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Unveiling the True Impact of Artificial Intelligence in Talent Selection: Separating the Hype from Reality
166 Plays1 year ago
In a recent study, over eighty percent of artificial intelligence initiatives within human resources and staffing involve some form of talent acquisition process. We find chatbots, machine learning, even automated selection tools that are used to rank order candidates. But where can AI powered applications really make a difference? How will it transform talent attraction and sourcing? Where can AI applications deliver specific value? And, ultimately, how will it change recruiting as we know it today?
In this episode of Avionte Digital Edge, we’ll dive into the world of Artificial Intelligence (AI) and talent selection with special guest, Dr. Amy Lui Abel, a Global Talent Partner at Lee Hecht Harrison and co-author of the book, Strategic Human Resource Development in Practice: Leveraging Talent for Sustained Performance in the Digital Age of AI. Together, with Chris Ryan, Chief Marketing and Strategy Officer at Avionte, she’ll help separate the hype from reality, focusing on practical ways for the staffing industry to leverage AI, evolve recruiting practices, create efficiencies, and transition to a more human-centric approach.
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Transcript
AI in Talent Acquisition: ChatGPT's Role
00:00:00
Speaker
In a recent study, over 80% of artificial intelligence initiatives within human resources and staffing involve some form of talent acquisition. Already, many recruiters are using applications like chat GPT to help write job descriptions.
How AI is Revolutionizing Recruiting
00:00:17
Speaker
We see chat bots, machine learning, even automated selection tools to rank order candidates.
00:00:23
Speaker
But where can AI-powered applications really make a difference, and how will it change recruiting as we know it today? On this episode of Aviante Digital Edge, we discuss artificial intelligence with talent acquisition expert Amy Lou Abel of Lee Hecht Harrison.
00:00:51
Speaker
Hello, this is Chris Ryan, the chief strategy and marketing officer with Aviante.
Cultural Perspectives on AI
00:00:56
Speaker
And this is the Aviante Digital Edge, a podcast focused on the digital transformation of staffing. Artificial intelligence is a loaded topic. In the 1920s, even before movie theaters had sound, we had silent films that explored the humanity of artificial intelligence. AI has become a pervasive trope in modern culture.
00:01:20
Speaker
Is it benevolent? Is it evil? Is it all-knowing or even just silly? In truth, we are fascinated by AI because it serves as a mirror for the way we view ourselves. Any virtue or flaw we have attributed to AI, well, that's something we have already assigned to ourselves. So what does this mean for employment and specifically staffing?
00:01:44
Speaker
Attracting and selecting the right job candidates has extraordinary economic impact for all stakeholders. And it has always been notoriously difficult.
Complexity in Staffing with AI
00:01:54
Speaker
And human judgment has always been the critical ingredient leading to success and to failure. And adding more complexity, we are now adding AI applications to the mix. So how will AI transform talent attraction and sourcing?
00:02:11
Speaker
Where can AI applications deliver specific value now? How can the staffing industry begin to approach artificial intelligence in a practical way without all the hype? To explore this further, I'm joined by Amy Lou Abel, a global talent partner with Lee Hecht Harrison and formerly the head of human capital research at the conference board. Amy has held roles at Accenture, Adobe, and Chaby Morgan Chase.
00:02:39
Speaker
And she recently co-authored a book, Strategic Human Resource Development and Practice, Leveraging Talent for Sustained Performance in the Digital Age of AI. So Amy, welcome. Thank you for having me, Chris. I'm delighted to join you.
00:02:55
Speaker
So Amy, when people describe artificial intelligence and the future of staffing and recruiting, many of us imagine there's this large black box that runs the entire recruiting funnel. You take a million names, you put them in a hopper, you throw them in, and out comes the perfect candidate, pre-selected and ready for hire. But the reality seems a little different.
00:03:20
Speaker
Apparently, AI can be used in a lot of different ways to augment different stages of the talent acquisition process. So take us through the landscape of artificial intelligence and talent acquisition. And from your perspective, how would you describe this ecosystem?
Efficiency Boost: AI Handling Mundane Tasks
00:03:37
Speaker
That's a big question. Thank you, Chris. And I like the way you frame that, which is everyone is now reading and learning and hearing about artificial intelligence and how it's somehow taking over our world. And that's just a little bit too broad of a statement. It's much more nuanced when you actually think about how AI can be used
00:03:59
Speaker
as tools to support what we do in a more efficient manner, in a faster element. Just doing a lot of activities and tasks that are frankly mundane, tedious, and time-consuming for humans that somehow a computer, artificial intelligence, can help us with. If we narrow that down a little bit, it's not just this big black box taking over our world and our lives and our jobs. It's really how can we implement these tools?
