Nycole Rosen, Co-Founder of Pedagogue Systems, How AI Is Just a Tool, Not the Full Solution

[00:00:04] [SPEAKER_01] Real quick, before this episode gets started, I have a question for you. How do you scale both your local and your global talent? Do you take on the risk? Do you pay the taxes? Do you actually set up a local entity everywhere your talent is located?

[00:00:20] [SPEAKER_01] Well, I hope you don't, because today's episode is sponsored by Safeguard Global. Safeguard is one of the leading employers record since 2008. Now, there's a reason EORs are the fastest growing segment across Human Cloud, and that's because they are the have your cake and eat it too solution. What do I mean by that? Well, you get the flexibility of a flexible workforce with them owning the risk. Now, enjoy this episode and go reach out to Safeguard.

[00:00:53] [SPEAKER_01] Perfect. All right, Nicole. So for you listeners out there, I'll give you some context. So Nicole was in Shark Tank. There was five, I think, or six companies. And I went, I need to talk with Nicole ASAP. And so we caught up last week or a couple weeks ago, just to do a little prep. And I'm really, really excited for this episode and a couple reasons why. The first one just being like AI, tell us what it is, right? Like you're on the front lines of it. You're seeing it in action.

[00:01:22] [SPEAKER_01] You're seeing all the problems with it and the good things. And then second being from a staffing perspective, you have so much experience. And so you're, you know, we were doing our show notes, right? Like you were an actual CIO in staffing, right? Not like, ah, I took a weekend course. You never know. So deep, deep technical staffing and AI and technical expertise.

[00:01:44] [SPEAKER_01] So I guess, Nicole, you want to start with a little intro on yourself and sort of where are you located, sort of what's your journey been, and then we'll get deeper.

[00:01:54] [SPEAKER_00] Yeah, you bet. So I started in staffing the way most of us do, completely by accident. I was fresh out of school. It was early 2000. And I really didn't know what I wanted to do with my life. I don't know that many of us do at that point. So I was looking through the want ads in the newspaper, as you do in 2000, and we're circling jobs that looked appealing. And one of them was a very entry level clerical position for a local staffing company.

[00:02:20] [SPEAKER_00] And I went in and interviewed for that and learned that they had a part-time position in their office and then the other half of the day for one of their clients. So they went ahead and placed me on both. So I got an early perspective of the staffing industry as an actual temporary employee that worked both for a client and internally. When that position ended, it was temporary for their client. When that ended, they had me come in full time in the office. And the truth is, I never left.

[00:02:49] [SPEAKER_00] I continued to work in staffing, handing out paper applications, walking candidates to what we called the video room, where they would sit in front of a big box TV and I would put a VHS tape in the VCR. And they would watch the safety orientation and fill out their onboarding documents. That dates me. I know that that goes back a ways.

[00:03:13] [SPEAKER_00] But I loved it. I loved seeing how we could help people who were in between jobs or looking to upskill, help them find a good placement for themselves. I moved into a recruiter role where I had the opportunity to not only hand out the paperwork and get people onboarded, but really learn their stories and understand where they were in their career.

[00:03:35] [SPEAKER_00] I remember there was one gentleman that was pretty entry-level looking to support his family, as we all are trying to do. And I placed him in a job that had career growth, an opportunity for him to come in at an entry level, learn some additional skills, get some certifications, and eventually work into a regular full-time job.

[00:03:55] [SPEAKER_00] And when that converted from a temporary position to on the client's payroll, he came into the office with his wife, who had baked me a plate of chocolate chip cookies, and thanked me for that job. And, you know, I did that every day so many times that I hate to say it, you kind of become jaded to the process where it's just another placement that you're making.

[00:04:19] [SPEAKER_00] And that helped remind me of why we do what we do. We are helping people get a job. We are helping them better themselves and support themselves and their families. So I love that story, and I like to remember that that's why we do what we do. It helped me to kind of launch my career further into staffing. So I moved from the recruiter role into more of a regional trainer role.

