[Podcast] Panel: Greater Efficiency with AI in Staffing & Recruiting

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Show notes

We’re diving deep into how AI can handle tasks to boost productivity, with Tom Erb sharing insights on tools like Fireflies and Google Gemini that expertly tackle note-taking, job postings, and more. We’ll explore the second wave of AI as touched on by Erb, with mighty nations like the EU and the US fueling resources to harness its potential.

Our guests bring a treasure trove of expertise, with Benjamin Mena spotlighting the automation magic of AI in marketing and finance, while Brad Bialy advocates for user-friendly AI solutions that offload mundane tasks. The AMA with the audience brings a discussion balancing AI and human connection in recruiting – a critical dance for success.

Join us for a riveting discussion where our guests share their rich backgrounds in digital marketing and AI, while we unpack the infinite potential of AI tools to revolutionize how we work, communicate, and balance our work-life dynamics.

_______________________

The following tools, applications, and websites were mentioned in this podcast episode:

1. Firefly
2. Zoom with AI
3. Chat GPT
4. Google Gemini
5. Apollo IO
6. Taplio
7. Microsoft Bookings
8. Calendly
9. Opus
10. CastMagic
11. Note taker (specific tool not named)
12. Buffer
13. SeekOut
14. Betterleap
15. Juice Box
16. Sense Spark
17. Metaview
18. ReadAI

Transcription

Brad Bialy [00:00:00]:
AI to me is a tool, right? It's another tool in the toolbox. And at the end of the day, we all know what we're trying to achieve. We're trying to put great people to work and great opportunities. We have some sort of goal or a north star. We know our number, we know what we're trying to hit. AI is a tool to get us there. It's not the end all, be all in my mind. And you know, when I think about pitfalls or anything like that, it's people who become too dependent on something, right? You're so hyper focused on one avenue that you forget about all the other things that got you here.

Kortney Harmon [00:00:28]:
Hi, I'm Kortney Harmon, director of industry relations at Crelate. Over the past decade, I've trained thousands of frontline recruiters and I've worked with hundreds of business owners and executives to help their firms and agencies grow. This is the full desk experience, a crelate original podcast where we will be talking about growth blockers across your people, processes and technologies. Welcome to another episode of the full desk experience. Good afternoon and welcome to the full Desk Experience live workshop. I'm your host, Kortney Harmon and I am joined by three of the best people in the industry today. I want you to get ready for an insightful and forward looking discussion on one of the hottest topics in staffing and recruiting, the rise of AI and its transformative potential. So joining us today are three true influencers and thought leaders in our industry.

Kortney Harmon [00:01:28]:
First up we have Tom Erb. Tom is a staffing veteran with over 25 years of experience. Nationally renowned speaker, author. Tom's strategic mindset and workforce expertise really is going to provide invaluable perspective on how AI can impact and optimize some workflows. Tom, I could write a novel on your background. Oh wait, you actually wrote a novel. Winning the staffing sales game. Tell our listeners a little bit more about you and talent resources.

Kortney Harmon [00:01:55]:
What else I missed?

Tom Erb [00:01:56]:
Well, the first thing I realized is that I'm going to get on Amazon right after this and buy a boom mic because I feel horribly out of place. I was even thinking it just maybe holding this like this just so I would fit in. But thanks for having me. Yeah, yeah. Been consulting and training with the staffing and recruiting industry for the last 14 years and prior to that was with the couple of the big staffing companies for a total of 16 years. So this is my 30th year, so I love it.

Kortney Harmon [00:02:24]:
And what an amazing experience and background you have. So love your books. Ben and I were actually talking about your books prior to you joining. So next up we have Benjamin Menna. He brings Ben, I think, correct me if I'm wrong, 15 years of experience in building elite data science cybersecurity teams. Your insight on attracting top technical talent is going to shed light on AI. And also, you're the podcast host of the elite recruiter. What else did I miss? Ben, tell our audience a little bit more about you and what you do.

Benjamin Mena [00:02:54]:
I think you did a good job covering it. And before I say anything, make sure to give an awesome rating to the full desk experience. So make sure you do that on Spotify and Apple podcasts and all those places. Mostly work in the Govcon space. We primarily work with a lot of government contractors, help them sometimes win the work and then we come behind the scenes and fill the work. So mostly on the technical skill sets, like I said, you know, cybersecurity, data science, the tough stuff that the government struggles finding. And then about two and a half, three years ago, started the elite recruiter podcast. What it is is just stories from our industry veterans sharing how they're winning.

Benjamin Mena [00:03:28]:
So if you want to check it out, I have fun just sharing stories and that's all I do there.

Kortney Harmon [00:03:32]:
I love it.

Kortney Harmon [00:03:33]:
I think it's amazing. And all of your conversations, I can't wait to hear your twist on the industry and kind of what you're seeing from your perspective as well. So last but not least, saving the best for last, I told him earlier. Rounding out our panel is Brad Bailey, the forward thinking director of digital marketing at Haley Marketing. Wow, what a tongue twister with a track record of digital marketing success. Brad, I'm sure you're going to offer a unique take on AI, also the podcast host of Secrets of staffing success. Brad, what did I miss? You do a lot.

Kortney Harmon [00:04:05]:
I do, but I have a good.

Brad Bialy [00:04:07]:
Time doing it right. So director of digital over here at Haley, which means I get to talk to our clients and prospects about how to use digital marketing to drive sales leads and drive application submittals on the secrets of staffing success. I host two shows, so insights. We talk about digital marketing and what's working in digital and recruitment marketing. And then on our new show, take the stage, we talk to industry consultants and bring conference caliber speakers to the podcast to talk about what they're saying and what they're doing at conferences directly in your ears. So we try to do that every other week as well.

Kortney Harmon [00:04:34]:
So excited to be here, Kortney. I love it.

Kortney Harmon [00:04:37]:
Thank you all for taking the time out of your busy day to join me. I am so excited. Together, this power trio here is going to uncover and explore some biggest opportunities and potential pitfalls in implementing AI through our lifecycle recruiting. So get ready to learn how staffing leaders can future proof their success and their processes gain competitive edge and really talk about this topic of artificial intelligence that's already rapidly evolving. So Jens, thanks so much for joining us today. I'm going to start with you, Brad, since I saved you for last, we're going to start with you first. When we talk about AI, there's a lot of people that they think initially, like did I miss the bus? Where should I implement? So talk to me about what do you think some of the biggest reasons staffing and recruiting offices need to start to get this AI concept into their workflows, into their processes today?