00:04:27
Speaker
For talent acquisition specifically, it's not just this one thing that we do in this space, right? Yes, we have sourcing, meaning we find a lot of candidates and we hopefully identify the few that are the right candidates. But in recruiting, there's a ton more things that we do, whether it's
00:04:47
Speaker
branding our organization, branding the job. How do we reach out? How do we communicate? How do we find people all the way to the sourcing or fixing the resumes or scheduling interviews, assessments, background
Practical AI for Recruiting Workflows
00:05:02
Speaker
checking? I mean, there's so many steps that leads up to, of course, the onboarding process. And each and every stage or transaction that we have in this talent acquisition and recruiting process, there's opportunity
00:05:17
Speaker
to make it better, faster, and easier. I mean, what I hear you saying is let's stop worrying about the intentions and motivations of AI and figure out how we can improve a workflow or how we can improve a decision somewhere in the talent acquisition process. So let's get real. Let's get practical in the way we apply this technology to help us.
00:05:39
Speaker
Exactly. You know, let's walk away from the hype. There's a lot of hype right now. So let's figure out what is not the hype and what could be more specific and helpful to us. And I'll leave you with one sort of tagline to think about. AI will not replace people in jobs. It's people who use AI will replace those who don't.
00:06:04
Speaker
And that seems to make a lot of sense. Over the years, I've looked at how technology has changed the workplace. And the one thing that's clear is that when new technology is introduced, we need new skills and we need people who are willing to adopt that new technology in order to continue growing our economy, growing a business.
00:06:24
Speaker
So it's really the ability of individuals to put that technology to work that makes the difference. And the ability to change and adapt to new tools seems to be the most important characteristic for moving forward. So you don't believe that AI is going to replace a recruiter anytime soon. No, no. If anything, I think it makes the job and the function even better because we can take away the mundane and tedious things, right? Now, AI will
00:06:53
Speaker
evolve the role of the recruiter. And we'll spend a little bit of time talking more about that. But this is exactly what you just said. How can we as recruiters think differently about what we do? It's not everything being replaced by a robot. Which parts of our job will evolve
00:07:10
Speaker
and transition into things that we can basically add higher value. And where can we connect more with people and candidates on a relationship base? How do we enhance that experience with candidates that will then connect and make our jobs again better, faster, more efficient?
00:07:28
Speaker
You know, ultimately, our job is a matching job, right? We want to connect candidates with roles and jobs that they want to be in. And how do we do that in an optimal way? And AI, like a computer, like emails, like any of these other technologies that have been introduced can help us do it in a more efficient and easier way. So as you were talking about the ecosystem of the talent funnel, one of the things that I noticed was that
00:07:58
Speaker
There were a lot of different areas where AI can actually improve the recruiting process that have nothing to do with the actual moment of selection. For example, marketing to new talent or marketing to a broad network of people or supporting communications and mundane activities. I'm curious from your standpoint.
00:08:19
Speaker
What are some of the early successes of AI and the talent acquisition process that you think are actually working fairly well right now that you would recommend that people look at?
00:08:30
Speaker
Sure, absolutely. So you already said earlier in the podcast that as of two or three years ago, 80% of AI solutions within HR land in the talent acquisition recruiting space. There's a reason for that, right? Why did all the vendors and all the new technologists jump into the talent acquisition space
00:08:51
Speaker
And it's because where you have lots and lots of data is the perfect place potentially for the use of AI. So recruiting is about millions of candidates, and that's a lot of data. There's a lot of data about the candidates, the skills. How can we bring that in so that we can find the right people in a faster, easier way?
Targeted Talent Marketing with AI
00:09:15
Speaker
And I think that's the case.
00:09:17
Speaker
the usage in different parts of the TA process, right? There's not just the sourcing. It's marketing, for example, reaching out, finding the candidates. So AI is perfect for targeted talent marketing. Think about that as a new area of focus or a new area to improve.
00:09:35
Speaker
target talent marketing. So many of us, for example, use Facebook. And, you know, Facebook knows you better than you know yourself. And the ads come up very, very seamlessly. And they seem to know what you want to look for, buy or connect with.