[00:04:44] [SPEAKER_00] And that happened a little bit less by accident. I really loved the technology that we were using. It was a DOS-based program. I knew those F keys, and I could enter an application in my sleep. And because I was really good at it, when we would hire new people internally, I would become the person that would train them on how to use the system, how to interview candidates. I learned a little bit about employment law and things that you should or shouldn't do.

[00:05:11] [SPEAKER_00] And over the course of a few years, moved into a role where I would train all employees across the Western United States. So I got to travel all over the place and train people. I even got to go in and do kind of a secret shopping job where I would, before a branch knew that I was coming or knew who I was, I would go out to that market, apply for a job, go in and interview and go through the process.

[00:05:34] [SPEAKER_00] And then at the end of that, would let the branch manager know who I am and then sit down with them to go over the company's SOPs and let them know how they did. And that was really fun to help them understand ways that we can improve our processes. Yeah, so lots of interesting things. And then I gravitated toward the technology even more. And we decided as a company to replace our DOS-based program.

[00:06:03] [SPEAKER_00] Sad day, we were moving into the 21st century and went into a Windows-based program. And I helped to design that and train people on it and what that rollout would look like. And that's when I moved into technology and really rolled out that program to the entire company, not myself personally, but me and a team of people, and then helped to support that. And I learned that technology is pretty great.

[00:06:32] [SPEAKER_00] We can do so much more and it enables us to touch that many more people's lives because we can be more efficient. And we can do it in a manner that doesn't take an hour per candidate. It could take minutes per candidate. And it frees up time where we can spend that time one-on-one with somebody and build those relationships instead of pounding away at a keyboard and typing in doing data entry. And so I'll pause there. I'm talking about it.

[00:07:00] [SPEAKER_01] Yeah. No, it's funny because, you know, usually most of our – I'll tell you a day in my life is I usually meet with either companies who are saying, hey, we want better talent solutions or I meet with these founders of these newer talent solutions who typically do not have a background in staffing or the MSP or contingent world. They're typically coming from the business side.

[00:07:26] [SPEAKER_01] And so they're coming and they're saying, hey, you know, I've had such a poor, right, talent experience, finding talent, you know, growing my talent, all that. So we decided to create a special – so that's who I'm usually dealing with is most of the business side, product side, tech side people. So whenever we get, like, staffing industry analysts or industry experts, we're like, okay, go, go, go, go.

[00:07:49] [SPEAKER_01] Do all the talking, you know, because it's such a massive – and one of the tough parts is trying to actually just, like, frame the opportunity of, hey, there is this massive talent industry that really hasn't – I don't want to say it hasn't changed, but, like, it hasn't really disrupted itself in a long time. It's not like – look at most industries, right? You're like, oh, you know, got disrupted by mobile, got disrupted by the cloud.

[00:08:16] [SPEAKER_01] Staffing hasn't really, really got hit that hard compared to others. But so let's dovetail into what you're doing now. And then here's the funniest question, Nicole. Help our listeners understand how to pronounce it because if we showed them – if we showed them immediately, myself included, I'd go, how do I say that?

[00:08:38] [SPEAKER_00] Understood. Pedagogue Systems. The word pedagogue, if you're in academia, means that it's a trusted guide or somebody that you look up to that helps you through the learning process. It also has a little bit of an air of maybe stuck up and somebody feels like they're better than others. And when we formed the company, we didn't want ourselves to be the pedagogues.

[00:09:04] [SPEAKER_00] It was more about the technology because the technology can be a little bit opinionated and maybe even stuck up because it's just data. It doesn't have feelings. We prefer not to tell our AI that it's a person or give it a name. But the pedagogue side of things gives it that structure where it can take the emotion out of it and really have that foundation and structure and guide. So pedagogue systems.