Kortney Harmon [00:05:27]:
Yeah.

Brad Bialy [00:05:27]:
So I think it's even bigger than staffing and recruiting. We need AI because we have busy days, we have busy calendars, we have busy work life harmony that we're trying to figure out. We have a, B, C and D level tasks that we're trying to accomplish. AI to me is that executive assistant that lives directly in your laptop or on your smartphone. Friends, there are hundreds of things that you do throughout the day that you don't want to be doing. AI to me is where you start to offload some of those tasks. When I think about AI and why staffing and recruiting, we need to think about AI at least. One, you haven't missed the boat.

Brad Bialy [00:06:03]:
You absolutely haven't missed the boat. And two, it opens you up to doing what you actually like to do. If you think about your day and you think about the tasks that you're doing throughout the day that are repetitive or mundane, or you're thinking about the why am I doing this again? Or why are we doing it this way? That's a good time to think about, well, how can AI help me with this? In starting to think about how you can start to integrate AI into your workflow?

Kortney Harmon [00:06:24]:
Yeah.

Kortney Harmon [00:06:24]:
Tom, you are coaching some of the biggest offices here. And what are some of the things that they need to think about whenever they're implementing into these workflows and what their processes are or what are the challenges that you're seeing as you're talking.

Kortney Harmon [00:06:35]:
To offices about AI?

Tom Erb [00:06:36]:
First, I would add to what Brad is saying and just comment that sometimes the things that you like doing are the things that you shouldn't be doing too, right?

Kortney Harmon [00:06:46]:
Yeah.

Tom Erb [00:06:47]:
So it's not all about AI doing the stuff you don't like. Sometimes the stuff that you don't like is the most important stuff. And the stuff that you do like that you tend to a lot of times can be more administrative. That's the kind of stuff that actually AI can help you take on and allow you to scale. And what we really have to be looking at is where's the value add? And that's where we're going to be able to be more productive. And if we can get AI to take on some of that stuff that really doesn't need to be done by a highly skilled professional, then that's going to allow us to scale those highly skilled professionals to be more and more and more productive. So the thing I would say with AI, first of all, I feel like there is AI burnout already. And as much as there's interest and people are dialing into this, listening into this, there's just as many people that are going, oh, my God, another one about AI.

Tom Erb [00:07:44]:
And the problem is that I think there's a disconnect between what AI is, and I think most people understand what AI is, but then what can it actually do for us in practical terms within our lives and in our businesses? So the reality of it is we're all using AI anyways. AI is in everything. Some of it is AI. Some of it they just call AI. So there's varying levels to it. But the first thing that I would recommend doing is just look for one or two things that aren't really adding value, that are maybe repetitive tasks, that are manual tasks that something else can do. And can it be done by AI and then do some research on it, start small and really just start to get used to it. Because I found with my own use of AI, it started out very small.

Tom Erb [00:08:39]:
And then as I started to see some of the value of it, then I kept building on it. I kept doing more and more. And I'm using AI tools of all different kinds, some more sophisticated than others. All day long, every day. It's just, you got to jump in and just start to do it. Don't resist it. It's not a fad, so don't resist it.

Kortney Harmon [00:08:59]:
I don't think it's going away. We heard last year at staffing World, instead of artificial intelligence, it was like ambient intelligence. It's around us all the time. It's going to be here. So I think you sum that up very nicely.

Tom Erb [00:09:10]:
And I just read just this morning that European Union and the US are now putting more resources into how do they handle AI, because they fear that the second wave of AI, which is coming, is going to be so much stronger than the current wave that we have seen with chat GPT and Gemini and all that. The next wave is what really is going to be impactful. So we want to be up to speed on what you have going now. That way you can leverage that, but scary to them. We can look at the leverage.

Kortney Harmon [00:09:44]:
No, that makes complete sense.

Kortney Harmon [00:09:46]:
Tom, do you have any other insights? You mentioned that you were using AI. Now can you give me some tools that you might be using in your back pocket? Because I know that's what people want to hear. They want to hear what other people are using. For insights, can you share any, what.

Kortney Harmon [00:09:57]:
Might be your favorite?

Tom Erb [00:09:59]:
Yeah, I mean, there's a bunch depending on what you're looking at. Just a simple one. I use fireflies is my note taking app, and it's been huge, and there's all sorts of different note taking apps that have AI. Zoom has AI embedded in it now and I leverage it all the time. I mean, I think back nine months ago when I wasn't using it, I go, geez, how did I exist? So for $15 a month, it has become a great resource for me, obviously, chat, GPT, Google Gemini, using those for different things, as simple as somebody doesn't have a resume, that's very good. So you get their permission first because you're going to be throwing it into one of these AI tools, but then put it in there, have it spit out a better resume, job postings, things like that, and also play around with some of these different ones, like Copilot and Gemini and chat GPT, because they do have different personalities to them as well. And what we found is that they'll spit out different job postings and with different types of attitudes. I mean, those are just a couple.

Tom Erb [00:11:00]:
There's tons of them. They're in everything.

Kortney Harmon [00:11:02]:
Yes, I love that, Tom. I feel like sometimes I tell Katie all the time. I'm like, I feel like I'm cheating on Claude because I'm going to Gemini or vice versa, because each of them act differently every single day, too. One of them likes me one day and one of them doesn't. Benjamin, let's talk beyond sourcing and screening. What are some other steps of the recruiting processes that you see AI possibly disrupting or augmenting human efforts?

Kortney Harmon [00:11:28]:
Any thoughts behind that?

Benjamin Mena [00:11:30]:
So I think right now some of the biggest AI tools is for sourcing screening, like the front end stuff that recruiters have to do, whether on the sales side or the candidate side. So definitely make sure you take advantage of those and I'll share, kind of like my tech stack later. But you know, having a recruiting business requires a ton of work behind the scenes and there are many search parameters, whether you're a small shop or a large shop, where there's like everything that you have to do for marketing, everything that you have to do for business stuff. Like there's just so many things that you have to heavy lift that I believe artificial intelligence can make it. So that way you get to focus back on the money making part of the process. So I think that's where the biggest things that AI is going to, like you said, Kortney, we're in the first phase of AI. The second phase is going to be really what's chasing the enterprise back in things. And that's where we're going to see the biggest benefit in the workflows.