00:09:53
Speaker
And it just happens, because that's AI. Now, think about that from a target marketing perspective. But you're looking for talent and candidates. So an ad comes up in my Facebook or TikTok or whatever other tool you want to use. And all of a sudden, the ad's like, well, do you need to find a new role in this capacity? Do you want to enhance new skills in this way? And it's very targeted towards what you want, what you think you want to grow into.
00:10:21
Speaker
I mean, we haven't seen any of that, or at least I haven't seen any of that. I think that's an amazing opportunity for AI for us to reach the right candidates. What's interesting about that is we often think of AI as a tool that helps the recruiter make a decision, but talent marketing, it almost sounds like you're using AI to help potential candidates make a decision, to help them self-navigate to new jobs or new roles.
00:10:47
Speaker
perhaps in new industries. So it almost sounds like in order to make AI work effectively, you really need to look very carefully at each of the individual stages of the talent acquisition funnel and apply AI a little differently. So talent marketing, presumably that's not the recruiter selecting people. In that case, that's people selecting potential new roles and being able to find the people who are most likely to self navigate to those roles.
00:11:17
Speaker
Absolutely. Ultimately, the recruiting process again is about matching, right? And matching takes two people, takes two parties. And so it's not just what the recruiter feels and does and looks for, it's what the candidate feels and does and look for.
00:11:33
Speaker
How do we blend the two to this perfect match? And I think the challenge is there's lots of data about what candidates want, what their behaviors are, where they'd like to be, what they'd like to do, their skills. And if we can use AI to make sense of that, just like in target marketing for ads and purchases in your social media platforms, it's the same, but you're using it from a job and recruiting perspective.
00:12:01
Speaker
Yeah, you know, it's funny. Sometimes I've heard my significant other say that she finds it creepy when Facebook knows what she wants. Are people going to find it a little creepy when suddenly somebody knows that you're sick of your current job and you want a new one?
00:12:18
Speaker
So I find that completely creepy. I completely agree with that. But I will tell you that especially the generations that are coming into the workforce and younger generations, this is the way they live. This is the way they function. I don't think they find it as creepy as I do. And they want that. They want to know that advertisers are
00:12:39
Speaker
bringing in the right products that they're interested in. And if somebody is telling me to look at a different job that would increase my skills, increase my salary, increase my role in some capacity, I would click on that. I would be interested. Like everybody else, I want to
00:12:57
Speaker
do more, learn more, grow more, get paid more, all of those things. If you're appealing to the right aspects of people, why wouldn't they click on it? Why wouldn't they click on the ad and find out more? But to your earlier point, there's a number of different places in the recruiting process that AI could be used. So things like chatbots are fairly common used in different ways. So
00:13:21
Speaker
having a candidate be supported by an artificial intelligence chatbot throughout the recruiting process. So they're not wondering what's going on. There's a lot of pain in the recruiting process today about what's going on in the process. Where am I? Are they still interested? All these other questions that come up. It sounds a little like dating. It sounds a little like dating where you're sort of wondering what is the other party thinking.
00:13:46
Speaker
So if used in that way, a chatbot can actually lower your stress as you're going through an interview process, it sounds like. Absolutely. This is a fun story, which I think connect directly to what we're talking about from a recruiting process. So I have now seen a new app out there that is for dating, specifically what you said, dating and matchmaking. But there are lots of apps out there that just match people using data and technology, no human intervention, and they're fairly low cost and
00:14:15
Speaker
People complain about those apps, unfortunately, because you see a lot of nonsense and a lot of inappropriate candidates, but you can't filter, and it's very time-consuming. So, new apps are now presenting using tech and data, but also a person, a matchmaker,
00:14:34
Speaker
who actually filters for you and then presents to you real personal connection. They talk to you, they get to know you, they interview you, they talk to the other candidate, and then they suggest that the two of you meet for a date.
00:14:49
Speaker
So to me, this is a great example of the future of recruiting, where it's not that robots will take over all of it, it's that the human provides higher value to the process and make a better match and an easier transition and less stress, less anxiety, all of those wonderful things. I just thought it was such a great example from a dating perspective that connects to this topic.