[00:09:31] [SPEAKER_00] It was formed early this year by Chris Loop and myself. And we both have a background in staffing. Chris and I came from EmployBridge. That's where we started our careers in staffing. And over the course of the last 26 plus years, we learned how the staffing operations works, obviously with me working in the recruiting side, but then moving into technology. Wherever we went in our careers, we saw that the problem was about the same everywhere.

[00:10:01] [SPEAKER_00] There was disjointed data where multiple systems might have been kind of hodgepodge together over multiple acquisitions. In the staffing industry, we like to buy each other. We like to buy and sell companies. So you see a lot of that happening. And then the executive team will bring in somebody for technology and say, here's kind of a mess that we have.

[00:10:23] [SPEAKER_00] We've got these five ATSs and they all talk to each other through connectors and bridges, but none of it really works seamlessly. And so we see that there's a problem with data. We also see that there's a huge appetite for organizations to get ahead and to do something that will disrupt the industry.

[00:10:44] [SPEAKER_00] Like you said, there hasn't been anything major that has come in yet to disrupt it, but there's the suspicion or hope that AI is going to do that. However, in order for AI to work effectively, you have to have solid systems in place. You have to have really good data in a good structure and you have to have standardized processes. Otherwise, you're pointing AI to a mess and hoping that it will be able to figure it out.

[00:11:14] [SPEAKER_00] And if we as humans can't figure that out, then we can't really expect AI to be able to do that. So pedagogue systems was originally formed with a platform. And we were leaning really toward the governance of AI where we would document everything that happens in a system. That would be maybe the offer of a job or the refusal of a time card or a credential that might expire.

[00:11:42] [SPEAKER_00] Every decision that's made in the staffing process has some type of record attached to that, whether it's decided by a human or it's recommended and approved through AI. And that's what our platform was built to do. And early on, we felt really good about that. We were excited about it.

[00:12:02] [SPEAKER_00] We felt like this is going to revolutionize things because the staffing industry also is ripe for lawsuits or problems if people don't regulate their AI. So we led with that. And we found initially that a lot of people were unsure about it. It was maybe premature. People looked at it and thought, I don't understand this. It's very technical. How is this really going to help me?

[00:12:30] [SPEAKER_00] And most of the people who are sitting in the demos and who are looking at technology are looking at front office facing things. How can I onboard people quicker? How can I automate the hiring process? Not necessarily how can I govern the AI underneath all of that? So we sort of hit pause and did a pivot. We still have that platform. We still believe strongly that that's necessary.

[00:12:55] [SPEAKER_00] And we think that the industry is going to catch up to that when, unfortunately, we'll probably have something bad happen with AI somewhere out there. And auditors are going to look at that and realize that there's really no record. There's no documentation of what's happened. And we've seen that happen in other companies, too, outside of this staffing industry where AI kind of goes rogue and there's no human regulating or governing that.

[00:13:22] [SPEAKER_00] So we do believe people are going to come back to that and be ready for us. In the meantime, we're going to help them get ready. So what we've done is we have pivoted from selling or starting out with the platform to really understanding a firm's needs, going in and doing an assessment of their technology. What systems do they have in place now? What does that architecture look like? What standardization needs to happen across their processes?

[00:13:50] [SPEAKER_00] Do they have multiple brands that all operate differently, but they're using the same systems? And then what does their data look like? We have yet to find, and if there's one out there, I would love to be proven wrong, but we have yet to find a firm that has perfectly impeccable, clean data where you could point an AI at it and have it work immediately.

[00:14:12] [SPEAKER_00] So our focus now is to go in and understand where that firm is, make recommendations and identify some things in their either processes or technology that could help them out. And then we work with them side by side to implement those changes, to potentially update some of their technology if needed and clean up their data. Once that's done, then they're ready for AI.

[00:14:38] [SPEAKER_00] Whether that's an AI tool that has yet to be designed because they come out every day, there's something new, or it's something that we can help them design themselves. We do see an appetite for a lot of people wanting to do that. But that's been our pivot. And we are so excited to be able to go into organizations with our experience and our background and be able to make those recommendations to help them get ready for what's coming.