Benjamin Mena [00:12:19]:
I don't have any like super good examples yet. I'm hoping to see some too. But I think it's going to be everything from automatic marketing based on the conversations you're having, based on what's picked up from Firefly and all those other places. You're also going to see some automation when it comes to your finances, like the backend, whether you're working with contractors, all that stuff. Like you can literally just turn it down to like. Instead of like having an entire finance team, you now have a person part time per week with multiple AI programs working with through your finances.

Kortney Harmon [00:12:50]:
It definitely is interesting. Brad, do you have any thoughts? Both Tom and Ben have mentioned the idea of the next wave of AI. Yeah, I'm throwing a wrench out there, but any idea like what that next wave could be? Or do you have any insights on like the sourcing screening with you guys being in marketing, what might play into with AI here?

Brad Bialy [00:13:08]:
So I don't have any inside information, but I mean, for me the next wave is just better, faster, stronger, better solutions, better answers, better user friendly. I almost said user ability, that's not a word. But ux and ui, right? Making sure that you actually use it to your advantage. Some of the tools, I mean, you could download them now are clunky, right? You know what they're trying to do, but they're not built for speed yet. That's the first wave in my opinion. Now that we know, okay, this tool can do x wave two is okay, well, how do we make it better, faster, stronger? You had a second part of the question of sort of what am I seeing in recruiting and screening and sourcing? For me, it really comes down to how do you. And Tom, I think you articulated it well. How do you get rid of the things that you don't want to do, but also the things that you do like to do that aren't making you money.

Kortney Harmon [00:13:50]:
Right.

Brad Bialy [00:13:50]:
And I think, Ben, you alluded to that as well. For me, it's just offloading those tasks. Right. We all have finite time and we're all trying to do too much in our days. AI to me is that executive assistant who I can punt whatever task that I don't feel is worth my time to still get it done and keep it moving. And that's where I'm seeing a ton.

Kortney Harmon [00:14:10]:
Of success right now. I love it.

Kortney Harmon [00:14:12]:
Tom, I'm going to come back to you. Are you seeing any bottlenecks or inefficiencies with workflows when it comes to AI that maybe AI could potentially help streamline?

Tom Erb [00:14:21]:
So as far as AI streamlining, a more of a manual type process?

Kortney Harmon [00:14:27]:
Yeah.

Kortney Harmon [00:14:27]:
Or you mentioned that it could be doing stuff that maybe you do like to do, but it may be in the recruiting workflows that bottlenecks within an organization to help it move faster. Brad talked about better, faster, stronger. Is there any particular workflows or areas that people really need to focus on implementing this AI? Make those bottlenecks dissipate?

Tom Erb [00:14:48]:
Yeah. If I had to pick one that I think is the biggest bottleneck, it is speed to applicant. When we have people that apply to jobs, I talk to companies all the time. I go, okay, well, how long do you have from the time that somebody applies to your job to the time when they're not available anymore? And the most common responses I get are anywhere from an hour to 24 hours. And then my next question is, okay, so in your current process, how fast do you get to them? And the most common response is, oh, anywhere from 24 to 72 hours. And I go, well, hold on a second. You just said they're only available an hour to 24 hours and now you're not getting to them for two or three days, sometimes a week. And it's always an issue whether or not you have dozens of people that are applying or you have hundreds of people applying.

Tom Erb [00:15:40]:
And the more people that you have applying, the faster you need to get through it. So to use some sort of an AI screening, whether that is through AI, voice chat AI, we're seeing other types of chat AI, we're seeing streamlining interviews, setting up pre screenings, all sorts of things where instead of it taking 72 hours to get to somebody, we can get to them in seconds or minutes, that's really one of the keys is get to them quick, start to engage them in the process, get them to a point where we can hand it off to a skilled recruiter. And we're going to have a much higher success rate because, of course, we all know here the ones that we lose first are the best ones. They are the ones with all sorts of choices. And so for us to go 72 hours, I almost feel like by the time you reach out to them after three days, you're going, why are you still here? It took me three days to get to you. Do you not have any other choices? I mean, you know, it's like, I wouldn't belong to any club that would have me as a member.

Kortney Harmon [00:16:43]:
Yeah.

Benjamin Mena [00:16:44]:
I mean, now you also got the candidates using artificial intelligence to multiply what they're doing, too.

Tom Erb [00:16:48]:
Yeah, well, and that's the other thing we've seen, too. I just saw an article yesterday. Somebody was talking about applying for a job. They couldn't get anybody to respond to them. They started using AI to respond to each of the jobs, to basically tailor it to that job. And she had almost 100% response rate once she started using AI to actually respond.

Kortney Harmon [00:17:09]:
Yeah.

Benjamin Mena [00:17:09]:
There's a website called earn better, and it actually tailors your resume per job and automatically applies for you.

Kortney Harmon [00:17:15]:
Wow, it's crazy.

Benjamin Mena [00:17:16]:
It also makes it tougher on the recruiters to go through. Like, you know, if you get a plethora of applications and you don't want to utilize AI fully in the screening process, but you definitely need AI to help with the screening, too.

Kortney Harmon [00:17:27]:
It's interesting.

Kortney Harmon [00:17:28]:
It's interesting to think that we're using AI on our side, but you don't always look at the flip side of that coin to say they're using AI to help their process as well, because it's going to be embedded on both sides. Ben, what was the name of that?

Kortney Harmon [00:17:39]:
That site is called? Earn better.

Kortney Harmon [00:17:41]:
Earn better.

Tom Erb [00:17:42]:
Pretty soon it's going to be, have your AI call my AI. Pretty much let them figure out if we're good.

Benjamin Mena [00:17:49]:
I've played with tons of different bots in AI software. I'm waiting for the company that's going to come and just say, we'll do the sourcing, we'll do the screening, we'll do the candidate BD. There's a lot of companies that are saying it right now. I've been testing them. I think they all have a long way to go.