00:15:13
Speaker
Well, it also makes me wonder what would happen if you took a company and you took its culture and put it into me harmony and then try to have people match up. But we won't go down that road. I guess we should stay on the straight and narrow. When we think about that process, you talk about different levels of AI intervention, one of which is augmentation. I think there's another level where it's true assistance and then it's essentially autonomous use of AI in order to make decisions.
00:15:43
Speaker
Talk to us a little bit about where you think the most appropriate use of AI and the level of intervention that should be used in a recruiting process. Yeah, no, great question. And let me clarify just a tiny bit for the listener, which is
00:15:58
Speaker
There are many, many shades of AI. It's not like this one app or one system. And depending on how you design the AI app, there are levels of application, meaning the more sophisticated the AI app, the more it learns by itself,
00:16:17
Speaker
and the more it makes decisions by itself. So you can have a chatbot that makes no decisions. You ask a question, it spits a response. It's a very simple, assisted AI tool. No decision, no learning. But then if you sort of evolve into different shades of AI, for example, a driverless car. A driverless car
00:16:39
Speaker
is actually making decisions about turning left or turning right at this point. And that's what the testing is doing nowadays with driverless cars. So you have very simple AI to very sophisticated autonomous AI that are actually learning and making decisions as we go. So there's many variations of that. It's a spectrum.
00:16:59
Speaker
So the goal for us is to figure out what are the different apps that would help in our specific TA transactional processes and figure out how much decision making is being made. Now, sort of good news and bad news. The good news is that the technology can make decisions. Like you can tell an AI to rank order 500 candidates and present to you the top 10
00:17:27
Speaker
based on certain number of criteria that you've added. So that seems really great. But the bad news is there's a significant amount of data privacy, risk biases, as well as law, like GDPR in Europe. There's lots of laws around actually making a decision on people with technology, meaning AI.
00:17:51
Speaker
So we kind of need to balance that there's a little bit of a risk that we need to really be careful with where we want to distinguish using the tool to help us filter rank match do all sorts of different things.
00:18:05
Speaker
But then ultimately, we as humans have to make the decision on another human being because there's so many risks that you can just imagine out of it. If the AI tool made a wrong choice, which they often can, you could literally ruin somebody's career if you're letting the tool make the decision. And so you don't
Challenges: Privacy, Bias, and Legal Constraints
00:18:23
Speaker
want that. I don't think we want that as human beings. We still want to make decisions, but it's great to have a tool that will make perhaps our lives a little bit easier to make those choices. And how do we use that?
00:18:34
Speaker
So since you brought up the issue of legality and compliance, I wanted to talk a little bit about the law in New York City and the use of artificial intelligence to make selection criteria. I don't know of anyone today who is actually using artificial intelligence to say yes to one candidate and no to five others, but there may be artificial intelligence tools, even simple things like resume parsing, where
00:19:02
Speaker
If you've got 10,000 names and you set your resume parsing in a certain way, you may create various kinds of bias that will create a problem from an EEOC perspective. And so I'm curious, how do you think the New York law might change the way we use these tools if it becomes more widely applied in other states?
00:19:24
Speaker
So usually laws are a little bit behind in the technology. And I think we struggle with that as a society. And there was the new law also coming out of Europe. It's the new AI Act, whatever they're calling it, where they are banning, basically in the EU, facial recognition and all sorts of use of AI on people.
00:19:46
Speaker
And so we see a lot of legality changes at play trying to support what is basically very fast evolving technology. And let's be clear, all the AI tools and tech can do all of those things today. This is not five or 10 years down the road. They can select, they can rank, they can filter, they can select the one candidate. All of those things can be done today. But I don't think we want that to happen as human beings because we know inherently
00:20:16
Speaker
AI uses past data, the data can be flawed. The data can be biased. There's many examples out there of companies that have tested this and found biases and flawed data everywhere. I think the law is pushing all of the vendors that develop new AI apps and us as consumers using the AI to be really careful about how we use the data.
00:20:41
Speaker
And there's some basic premises that we can say, for example, allowing people to opt in or not opt in. You need to get the permission to use the AI tool. So that's opt in. And then the other thing is setting up policies and governance around basically human beings can only make decisions on another human being.