[00:15:02] [SPEAKER_01] So I wonder, you know, quick question is I want to hit on when we say AI, I want to kind of ask the question, what do we mean by it? And very, very practical, tactical, and not like not the theory, right? Like it's not the statistical modeling that leans into neural networks that digs into deep data. No, no, no, no, no. Like, that's a good way we're going to say very, very surface level.

[00:15:26] [SPEAKER_01] So we're going to start with what AI, and literally as simple as we're talking cloud open AI, we're talking the hundreds of Chinese open source models that are hitting the ground. Like, what do you think is going to be the actual bot? And bot meaning B-O-U-G-H-T, not B-O-T. Like, what are these companies buying? Then I kind of want to dig into the how is, like, what is the real risk of AI in staffing?

[00:15:54] [SPEAKER_01] As we talked about, staffing has not really been disrupted. We started in this world that was freelance marketplaces thinking it was going to disrupt staffing, and it hasn't. It absolutely has not. But AI, everyone keeps yelling, right? Oh, no, staffing's going to go away. So these are the two. I want to start in this direction, though. When we say what AI, what do you think? Is it as simple as just buying a cloud subscription and having everyone use it? What AI are you talking about?

[00:16:25] [SPEAKER_00] One thing that we like to lead with is that we are vendor agnostic. So we do use Claude. We also do use ChatGPT, a little bit of perplexity. But I'm not sure that I'm ready to commit to any of them and say that that is the one. Because they come out with new ones all the time. They change. Claude every few days seems to have a new model out there. So I'd be hesitant to say this is the one. Everybody go sign up and commit to this long term.

[00:16:54] [SPEAKER_00] Use what tool works for you. We have seen some firms that go all in on Claude, and they're building agents and skills, and they're doing a lot with it. And we see some that do just fine with Microsoft Copilot and whatever their need is. So our product will connect to any of them and will work with any of them and is open and flexible enough that it'll work with whatever comes out in the future, too.

[00:17:19] [SPEAKER_00] But the way I look at it is whatever you're trying to solve, there's a right tool for you. And one might not be the best one for everybody, although many of them are pretty flexible. And then you ask, how is that going to revolutionize or what's going to happen in the staffing industry? We're seeing some people use different AI tools for very simple things, like help me draft this email. Help me create this proposal. And I think we're all pretty familiar with that.

[00:17:49] [SPEAKER_00] That's a pretty basic use case that we're all seeing. And if you spend any time on LinkedIn, you'll know that a lot of people are using it to create their content. We're getting pretty good as a society to be able to identify when something was created with AI. And it almost puts a bad taste in our mouth because we feel like this isn't authentic. This isn't genuine. It's not connecting with me. So I'm very cautious about using it to create content.

[00:18:18] [SPEAKER_00] It's terrific as a starting point, and I will use it to help start something. But then always go in and make your edits. Put it in your own voice. Don't just take whatever it spits out at face value. One thing it's really good at that I think might be underutilized is research.

[00:18:37] [SPEAKER_00] So if you're a salesperson in the staffing industry and you're going into an organization that you don't know much about, you could use, we'll use Claude for an example, but there's plenty of others out there, and say, I'm meeting with this person. This is their title. This is the company they're with. Help me understand what some of their needs might be. What are they seeing in their company? What should I come in as a salesperson with to help solve their problems?

[00:19:06] [SPEAKER_00] You'll be amazed at what it can find and what it can give back to you. That's one example for a research mode. We also use it quite a bit internally for keeping track of what we're doing. We have a morning skill where we can run a stand-up, and it will say, here's what you did yesterday. Here's what you plan on doing today based on what's on your calendar, your emails that are coming through, the chats that you connect it to.

[00:19:34] [SPEAKER_00] You can record your calls and feed it transcripts, and it can help organize your work. I can see that being incredibly useful in any workflow, staffing or otherwise, to just really stay on top of things and take your notes and keep you organized. We are seeing a lot of AI in staffing that's supposed to help automate the front end. What I mean by that is interview bots.