Kortney Harmon [00:18:03]:
But kind of just going into the.

Benjamin Mena [00:18:04]:
Conversation, there are so many things that we could do as a recruiter to multiply ourselves or as a company owner, where instead of what it took 20 recruiters to do, you can now have a team of five to eight recruiters with the same production level of a team of 20.

Tom Erb [00:18:17]:
If you do it right.

Kortney Harmon [00:18:18]:
If you do it right.

Benjamin Mena [00:18:18]:
Yeah, yeah, yeah.

Tom Erb [00:18:20]:
And that's the key, and that's the competitive advantage that we can have right now. If we really put some focus on it and understand that we are in the first iteration of this technology that's going to improve by leaps and bounds. So to get in on it early, we've got a window, I think, of two to four years for the people that now are leveraging AI already to scale their team. It's like looking back at when texting platforms first came out. The ones that jumped on at first were able to scale and then that evolved into candidate engagement platforms. The ones that jumped on that early were able to scale, and then everybody caught up to them, but it took a few years to catch up to them.

Kortney Harmon [00:19:02]:
And that's where we are right now.

Tom Erb [00:19:03]:
With the AI tools.

Kortney Harmon [00:19:04]:
Absolutely, Brad.

Kortney Harmon [00:19:05]:
As we think of all these tools, we think of the shiny object. Right. How can organizations ensure AI doesn't really create new silos or friction points into their end to end recruiting process? Because it's something that they need to think of. How do we make sure it doesn't get lost? Because there's a lot seems to be that could get lost in translation.

Kortney Harmon [00:19:24]:
Any thoughts on that?

Brad Bialy [00:19:25]:
I've seen it firsthanded. Haley, you got to talk to each other, right. And if you're exploring a new tool, Ben's saying that he's going through all these new tools and new, we'll call them shiny objects because that's what you call them, Kortney, and you're going through, okay, I'm going to try all these new things. If you go to there's an AI for that. That's sort of an aggregator, a search engine of AI tools. So you go to there's an AI for that, and you type in video editing or video clips, it will give you all of the AI tools that will chop your video up or your content, whatever, and it will give you all of the AI tools. Now, it's great to try new things, right? I am the biggest proponent for trying new things, but if your team isn't talking amongst each other and saying, listen, this is working for me, this isn't working for me, well, then you're instinctively going to create those silos. And if you have recruiters that are doing really well because they're using a certain tool, then they need to have some sort of lunch and learn, or they need to tell others about it, or you need to empower your team to share what they're seeing and what they're hearing and what they're feeling, because otherwise you're inherently going to have those silos.

Brad Bialy [00:20:18]:
It's just going to happen. And, I mean, you might have some team members who say, listen, this is working for me, and I don't really want to tell everyone what's working for me because it's working for me. But you need to create that culture where you want to share what's working and more importantly, you want to share what's not working. I've wasted a lot of time on AI tools and trying to find what works for me, and that's where I think the biggest bottleneck is. I know you asked that question a little while ago, but the biggest bottleneck is trying to chase after an AI tool. It's trying to find or force fit an AI tool. If you're not talking amongst your team and you're not having that communication, then you're just going to have multiple people falling down the same rabbit hole, which is going to waste even more time.

Kortney Harmon [00:20:52]:
Zachary.

Kortney Harmon [00:20:52]:
Okay, so do you think there should be like one person that's kind of leading that charge of all the AI?

Kortney Harmon [00:20:58]:
What are your thoughts?

Brad Bialy [00:20:59]:
I think you should have one person who sort of oversees that people are reporting to that are saying, listen, here's what I'm trying, or here's what I've tested the last week or so and have team huddles or have team bi weekly meetings to say, listen, here's what I've tested. Ben, what did you try the last week? Tom, what did you try the last week? What's working? What's not? I don't think you need a chief of AI to say, listen, you're going to test this and you're going to test that, but you need to have somebody that's responsible for, okay, how are we using this? What are we using it for? Is it working for you? Is it not working for you? I do think that should fall into a team huddle or a team meeting every other week at least.

Benjamin Mena [00:21:33]:
Well, a lot of teams are somebody that's always, like, interested in AI, like empower that person on the team and give them the wiggle room to test different things.

Tom Erb [00:21:42]:
Yeah, I think most companies, depending on the size of the company, should have some sort of technology committee in general, that is so many times what I hear is, well, we tried it and it didn't work. Well, did you try it the right way because other companies are using it successfully? That company is successfully in business because people are using the product the way it should be, whether it's AI or any kind of technology, candidate engagement or texting or mobile or all the different things that we have available to us. One of the biggest mistakes that I see companies make across the board and over and over again is that they bring in a new technology, but they don't integrate it into their process. They're still running their staffing company like it's 1995, but yet I got this technology over here, right? And then everybody goes, well, yeah, but that technology just creates extra work for me. And so it needs to be integrated into it. It can't just be sitting on top or to the side or whatever. It needs to be woven through and really help people scale. And that's an issue across all types of technology.

Tom Erb [00:22:48]:
So to me, I also would not leave it up to individuals within the company. Now we want individuals that run across their own AI technology to please share it and try new things out. But don't say, hey, here it is, it's for you. There needs to be structured, process needs to be universally implemented. And the more that it can be implemented for people to use it seamlessly as opposed to here it is, learn how to use it, the better the adoption is going to be. But that's the same with any kind of technology. It's the same with your ats, right?

Kortney Harmon [00:23:21]:
I mean, at the end of the.

Benjamin Mena [00:23:22]:
Day, the goal is to try to make sure you're having more conversations, more authentic conversations with the people that you're going to be working with, whether your client side or your candidate side. And just the tools out there at the moment. There are some that save time, there are other ones that are shiny object syndrome, waste a lot more time.

Kortney Harmon [00:23:38]:
Yeah, yeah. All right, Ben, I'm going to stick with you. You kind of just talked about it a smidge, but I want you to elaborate. What are some potential risks or maybe some unintended consequences that could arise from maybe the over reliance on AI whenever it comes to recruiting workflows or sales workflows.

Kortney Harmon [00:23:54]:
Any thoughts? I mean, I think one of the.

