now serving AI agents, which is really hard for me to understand. You know, how, how? Well, you know, they actually mimic human behavior and so forth. But the reality is I have to come to grips that the world that I want is no longer there for my profession.
21:11
Kelly Monahan
And so instead it is up to me to start to create that opportunity of what I now want my job to look like with these new realities. I think retaliation acquisition is the same thing. The way that were recruiting talent to two years ago, 18 months ago no longer exists and we’re never going back. And so now in this new reality, what is the opportunity before you and how does your job shift? And the more that we have agency and control in that conversation, I think the better our we’re going to be able to future proof our careers.
21:39
Matt Alder
And as a final question that sort of leads directly on from that. What do you think the future looks like? Where is all this going? What might we be if we’re having this conversation again in a couple of years time? What would we be talking about?
21:51
Kelly Monahan
You know, Matt, can I do 2 future? We’re like at a crossroads. So like let me start with the doom and gloom and then we’ll end on optimism. Yeah, I worry if organizations continue to pursue AI the way that they are as a cost cutting measure and efficiency play. I do worry we may see job loss, especially in the knowledge work that we haven’t seen before. And so I think it’s going to require a lot of people to really reinvent themselves and really rethink through. If we need less of what we have today, what do these college educated, trained professionals do? And we know where the shortages are and oftentimes that is naturally in the industries that we’ve been trained in, you know, and so if we think about manufacturing and healthcare and education, that’s where all the job growth is right now.
22:39
Kelly Monahan
And so I think there’s a future where we’re going to see some pivots in terms of both industry and career pathway to stay employed and kind of moving where the demand is. I think that’s going to be a hard reality for many of us. The brighter optimistic side, I think where there’s a future, we’re talking a couple years from now. And organizations have really begin to extract value, not efficiency, out of this technology. And with value comes greater job creation and new ways of doing things and new ways of delivering value. And with that, I think the pivots then become within one’s industry, within one’s organization, and actually both command higher wages as they’re able to do higher value work. So I think the reality is there’s probably going to be a middle reality that represents both of those two.
23:22
Kelly Monahan
I just encourage people who are employed today to really be pushing their organization to think through what future is that organization creating? Because those are the two pathways that I think are present before us today and they are being made every day. And the choice is that we have. And so making sure you’re aligning yourself with an organization that is attracting value and not just efficiency right now, 100%.
23:42
Matt Alder
Kelly, thank you very much for talking to me.
23:45
Kelly Monahan
Thank you so much for having me this wonderful conversation.
23:48
Matt Alder
My thanks to Kelly. You can follow this podcast on Apple Podcasts, on Spotify or wherever you listen to your podcasts. You can search all the past episodes at recruitingfuture.com on that site. You can also subscribe to our weekly newsletter, Recruiting Future Feast, and get the inside track on everything that’s coming up on the show. Thanks very much for listening. I’ll be back next time and I hope you’ll join me.