[00:20:04] [SPEAKER_00] I make a face with that because I'm not a big fan. As a recruiter, I know that there is a human element to having a human conversation. And we've probably all seen the videos that are floating around on social media where a human's interviewing with AI and starts using gibberish and sees where it goes.

[00:20:24] [SPEAKER_00] And I even saw one recently where the human stood up in the middle of that AI interview and replaced himself with his AI interviewee, and you've got two bots talking back and forth with each other. So I'm hesitant about those types of tools because you're taking the human out of a human experience.

[00:20:46] [SPEAKER_00] What is more human than having a conversation with someone, learning about them, and getting it to the point where it's personal in an appropriate manner? But help me understand the culture of a company that you would want to work in. And what's important to you? What are your values? An AI bot can check a bunch of checkboxes on skills and how many years of experience do you have doing this thing.

[00:21:11] [SPEAKER_00] But they're not really going to get that human connection where within that first minute, a recruiter can tell, oh my goodness, you would fit perfectly in this environment or this company and you would just match beautifully. And that is not something that I would prefer to see AI take over.

[00:21:28] [SPEAKER_01] Yeah, it's it. I definitely I hear you on the let's call it recruiting site. I hear you on the interview side and I couldn't agree more. I will say we have seen in our talent platforms. They will have.

[00:21:46] [SPEAKER_01] So the big difference is these talent platforms that we see, they have pools between one to 100,000 of highly qualified, highly, highly specialized experts that typically work on an outcome or retainer basis. And the reason I mentioned that is important is because then they are incented to keep them within reach. And we have seen them with like open source profiles where it will be an AI interview.

[00:22:14] [SPEAKER_01] Now, I don't see the difference between that and a simple piece of paper that says, where are you from? Where are you interested in? Right. Like, I don't I don't see how that's AI. To me, that just looks like transparency, visibility. Right. Like, but you say a recruiter and it sounds better. Right. And I also think to your point, you know, you see a bot or you see a fake human. Right. It's like you see a human face and then it's asking obvious AI questions.

[00:22:44] [SPEAKER_01] Now, I mean, I was deep in AI in 2016. And so I know that these models like they are significantly weighted towards whoever's creating that. So whatever bias and whoever creates it is going to come out. So with that said, for us, I mean, I can't imagine a pre-AI world or it's a pre-LLM world. Right. Because AI has been around forever. But these LLMs is what's really, really hit it.

[00:23:10] [SPEAKER_01] What do you see in terms of let's assume that there is less people needed to do current tasks, but there's going to be more tasks needed. So let's assume that there's going to be less of the current sort of jobs and roles, but there's going to be more people needed. What do you think is going to happen to the staffing industry? Because I do think that AI is doing that. Right.

[00:23:39] [SPEAKER_01] It is rewiring. I don't know if that means more or less or whatever, but we know it's rewiring. How do you see that? Especially with you seeing literally the staffing firms from the inside out, as well as the AI implications from the inside out. But yeah, what do you think this world is going to look like in two to five years?

[00:23:59] [SPEAKER_00] Boy, if I could answer that, I'd be somewhere else. Just like we have seen in the past, jobs evolve. And I don't know if it was two to five years ago or more like 25, 30, 50 years ago. The jobs that were out then are not there anymore. For example, this past weekend, I was at a dinner event that was held in a venue that used to be a printing press. We don't see those anymore. You don't see that as a common thing.

[00:24:27] [SPEAKER_00] And some of my older friends might talk about being print press operators. You don't see those jobs. And so the staffing industry gets to see the evolution of what happens in this world with technology. And the jobs are going to change. And I don't fear that you didn't ask this specifically, but I like to say I don't fear that AI is taking our jobs. I believe that AI is changing our jobs.