Benjamin Mena [00:23:56]:
Biggest ones is taking the human out of recruiting. We are a human business, we are a relationship business. And using AI can really just like you, automate too much, you've automating your job away. Secondly, I think one of the biggest things is a recruiter getting lazy or a manager getting lazy, like the reliance on all these tools to work behind the scenes to do all this stuff to magically make you more money. At the end of the day, like, the second one of those tools works, it could work for you right now, but the second everybody starts working on it, or the way that Google just changed something, like the power of a tool can disappear. So you didn't make sure that you have the foundational structural knowledge. The foundation in recruiting has to be strong no matter what you're doing. So I see those are like some of the biggest things.

Benjamin Mena [00:24:39]:
And you can also just use the AI to like, it runs through pisses off companies, too. People are now understanding, like, they can catch a badly written AI message. So you need to make sure your prompts are strong. You need to make sure that personalization is strong. Like, if you're using AI video tools, you got to make sure it's like an actual real, instead of that really chopping people's names up. So there's like ways that you can over AI that will actually make it worse and the clients won't even want to ever use you or the candidates don't even want to ever talk with you. So those, I'd say the biggest things and just the random message to the wrong person too, which, you know, we all learned in our early days in drip marketing. AI makes it even worse.

Kortney Harmon [00:25:15]:
Yep. Yeah. Anyone else?

Kortney Harmon [00:25:17]:
Brad, any thoughts on potential risks or consequences that we might be facing?

Brad Bialy [00:25:22]:
Getting lazy is a good one. I would support that one that Ben shared. I think the other risk is having too much dependency on anything is a bad thing. And that's from social media to even just what you're doing day to day as a recruiter. Being too siloed into one tactic is never a good thing. If that silo goes away, you're in trouble. So AI to me is a tool. It's another tool in the toolbox.

Brad Bialy [00:25:46]:
And at the end of the day, we all know what we're trying to achieve. We're trying to put great people to work and great opportunities. We have some sort of goal or a north star. We know our number, we know what we're trying to hit. AI is a tool to get us there. It's not the end all, be all in my mind. And, you know, when I think about pitfalls or anything like that, it's people who become too dependent on something, right. You're so hyper focused on one avenue that you forget about all the other things that got you here.

Benjamin Mena [00:26:11]:
A perfect example is email marketing. Like it's been a goldmine for years. I know people that were literally like one or two person shops sending out 10,000 emails a day. The way Google just changed everything and Yahoo just changed everything. You are now like in a black box if you're sending that many messages on a daily basis. Yes, it worked. Yes, it brought in business, but technology changes fast.

Kortney Harmon [00:26:32]:
Absolutely.

Tom Erb [00:26:33]:
Kortney, I would say that for me, the biggest risk is not doing it. For every company that I see out there that overdoes technology, there are 100 that under do it, maybe a thousand. There are so many companies out there that will what, f themselves into complete inaction. And what I hear all the time is that, well, if we do this technology, we're going to lose the human element. Ben mentioned that that rarely happens. It rarely goes because nobody adopts it. But what does happen an awful lot of times is that I'll have a company that will come to the conclusion that it would take away the personal elements so they don't even do it. And when we really think about it, if you're doing it the right way, yes, you run the risk of making it impersonal and making it all, talking to an AI tool and all that, but that's not the right way to implement it anyways.

Tom Erb [00:27:35]:
The right way to implement it is to do it in ways that scale is to do it in ways that bring that candidate or that employee or that prospect or that client back to us to have live conversations that weren't going to happen anyways in a lot of cases. And we see that a lot of times when we are looking at a database of 100,000 people that's just sitting there and we're going, well, you know, but if we send them a bunch of automated messages, then we won't have live conversations. Well, we're not having live conversations with them anyways, so let's get some interaction going and bring them back. Because if we can get qualified people, we can pre qualify them to a certain point and then get them on the calendar to have a 15 minutes conversation with the recruiter. Recruiters going to like that for the most part, right. And if it can be valuable conversations, then that works. So my biggest risk is just coming up with reasons not to do it. That's where I see the biggest risk.

Benjamin Mena [00:28:36]:
There's like one more risk that I know somebody just mentioned. It was something I was thinking about earlier. It's just like the built in bias that AI has, which it's a real thing. We've seen it time and time again. But the one thing I've come back to multiple times is what is the built in bias that humans already have that you're looking at your data, how long does it take you to look at how many resumes or how many LinkedIn profiles or how many different companies? When you can use an AI tool that does have flaws, it can just speed things up for you.

Tom Erb [00:29:03]:
Yeah, I think that's a great point. I was just having a conversation with a client this morning about that, about being careful about the biases that are still in this first generation because they have all sorts of data that shows, because developers are so heavily male, that there has been a male bias, there has been a bias with different ethnicities. We've seen all sorts of different things like that. And we obviously are in a business that has a lot of employment law and is trying to keep the biases out of these decisions as much as possible. So we need to be aware of those if they're part of our selection process and need to be able to defend those. If somebody comes back and goes, hey, listen, you had an AI chatbot or something like that that was talking to me and I didn't get selected, and it was because of some illegal bias. You need to know that and be able to adjust for that and defend it.

Benjamin Mena [00:29:56]:
A perfect example of that is a few years ago, Amazon actually had an AI processing doing AI hiring. I think it was blocking out women out of the process.

Kortney Harmon [00:30:05]:
They had to scrap it.

Benjamin Mena [00:30:06]:
But there are flaws within the AI, but at the same time, all the algorithms are just getting better and better each day.

Kortney Harmon [00:30:13]:
It seems to be at this point. All right, Ben, Brad, Tom, as you think of other ones, Ben, I know you mentioned that you talk about that a little bit more. Talk to me about what are some of the AI tools that you're using today that are forefront of your mind are audience wants to know?

Benjamin Mena [00:30:29]:
So some of the ones that I'm playing around with are at least on the sourcing side of the house. It's seek out and I use them at the government space because they actually use some AI matching on the back end to figure out if people have security clearances or not or might have a security clearance. Perfect example if there's an engineer working in Fort Meade, Maryland, but they have like almost no profile. But if you're working at Fort Meade, at a company called Boeing or Lockheed Martin, there's a high profile. You have a high probability. You have a full scope poly, a TSSI and a full scope poly so that's one. I'm also a huge fan of better leap, too. Betterleap is another sourcing platform that I've been playing with.