00:21:02
Speaker
It doesn't mean we can't use the tools to help, but we're basically never going to cross that threshold of having just the machine make a choice, even though we can do it today. It can absolutely do it today, but we don't want that. And so this is where it gets very almost philosophical, right? How do we as a society want to use these very powerful tools to figure out how we want to evolve? Now, do I think there is a risk in
00:21:32
Speaker
Some companies, some applications somewhere, somebody's just saying, okay, let's just use the application. Let's just use the technology. They make the choices and we just move on. I think that's a very likely risk, but there's a high problem with that. And so we just need to be well-educated as people.
00:21:49
Speaker
to say, how do we not make that happen? How do we not let that happen? And I don't want to exaggerate to go into the movies, like the Terminator movies, where AI takes over. It's not quite that dramatic yet, but the laws are all coming in, right? They're all happening because I think people see the potential of where things can go wrong. So presumably, having very focused AI applications, for example, there's an AI application for talent marketing. There's an AI application for chatbot.
00:22:18
Speaker
there may be an application for resume parsing or filtering certain kinds of skills and qualifications or managing credentials but each of those would be its own separate and discreet application augmenting an existing process rather than replacing it autonomously.
00:22:35
Speaker
is essentially what you were saying, that the real opportunity, if I understand, is we're going to improve the efficiency and the workflow, and we're going to augment all along the entire talent funnel, but we're not going to do it holistically with a single Colossus style AI entity. Rather, it's going to be small, discrete tools that are used for very specific, well understood purposes. Is that fair?
00:23:00
Speaker
So it is fair as of today. This is about evolution of any technologies where small apps and small companies come up with all sorts of different ways. And you're right. Pretty much each step of the recruiting process today
00:23:15
Speaker
there are AI tools that will help you do it faster and better. So whether it's job advertising or sourcing or scheduling, interviewing, background checking, there are tools and apps for AI to help you with this. But it sounds like it's very cumbersome, doesn't it? Like you mean I as a recruiter have to learn 10 different tools because each tool takes care of each different transaction. So as a technologist with some background in this, I think that will evolve.
00:23:45
Speaker
and apps will integrate and the market will come up with more holistic applications and offerings where it's more of a one-stop shop or at least less cumbersome.
Selecting AI Tools for Recruiting Needs
00:23:56
Speaker
However, for today, what I would say to our listeners and those that are recruiting and looking at these different tools is identify where you have high need. Again, from a tech perspective, we call this the use case.
00:24:10
Speaker
What is the need or the problem areas that you have? Think about each step of the TA process that you use today. Where is there a higher need, more pain, more inefficiencies? And I would target those as first use cases.
00:24:28
Speaker
and then think and identify AI apps that might be able to help you with those specific areas. Is it sourcing, which is a very big and popular one? But you know what? Maybe it's background checking or assessments. Assessments is a big one. You want to assess candidates whether they're appropriate. And AI is perfect for assessments because it's all about data. How do we dig into a bazillion points of data and identify the right patterns and the right attributes that we want
00:24:58
Speaker
in a candidate so that we think this will make it a better match to the job and the role. And there are apps already that exist today. So in your business, where are there higher need and higher pain points is where I would say is a good place to start.
00:25:15
Speaker
Yes. And you know, it's interesting as you were commenting on technology, and I was thinking that certainly for the staffing and recruiting software platforms like Aviante itself, one of the things that we are heavily focused on is the ability to integrate third party software applications into the existing workflow. And from our standpoint.
00:25:35
Speaker
being able to integrate separate best-in-class AI capabilities into the core platform, understanding that they're constantly going to be evolving and changing, is actually an advantage for us rather than trying to put AI into every aspect of our platform. It's almost more important for us to be able to do appropriate AI callouts at different stages of the process because, for example, the application du jour that we are seeing,
00:26:01
Speaker
is around programmatic job advertising is an area people are concerned about managing total spend on job boards and so there are now applications out here that can help you optimize your market spend.
00:26:14
Speaker
One thing I was curious about as well, Amy, I know you've spent a lot of time doing what I would call high value recruiting, where you are looking for that needle in the haystack, that one right person, whether it's a programmer or a senior executive who will fit in and add extraordinary value.
00:26:32
Speaker
Many Aviante customers are in staffing where it's not that they need to hire one perfect candidate, but in some cases they need to hire 20 qualified candidates who are reliable, who will show up, who will do their job, and will stay through an assignment. And so I'm curious, does the calculus around how we use AI as a recruitment tool change when you're doing higher volume recruiting as opposed to precise needle in a haystack recruiting?
00:26:59
Speaker
I actually think it helps even more because it's about scaling.