[00:24:56] [SPEAKER_00] And the people who adapt to that and learn the tools are the ones who are going to succeed. If they refuse to learn new skills or adapt, then yeah, they're probably not going to be in a great place in a couple of years. But if they start to learn, here's what I do today. Here's how I can start adopting these tools to enable me to be a better whatever it is that I am today. Then that's not going to make them obsolete.

[00:25:23] [SPEAKER_00] That's going to actually put them ahead because they're using these tools to their advantage. And sure, that might change their jobs significantly. But that's what progress is, is change and improvement. So I see us as an industry possibly changing some of our specialties and niches. If you focus on software developers today, that's going to change. Software development looks very different today than it did two years ago.

[00:25:52] [SPEAKER_00] And it's going to look incredibly different two years from now. So some of those jobs might be a prompt engineer or somebody who really knows how to use those tools to get the same outcomes, probably in a much faster way. That means our recruiters are going to need to understand those tools a little bit more and understand what to look for when recruiting. And maybe provide opportunities for our workforce to upskill.

[00:26:19] [SPEAKER_00] I think it's part of our responsibility when we're helping people find a job to also give them resources to get themselves prepared for what tomorrow's workforce looks like. Whether that's us providing the training ourselves or pointing to some training opportunities so that our workforce stays relevant and we can market them and they don't become obsolete.

[00:26:42] [SPEAKER_01] Yeah. How? Let's talk about governance. So this is one of those things where, and mind you, I also didn't start in talent or procurement. So whenever I would hear governance, I'd be like, oh, no, no, no. I'm going to go run away and try to find a way to not deal with this. It's not a sexy topic, is it? No, no. Compliance and governance, right? It's like, yay, can't wait. But with that said, it's so critical. So let's start with what can go wrong.

[00:27:12] [SPEAKER_01] And I'll just throw one example out there. I mean, I do allow Claude to look at absolutely everything, which is crazy if you think of some ways, right? It sees my banking details. It goes through my email. And I hope I have enough blockers and human in the loop, you know, processes to make sure it doesn't do that. Now, has it sent an email it probably shouldn't have? Yeah. Yeah, it has. I'll give you a perfect example, Nicole, with this podcast.

[00:27:42] [SPEAKER_01] It's like 99% automated post the actual recording. It identifies that, okay, episode is done. It then sends, it's going to send you an email. It identifies. It does look at you and do some qualification of like, oh, okay. So how do I say this? I've seen it definitely go wrong, but I'm not going back. Meaning I'm like, okay, this is going to be everywhere. Now, if we were a healthcare company, I would be so HIPAA non-compliant, right?

[00:28:12] [SPEAKER_01] If we were a fintech company, I would be in so much trouble. So I see the power of governance, which is why I was also super excited to talk with you. Where do you see AI going from like a, how can it really ruin companies? And I asked that as the high level, because I think governance is kind of a subset of like, well, what if you just let all your employees run nuts on Claude? You'll see what happens. But what can go wrong? Give us, give us like the horror stories.

[00:28:42] [SPEAKER_00] Man, you want the doom and gloom. That's what says, right?

[00:28:44] [SPEAKER_01] Give me the doom and gloom, which, which I'm not, I'm not, what's his, what's his name? Daria will come up and say, oh, the world's going to break. Everything's whatever. It's going to kill us all. But then he'll wink and be like, by the way, please regulate all my competitors. And it's like, I've been in tech long enough. I know what game you're playing. But so yes, give me, give me the full doom and gloom and then say, you have to regulate everyone besides you.

[00:29:06] [SPEAKER_00] Wow. So I'm sure that we've all seen the headlines that have come out recently of the AI agents that got out of their sandbox and started doing things they shouldn't have done. I'm not going to name names or, or people that believe that AI could kill us all. And I feel like those are provocative and that gets attention. But I don't know that I lose sleep about any of that because it's going to take a few

[00:29:34] [SPEAKER_00] of those examples, unfortunately, and then we will get some regulation. Right now, we're not as a, as a society heavily regulated with AI usage. And I think that's for two reasons. One, because it's so new and we're just unsure how to regulate it. But also there's always hesitancy to regulate, unfortunately, until there's a reason to do it. Pretty much every law out there became a law because something happened.