Benjamin Mena [00:31:02]:
You can actually just drop in the JD. It'll start using AI to actually source potential candidates and also personalize those candidates too. So send personalized messages based on the data that they're able to find. And they actually just flipped up to what I call the third level of AI and recruiting, where natural language search. So you can type in like, I'm looking for an engineer near Google's headquarters and it knows where Google's headquarters is and can start pulling apart engineers in that area based on. I kind of like what you're talking about. Juice box is another fun one. When somebody was talking about market mapping, it actually does a good job also integrating crunch based data.

Benjamin Mena [00:31:38]:
So if you're looking at like those companies that series A, series B, and companies working there, so that's a good one. Sense Spark is another one of my toolkit. You can actually send personalized videos at scale. So you can actually make like one video and it will actually change the name in the conversation. You drop that into one of your emails. You got to be careful with that. Like, it's getting better and better. But the biggest thing is trying to find ways to personalize that scale.

Benjamin Mena [00:32:01]:
Metaview is another one. It's kind of like Firefly, but it's actually made for recruiters. So it actually has a built in behind the scenes prompts. Those are some of the bigger ones. Claude is one of my favorites when it comes to content writing. I'm an absolutely suck at writing. So I kind of put my notes together. Cod cleans it up.

Benjamin Mena [00:32:17]:
Of course, chat GPT. And I think a lot of recruiters now that I've been speaking with are actually building out their own GPTs in chat GPT. Then they're actually using that for picking up new clients, you know, giving to candidates and that kind of stuff. So that's my little AI toolkit.

Kortney Harmon [00:32:30]:
I love it.

Kortney Harmon [00:32:31]:
Brad, do you have any tools to add into that?

Brad Bialy [00:32:33]:
Yeah, mine is not as robust. But I will tell you what I use on a daily basis. So on a daily basis, I am using read AI in every single meeting that I go to so that I can focus on the meeting and not have to take notes. One, I'm a terrible note taker as it is. And two, if I'm focused on my notes, I'm not focused on you. And I would rather have a good 15 to 30 minutes conversation. Circle back to the notes afterwards if I need to, gives me the summary. You know, Zoom has notes in there as well, but I like read AI personally.

Brad Bialy [00:32:59]:
The second isn't really built on. I mean, maybe it is a form of AI, but Microsoft bookings or calendly I cannot live without. There is nothing more outrageous than trying to schedule a meeting with somebody and going back and forth in six emails trying to find the right time. Here's my link. Pick a time that works best for you, just click the time and you're booked and that's it. And if you're trying to schedule meetings with candidates or prospects or whatever, it might be internal team members, if you're going back and forth to try to find the right time for a meeting that doesn't need to be done anymore. I live in chat GPT and I do pay the dollar 20 a month for the premium version of chat GPT because it opens it up to so much more than just the base level GPT. I live and do everything in there personally.

Brad Bialy [00:33:39]:
And then as a podcast host, content creator, I use two tools. One is Opus and one is video, to turn every episode into clips and get that off of our creative team. Now, we do have individuals who oversee it, make sure they're polished before they go to post production and actually go out the door. We do have a human eye spot check everything, but the initial clip is all done through AI. And those are four that I use pretty much every single day.

Kortney Harmon [00:34:06]:
I love it.

Benjamin Mena [00:34:07]:
Brad and Kortney have like teams for their podcasts. I am the team. So I live off like I live off podcast AI tools so I can focus on recruiting during the week.

Brad Bialy [00:34:16]:
Oh, you're exactly right though. So, you know, you think about what it used to be to cut a video, right? So let's say we have this hour long webinar or hour long conversation and Kortney and her team want to cut that video. You have to go back, watch it, find the timestamp, cut it, brand the intro brand, the outro, and burn in the open captions that they show up on LinkedIn. Now you upload that to Opus and it's done in 15 minutes and you have 14 or 20 different clips that you can use. It's perfect.

Kortney Harmon [00:34:42]:
I love it.

Kortney Harmon [00:34:42]:
The only thing that you guys didn't say I used majority of all the things that you say, I use a note taker. I also use buffer because I have to post on social. And I will tell you, I stink at remembering. So if I don't go schedule the time to go post to a social platform. It will not get done, just like my calendly link and all of the other things. So I love all those things. Katie, I have a feeling if we don't stop because I see the chat going crazy. If I don't stop, you might yell at me.

Kortney Harmon [00:35:11]:
So I'm going to be quiet for a minute.

Katie Jones [00:35:12]:
I'll kick you under the table from Nevada. So yeah, we have tons of questions. This conversation has been awesome and incredible.

Kortney Harmon [00:35:21]:
Don't worry guys.

Katie Jones [00:35:22]:
Those of you who are listening, both live here and on the podcast, we will drop every link to every AI tool, to everything that we have talked about today in the show notes, and we will make sure that nothing gets left behind. Several examples of how to use AI for marketing, mapping and research. I think you guys talked about that, but there's a lot of people who want to know like what processes are best to use AI. Can you give tangible examples of what a workflow might look like with AI? Those kinds of questions.

Benjamin Mena [00:35:50]:
Do you mind if I jump in first? Because I don't have a marketing team and I know some of you guys have awesome marketing teams. So I actually use Opus pro for video clips. I do podcast interviews and if you do any interview with an industry leader that you're doing with our zoom, you can drop it in there. I actually pull the transcripts out and use an AI tool called cast magic. So it actually rips apart any interview that I have and creates a bunch of highlights. It can also like I can pull those highlights into canva. So I suck at making anything before canva. I don't know how people marketing teams did that magic, but now I literally in my hands have canva that I can really pull information from and drop that in.

Benjamin Mena [00:36:27]:
And that's like his marketing superpower. I'll let the pros go. Now, I was going to go somewhere.

Brad Bialy [00:36:32]:
Completely different with that, and I was actually going to talk about prospecting. A concrete example, I was working with a recruiter who specializes in placing individuals in shipyards, right? So we were talking the other day and he said, Brad, we're prospecting. We don't know exactly what to do. Wanted to put together a marketing plan. So I went to chat GPT because I don't know much about shipyards in the south, being in Buffalo, New York. So my first thought was, okay, well, let's learn what the five leading shipyards are in these five states. Chat GPT, spit those out for me.