00:27:04
Speaker
you're not looking for the one candidate, you're looking for more candidates, which means you need a larger pool to search and define. And how do you identify? So again, not only from the sourcing perspective, but think about like using AI to match behavioral attributes. You need to find 20 candidates with these right behavioral attributes that matches to this open position job description that you have in different ways. And how do you
00:27:32
Speaker
connect those opportunities to the candidates. And so I know this sounds so inhuman, which is there's so many points of data about us as human beings, skill sets, behavioral attributes, characteristics, personality traits, whatever you want to call it. And there's any one of those traits to disqualify a candidate, presumably. So it's good.
00:27:52
Speaker
It could. But here's the thing. So this is how we train AI applications. And that's actually the words that are used. We train AI applications, I don't mean to be facetious, but like training a dog or training a pet. You're training an application on what to look for, how to look for it, and what are perhaps some variances around that. It might eliminate candidates. If there's one characteristic that you think is completely wrong for this role,
00:28:21
Speaker
and you've kind of marked it and you train the artificial intelligence app to say, anybody with this characteristic, we don't want. But you have to be very careful. You have to be really clear that that's what you're going after. But this is the potential for AI and the use of any of those characteristics to filter and to identify the right candidates. So presumably, if you're evaluating an artificial intelligence tool,
00:28:47
Speaker
you need to ask what variables are you training on? What variables can you manipulate? And how much data have you used to train? And then how much feedback can you get from an existing workflow to improve that model in order to make the selection as effective as possible?
00:29:04
Speaker
Yes. The app can learn, right? You can continue to retrain it, refine it, and you definitely need to vet what comes out of AI systems, right? Whatever the result is, you want to make sure you're just not believing it wholeheartedly. You definitely want to vet, you want to verify, you want to check, whatever you want to call it, but making sure that result is actually what you want.
00:29:28
Speaker
So if you were starting your own recruiting or staffing agency and you wanted to put together a technology stack that had best in class artificial intelligence tools, what components would you look for first? How would you assemble it? How would you go about building it? What questions would you ask? Where would you start?
00:29:49
Speaker
Okay. Great question. I would start with a bigger picture view and then dig deeper. So one of the evolutions that I think about for the role of the recruiter is, you know, we just, we keep talking about the transactional steps in the recruiting process, right? Step one, we do this step two, step three, et cetera.
00:30:11
Speaker
We all are familiar with these steps in the process, but the role of the recruiter I think will evolve from focusing on these transactional elements in the recruiting process and evolving it into more relational aspects, the people aspects. This is where we have the advantage that AI can never replace because AI is not human.
00:30:34
Speaker
So what does that mean? In thinking about the process, where in the flow can we really think about the human-centric design of it? And this is what companies do inside the company as well. They call that the employee experience. We're just taking the same premise and thinking about the candidate experience. And I know we all talk about candidate experiences, but
00:30:57
Speaker
really thinking about the steps in your process from a candidate's experience, the human design, again, tossing everything that's more human-focused, and does that mean, I mean, I am making this up, does that mean in the process we connect them more with other human beings? Are there groups of candidates that they can connect with more to form communities that helps them in certain ways around the process?
00:31:23
Speaker
And what other human elements can we introduce so that we make that experience more relational versus more transactional? And easing any anxiety, stresses, and all that kind of stuff also helps. So sourcing, I think, is always going to be a big problem. There's a lot of people, lots of skills. And I still believe there are lots of people around that we don't know enough about them. We either don't know where they are, where they exist, what kind of skills.
00:31:51
Speaker
But where are these hidden sources of talent pools? And what if they're not on LinkedIn? Where are you going to find them? And how are you going to find them? This is where I think that target marketing approach can really start to reach out in different ways. So things like sourcing, which includes job advertising, target marketing, things like that. The assessments, I think, and again, it sounds a little bit less human. We want to assess more is another area I think
00:32:18
Speaker
of growth opportunity where using the assessments and by the way, you can ask chat GPT to create very personalized, customized assessments for you on the fly. You don't need to be a scientist creating this perfect assessment tool. So I can get a upper or a 16 PF from chat GPT that will assess somebody. So
00:32:41
Speaker
I mean, you can debate this because those companies will say, we've got the better tool, it's a better assessment. But if you want to ask a couple of candidates five questions that are on the fly and very personalized, you can do that in like five minutes with chatGPD today. And how do you refine your technique as a recruiter
00:33:02
Speaker
to continually assess and find those right candidates. So I think that's another area of opportunity because it's all about identifying the right attributes or the right traits, the right skills for people to fit into this role better.