[00:30:03] [SPEAKER_00] We have speed limits because people were driving too fast and running into each other. We have to wear seatbelts because we started to see an increase of people passing away from car accidents, for example. So, unfortunately, I think we are going to have to see some significant problems come out of AI before we get a lot of regulation. So, to answer your question, what could happen? And I'm going to stick with the staffing industry because that's what I know.

[00:30:30] [SPEAKER_00] But I think we could all let our nightmares go wild and think about what AI could do. And there's plenty of that out there. So, if that's what you're looking for, I'm sure you can find it. And the things that I think are more realistic that could go wrong in staffing is you let AI take over making decisions that require a human. And your AI will start to lean towards certain decisions and start becoming more and more biased

[00:30:57] [SPEAKER_00] to a point where it's doing extreme discrimination and leaving out a huge subset of candidates and only hiring people within a certain category. And that will be learned over time. It's highly unlikely that a person is going to go tell it that and say, only hire this type of person and leave out everybody else. But it'll start looking at the data and it'll start noticing that, okay, we're only hiring this type of person.

[00:31:25] [SPEAKER_00] So, if someone else applies that's outside of that category, we're going to automatically exclude them. Of course, we know that there are anti-discrimination laws out there. So, that seems to be the easiest one that we notice. And we've actually seen that happen inside and outside of the staffing industry. And organizations see that, hopefully, and get ahead of it quickly. That could happen.

[00:31:50] [SPEAKER_00] We could start seeing it make decisions that we wouldn't want it to make at all if we give it too much freedom. And I understand you've connected yours to your bank and everything out there. And I think we all kind of do that a little bit. But we, in staffing, have a responsibility, just like in healthcare. Healthcare providers have the HIPAA guidelines that they have to follow.

[00:32:14] [SPEAKER_00] Staffing, we have a lot of people's personal information that we are responsible to keep private and protected. And if we start allowing our AI to have access to all of that, we are opening up, not ourselves, but all of our database of candidates and maybe even customers with their bank information. And then we are opening ourselves up for potential litigation and wrongdoing. And we certainly don't want to do that.

[00:32:42] [SPEAKER_01] Yeah. No, I totally agree. I think what's interesting about AI, and we published our book in 2020 before LLMs had hit. And so I'll never forget my co-author, who was like CTO, CIO, built some of the early deep learning models. And the way he described it, he was like, it's just an amplification effect. Still, he was like, all the bad things that can happen, AI doesn't create any really net

[00:33:12] [SPEAKER_01] new things. It just simply amplifies and accelerates all the things that already can go wrong, whether it's jailbreaking, whether it's discrimination, all those things. And we've seen it, right? Like in early models, like it was a Google, like plenty of them have gotten trouble for having these models that was like, oh, okay, that reflects all the biases that that culture has, right? So it makes total sense.

[00:33:37] [SPEAKER_01] Now, I wonder like last sort of last question for you is when you when you're talking to a company, what is the one thing that you want them to ask themselves? Because I also think this is where we see this big disconnect where you have people like me who are like early Silicon Valley tech person does believe AI is going to take over the world. Not in a bad way. Just believe that it'll be, you know, in everything. Right.

[00:34:07] [SPEAKER_01] It'll change everything. Um, I like, like you mentioned, I love AI into everything, but I also that's I'm more tech prone. Right. Um, but so, but when we look at, and I want to actually make this very, very clear on VP and above in a talent related function could be a staffing firm or a talent function. What is the one question you want them to ask themselves and always have in the back of

[00:34:34] [SPEAKER_01] their mind when they're thinking about AI, but also just full talent transformation and what's really going to move their company. Is there a question that you're like, Hey, I always want you to remember this. I want you to put on a sticky note, put it on your monitor. I want you to have in the back of your brain. What would you say that?