Kortney Harmon [00:36:57]:
Great.

Brad Bialy [00:36:57]:
Now let's think about what purchasing decision makers, HR, individuals who are in a purchasing seat care about in those shipyards? What are their pain points? What keeps them up at night? What are their challenges? What are their biggest struggles? Great, now I know those. Then I'm dropping in this prospector clients value proposition. Okay, well, how does this value proposition and how does what we do, how does our mission align with these challenges? So now I have messaging that correlates specifically with the pain points of purchasing managers and decision makers in shipyards in Louisiana. Okay, great. Now I know what my go to market messaging looks like. Okay, now let's take that one step further. I'm a big fan of Alex Formosi. In his book hundred million dollar offers.

Brad Bialy [00:37:37]:
If you haven't read it, I would suggest that I drop that here. So I said, okay, following the framework that Alex Ramozi presents in $100 million offers, what are some offers that I might present knowing now that you know my value proposition, who my target audience is in Louisiana, what do they really care about? So now I have my lead magnet. And then you get creative and you think about from a marketing standpoint, okay, how do we get people to the lead magnet? And you could ask those questions as well from a concrete what can we do with chat GPT? And sorry, I don't have the chat window open to know exactly who asked the question, or I'd address you by name. It's getting into the head of the decision maker or the buyer or anybody that you are trying to reach in, knowing as much as you can about them and using as an exploratory research tool. I will say I don't really use Google search anymore. I yo to chat GPT for most of my questions because I feel like I can open up and get a little bit more from that. So from a research standpoint, as I'm coming up with marketing strategy, I'm using it daily to think about, okay, who's my target audience and how can I most importantly get in front of them with my messaging?

Tom Erb [00:38:37]:
Well, and on the flip side of that, move it over to the candidate marketing side, but also using chat GPT or Gemini or one of those others, is, if I'm trying to identify what are the selling points, we do this like in travel nursing, for instance, where we've got an opportunity that's in a market that people maybe aren't that familiar with, or we've got a company that we've got a healthcare organization that's out in Bend, Oregon, or wherever. We can actually go into chat GPT and go, what are the selling points of that market? What are the selling points of this organization and it will come back. And a lot of times it has a lot of great detail that you wouldn't have even gotten from the client. And then you can sell it to your candidates, you can incorporate it into the job postings. You do all that. I'm also a huge fan of taking a job posting, which most of our job postings are very important, employer centric, just sound like a job description boring and put it into chat, GPT or Gemini and say, make this more appealing to candidates. And one of the things I've done is take it a step further and say make it purpose driven. Because so many candidates are looking for purpose.

Tom Erb [00:39:53]:
They're looking for a reason to take this position over others. So those work out really well. Another thing that I've done is, you know, I write the bimonthly article for staffing success magazines recruiting today and I do not have it right. It I write my article just I want to say that I don't want anybody going, Tom uses chat GBT for the article. That is not true. But what I will do is I will say, give me ten ideas of something to write about and I'll just see if anything spurs ideas. I keep a running tab of the things I want to talk about, but if I have other ones, it'll just come out with some different things. You can do that for blog postings.

Tom Erb [00:40:33]:
So that's another way from a marketing standpoint. The other thing is that a lot of these automation sales automation tools are starting to incorporate AI into them, which can work really well, especially like Ben was saying, he's not good at writing. A lot of people aren't good at writing. A lot of people struggle to have creative things to say. And so Apollo is a great example. Apollo IO has sequencing in there, but then you can put in yours and then it will come up with an AI recommendations. It'll write the whole thing for you, or you can even, it'll rewrite it. Or if you don't even have stuff, you can put a few bullet points to have it write things for you.

Tom Erb [00:41:13]:
So those are some different things that you can take a look at from the standpoint of marketing. I will also say one other thing. I know we have other questions. Ben talked about canva AI. I was doing a presentation and I was wanting to talk. I wanted to show a picture of a three legged stool. I was making an analogy, which if anybody's watched any of my presentations, I always do an analogy. So I wanted an analogy of a three legged stool.

Tom Erb [00:41:35]:
But I couldn't find one that I like. I went to canva AI and I said, create a picture of a three legged stool. And I gave it some additional prompts. It came back with a bunch of them, for whatever reason, came back with a bunch of four legged stools. I don't know why, but it did come back with a great picture that it generated. It created from scratch of a three legged wooden stool in a living room or something like that. So those are just some of the different things you can do from a marketing standpoint.

Benjamin Mena [00:42:01]:
One more thing, in marketing, the tool that I used to use, but I don't use anymore, mostly because I hated being on LinkedIn, was taplio. So it would create LinkedIn posts based on other successful LinkedIn viral posts, and you could get it all scheduled out. So I used that probably about a year ago. I recommend it for people nowadays, if you really don't want to be on LinkedIn, but you need to show up. It actually does a good job using AI to write good solid LinkedIn posts. If you do a good prompt, prompting is key.

Katie Jones [00:42:30]:
Kortney and I will prompt different AI's with similar prompts that are slightly tweaked and get completely different answers. So.

Kortney Harmon [00:42:39]:
That'S great.

Katie Jones [00:42:40]:
Okay, so another question. You guys kind of touched on it, but I think that it's important to highlight again, does anyone feel that some of the AI capabilities take away too much human connection, especially on the recruiting side? And what are the best ways ways.

Kortney Harmon [00:42:54]:
To balance that out?

Tom Erb [00:42:56]:
Just have your AI have the intent of AI be to drive live communications to bring it back to your recruiters. So it shouldn't replace all of it. It should. It can replace some initial ones, but what it's really trying to do is be faster and initiate conversations that then drive back to the recruiter.

Kortney Harmon [00:43:20]:
I don't think we're at a place.

Benjamin Mena [00:43:21]:
Where Tom's AI can talk to my AI and everything gets figured out to a place that we close the deal. It is all about getting a chance to have those conversations. And now you can smiling and dialing. Yes, cold calling does work, but it's also harder to get a hold of people. So now what AI does is it increases your omni presence in multiple avenues for you to able to have multiple touch points. So that way you can actually have those real life conversations.