00:33:19
Speaker
And I mean, we can use a simple non-tech example. There's a famous hotel in India. This reminds me of the story where they go to villages and neighboring towns to find candidates for their hotel.
00:33:34
Speaker
They want people who have natural inclination for service. They're more humble. They have this deference to the elders. They have specific traits where they're looking to serve. And this is what they pull. And they go into the schools, like elementary, middle school, high schools, asking the staff and administrators and teachers to identify these students earlier on.
00:33:59
Speaker
and they bring them into the hotel and they're like the best hotel customer service people ever. They will do absolutely anything to bring their guests delight. It's like that. They did it in a very non-tech way, but how do we do this on a high scale with lots of people, lots of jobs? There's plenty of stories and analogies like that, but now how do we use AI to help us do that?
00:34:23
Speaker
Got it. So I guess back to the question of how would you apply AI intelligently in a greenfield operation? It sounds to me like having a very clear focus strategy around what you're trying to accomplish, who you're trying to look for. So the right application of artificial intelligence might look very different.
00:34:43
Speaker
Depending on the nature of, is it a staffing company focused on healthcare professionals? Is it for professional recruiting where you're looking for technologists? You might have very different approaches and uses of AI in order to get what you want.
00:34:58
Speaker
Absolutely. And if folks feel like it's very overwhelming because it can be, there's lots going on in this AI space, I would start with the use case. Where is the need? Where
The Future: AI in Talent Lifecycle Management
00:35:10
Speaker
is the most pain or a specific area you want to grow and change in your recruiting process? Start with very specific use cases, and then you can go out and identify apps that might start to help you with how to do that better.
00:35:25
Speaker
Got it. So Amy, we're towards the end of our interview. Are there any final thoughts or words of wisdom you have around artificial intelligence and recruiting? I think recapping some earlier thoughts, but then bringing it to a finer point around using AI to your advantage, not worrying and fearing about it and how it's somehow going to take over the world.
00:35:48
Speaker
These blended recruiting models are definitely coming, if not already here, and will change the recruiting landscape, I would say fairly dramatically. And so identifying and thinking about how it impacts what we do as individuals and as our own companies, how we do our business, getting to that human-centric design, and basically you becoming the talent advocate
00:36:15
Speaker
You're not just sourcing or looking for a candidate. How are you thinking about the talent from the beginning of advertising to them, finding them, sourcing them, but even onboarding them, training them? What is the skills that they need? Even expanding beyond the matching part and going into what does this talent need for the current role for future roles
00:36:39
Speaker
And how does that talent advocacy play itself out? So for example, a company that I know in this space is now finding candidates, training them, and then placing them out to a company. Meaning they're taking the risk of the learning, the time,
00:36:59
Speaker
the expense of training or retraining and upskilling for specific need to a specific company. And recruiting companies are taking that on because the talent doesn't have the specific skills that the client wants. So they're really expanding into different parts
00:37:16
Speaker
of the HR employee lifecycle, if you will. So not only the learning, the training, but think about employee experiences, employee retention, talent mobility. Those are very key buzzwords today. How do we continue to move our talent, grow their skills, and keep placing them in the right fit and roles? This is where I think this whole recruiting talent acquisition model is going to evolve into.
00:37:42
Speaker
So it's not really talent acquisition anymore. It almost sounds like a total talent life cycle, if you will. Yeah. Yeah. We need to think more about that. Now you may not do that tomorrow, but you really need to think about how it integrates and maybe it's integrating with your clients. Maybe it's integrating with different companies or like you said, from a software and platform integrating different apps, different tasks into a stream that makes it easier for me as a client to find the candidates on board them, place them.
00:38:12
Speaker
retain them. If it's a solution that makes it easier for me, that would be so much more appealing. Thank you, Amy, for joining us. This has been a lot of fun, and I look forward to having you join us as a speaker at Aviante Connect 2023 to explore this topic further. And thank you to all our listeners for joining us.
00:38:34
Speaker
You can subscribe to our podcast, the Aviante Digital Edge, or learn more about Aviante digital staffing solutions at aviante.com. Until next time, this is Chris Ryan, and thank you for listening.