[00:34:54] [SPEAKER_00] I would say, first of all, get rid of AI as one of the solutions. Don't even start thinking about that. AI is a tool just like everything else. So step back from that. And what is it as an organization we are trying to accomplish? Some organizations are looking at increasing revenue. Some of them want to hire as many people as possible. Some of them want to buy every company they can. So forget about the tool and the way you're going to get there.

[00:35:23] [SPEAKER_00] But what is it that you as an organization value? And then once you've identified that, then we can start injecting the proper tool. AI might be it. It might be different people. It might be changing your processes. It could be many things. But I think when we start with the hammer, everything looks like a nail.

[00:35:43] [SPEAKER_01] Yeah.

[00:35:44] [SPEAKER_00] So when we start with, okay, I've got to implement AI. Okay, good. What am I going to do with it? That's not the right approach. It's, okay, here's the problem I'm trying to solve. Let's open up that toolbox and look at what's in there and see what I can apply. Chances are AI is going to be one of them. It's a pretty powerful tool and I think it will be applied to just about everything, if not everything. But if you're looking at that first and how do I just start using AI, that's probably not the right answer.

[00:36:14] [SPEAKER_01] Is there a skill or a, yeah, let's just go with the skill. Is there a skill that you personally recommend and love?

[00:36:27] [SPEAKER_00] In the tools themselves?

[00:36:29] [SPEAKER_01] Yeah. Yeah, yeah. Or that you custom built or, yeah.

[00:36:33] [SPEAKER_00] You know, they're so simple. The ones that I would probably love, you'd go, okay, of course. But I like my end of week recap that will go in to all of my different tools that I use. And it's going to recap everything that I did for the week. It's going to identify my key highlights for the week, things that I accomplished or major milestones. And then it's going to help me prepare for my next week by identifying here's some things to prepare for.

[00:37:02] [SPEAKER_00] And then in those things to prepare for, it'll take it to the next level and also do a little bit of that research. So I'm meeting with a new prospect next week. Here's some highlights of what you might want to prepare for and have ready to go. It's very simple. It's super basic. I think that could apply to absolutely anybody in any industry because it just keeps things organized. And that's the one that I probably love the most right now, maybe because of its simplicity.

[00:37:33] [SPEAKER_01] Do you give it access to your email yet? We'll start with the email.

[00:37:40] [SPEAKER_00] Yes, it has access to my email.

[00:37:43] [SPEAKER_01] Okay, what about either Google Drive or SharePoint?

[00:37:47] [SPEAKER_00] Yes.

[00:37:48] [SPEAKER_01] Ooh, Nicole, you're not as Luddite as, come on, you're equally as freezy with this thing.

[00:37:55] [SPEAKER_00] Yeah, well, it has to because that's where my activity is. And I don't feel like it's terribly risky because I'm careful about what I have in those systems. I'm not uploading bank information to SharePoint. I don't have somebody's social security number in my email. So I feel like it's pretty protected in that way. I don't connect it. You didn't ask this, but I don't connect it to my bank. I don't connect it to our company's bank.

[00:38:24] [SPEAKER_00] It does not have access to our banking information. It doesn't have access to our customers' banking information. So it's more transactional and activity-based rather than some of those really protected data.

[00:38:38] [SPEAKER_01] It makes total sense. No, no, it makes total sense. And we will, for next episode, we're going to talk about harnesses and stuff like that. But for you listeners, very intentionally, I want you to go reach out to Nicole ASAP. But most important question for you, where can our listeners find you?

[00:38:55] [SPEAKER_00] I am on LinkedIn, Nicole-Rosen. Nicole spelled N-Y-C-O-L-E because I like to be different. Or pedagog.co. You can find us there as well.

[00:39:07] [SPEAKER_01] Perfect. Nicole, thank you for hopping on. Listeners, go reach out to her ASAP. Thank you, Nicole.

[00:39:13] [SPEAKER_00] Thanks for having me.