Kortney Harmon [00:43:46]:
Nothing to add. Good answers. Awesome.

Katie Jones [00:43:48]:
You guys kind of touched on this a little bit earlier, but you guys kept talking about next wave. How many waves of this AI iteration do you think there will be? What do you guys have any insights or thoughts on upcoming trends to keep an eye on? What might this next wave look like and when do you expect it to start?

Tom Erb [00:44:05]:
I think right now. I was earlier talking to somebody about we're safe from AI taking over the world right now with some of the functionality that we have right now. I equate some of the AI to a really bad administrative assistant that you have to constantly tell what to do and give it better directions and you end up spending a lot of time on it. It's going to keep getting better. It's going to keep getting just to the point where you're just having a conversation and it runs with it and it's going to be able to do multiple things. Whereas still right now a lot of what AI is, is kind of one trick ponies or asking it to do specific things. I want it to be able to go and do ten different things based on a conversation we've had. So that's where I think it's going to continue to go.

Tom Erb [00:44:52]:
I don't think there is going to be a last iteration of it. I think it's like any other technology. It'll constantly be iterative and improving.

Brad Bialy [00:45:00]:
I would agree there. I think it's just something that improves on itself. I think it's almost compounding on the easy button.

Kortney Harmon [00:45:06]:
Right.

Brad Bialy [00:45:06]:
And it's how do I make my day a little bit easier, a little bit more efficient, and then that's just going to grow on itself.

Benjamin Mena [00:45:11]:
Itself.

Brad Bialy [00:45:11]:
Right. So if you find one wave that's working, it's okay. This, what can we do now with this? What can we do now with this data? How can we take this data a step further? It's constantly learning from what you've done in the past to make the future a little bit better.

Benjamin Mena [00:45:22]:
I think we've had like three conditions of AI within recruiting. I think like the next, like one or two or maybe three will have the potential where you can have a small team of billers on your team using tools but still being able to spend time with their family every night.

Kortney Harmon [00:45:41]:
Yep, agree.

Katie Jones [00:45:42]:
I love that too. So I've got two more questions and I think we'll do our best to get both of them. Tanya and Bob, the first one is AI tools are really great, but you can't have them all. What are your favorite free or limited cost AI tools for staffing and recruiting?

Brad Bialy [00:45:58]:
You need to figure out what you're trying to do with it first. Right. So, you know, I could sell you a car, but if you're in the market for a truck because you need to haul lumber. Then I sold you the wrong product and I sold you the wrong vehicle. And Tanya, I think ultimately, you know, we could and maybe, Tom, I don't want to speak for you, but in my seat, I don't know that I can give you the best tool. I give you the best tool for what I'm trying to do in my day and tomorrow. But if you're trying to source, that's different than if you're trying to prospect. And the tool that I would recommend would be very different.

Brad Bialy [00:46:24]:
So I would start with a scratch pad on the side of your desk. And this actually comes from a guest that I had on my show. We had Trisha Tamkin on the show and she said her logic with AI is how can AI help me in insert task here? And if you have that on a sheet of paper next to your desk tomorrow, as you start working your eight hour day or more, whatever it is or less, I'm not going to judge you. Whatever you want to work tomorrow, start thinking through the tasks of how can AI help me in this and then find the tool that supports that challenge.

Tom Erb [00:46:51]:
I would say for free. And really the first thing to start out with is get as much as you can out of chat, GPT, out of Gemini, out of copilot, the different things that are free, get as much, max it out to the point where you go, I think I need to pay for the upgrade. Then now you're starting to get that, then you can start to look for some of the other paid tools that you can scale even more. Free is what free is, but it's a good place to learn before you start to spend a lot of money on AI tools. Brad had great advice about knowing what it is that you actually want to do.

Kortney Harmon [00:47:25]:
First, I'm going to jump in and my thought process and where we live in processes and scaling our organization is really figure out what your processes are first. Figure out where they can be implemented.

Kortney Harmon [00:47:37]:
The people that I'm talking to, they're.

Kortney Harmon [00:47:39]:
Like, they just want the AI tool to make them better, faster, stronger, but they don't even have their personal, their process developed to begin with to know where it should be inserted. So Brad, yes. That scratch pad, but do you have a workflow? Do you have a yes, no, like one of the little charts that the flow charts that show. But you should go through those processes. Start with recruiting, start with sales, go into existing clients, go to new clients, figure out what those processes are to figure out where it can help you first and foremost.

Tom Erb [00:48:08]:
The number one thing that I would say if you do nothing else is every one of your job postings should be awesome because of AI. Throw it into chat GPT and make it awesome. Don't make it a boring job description job posting if you do nothing else.

Kortney Harmon [00:48:23]:
I love that.

Kortney Harmon [00:48:24]:
I like to be able to say like who can this person become? Like paint the picture of who they can become if they would take this job. That's my favorite way to use that.

Katie Jones [00:48:32]:
Bob, I don't think that we're going to have time to get to your questions since we are at time. However, if you drop your email in the chat, I will have somebody follow up with you after the event. I'm going to hop off and let.

Kortney Harmon [00:48:43]:
You guys do your thing.

Kortney Harmon [00:48:45]:
All right, I will make it short and sweet. Thank you gentlemen for being with us today, giving a plethora of information from tools. Ben, you were on a roll like you listed twelve in a row. That was amazing. Tom and Brad, you guys had great insights of where and how and really understanding how these offices and what they should be thinking about because that's what it really comes down to. So I know our listeners got very insightful information and how to be able to take that away, how to use it in their own firms to be successful. So thank you all three of you for joining us. This is definitely no dynamic duo.

Kortney Harmon [00:49:20]:
Terrific trio right here. So thank you all three of you for joining us today.

Brad Bialy [00:49:24]:
Had a great time. Thank you.

Kortney Harmon [00:49:25]:
Absolutely. For our listeners, this podcast will drop next Thursday. Feel free to download, share it with your office, anybody else that you think would gain insights from this. Until next time, have a wonderful afternoon and see you soon. I'm Kortney Harmon with curl eight. Thanks for joining the full desk experience. Please feel free to submit any questions for next session to full full [email protected] or ask us live next session if you enjoyed our show. Be sure to subscribe to our podcast wherever you listen, and sign up to attend future events that happen once a month.
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