The Freelancer Advantage in an AI World with Dr. Kelly Monahan

Frank Cottle [ :00:00:02 ]:
Kelly, welcome to the Future Work podcast. Gosh, it’s such an honor having you here today. Head of research, upwork, author, doctorate, amazing background and I’m so excited. As you know, I’ve been a fan of upwork originally elance for decades. Anything temporary, anything remote, anything flexible, that’s where the future of work is going. And you guys have been pioneers. So welcome and I’m excited for this conversation.

Kelly Monahan [ 00:00:33 ]:
Thanks so much for having me today, Frank.

Frank Cottle [00:00:37 ]:
You guys do a lot of research and your reports in your most recent research highlights both AI specializations and the growing demand for human centric skills. Isn’t that a contradiction? Or how do those things balance out and basically what’s driving those two things? On parallel paths.

Kelly Monahan [00:00:59 ]:
Yeah. Now, Frank, I’d be curious to get your opinion on this as well and what we found, but we’ve actually been studying previous technology transformation. So robotic process automation, cloud computing and generative AI seems to be manifesting itself differently on our platform compared to the last 20 years or so of previous technology advancement. And there’s two reasons why. The very first is what our research is finding is that generative AI is requiring those that are working alongside of it really specialize in technical skill sets. If you’re in the STEM profession or you’ve been working with machine learning as an example before, you’re having to go even deeper to stay relevant and really capture the value of these AI models. Now, the second difference that we’re seeing is that before that was true for route across automation cloud computing. It really benefited anyone who was a software engineer in it. We saw a very concentrated disruption. Not so with generative AI. We see disruption across all categories of work on our platform. So if you’re a marketer today, you’ve got to start learning how to work along AI content creation. You know, if you’re a writer or you’re in our translation space, you have to now be able to work alongside AI, because that is where the demand is going. So because of those reasons, the reason why I think we are seeing, you know, these human centric, I’m calling them, learning how to learn skills because it’s growth in our categories of professional coaching, training and development is because I think this technology disruption is so widespread, the majority of the workforce today is under tremendous pressure to rethink how they’re doing their job to stay relevant and requiring a newfound sense of agility and resiliency that I would argue only comes from human to human coaching.

Frank Cottle [00:02:37]:
Wow, that was a mouthful.

Kelly Monahan [00:02:39 ]:
Too much?

Frank Cottle [00:02:40]:
No, no, no, that was a Ton of information. I think you’re right. If I were to take everything you just said.

Kelly Monahan [00:02:49]:
Yeah.

Frank Cottle [00:02:50]:
Put it in a little package and then throw my own bias on top.

Kelly Monahan [00:02:53 ]:
Yeah, go for it.

Frank Cottle [00:02:56 ]:
I look at AI as a new species, I don’t look at it as a technology. And if I’m looking at the growing demand for human centric skills alongside of a new species, which teaches us also how to work with our existing species better.

Kelly Monahan [00:03:17 ]:
Yeah.

Frank Cottle [00:03:18 ]:
I think I would say the human interaction skill sets that we’ve always. That we kind of lost in our existing other technologies, that AI can teach us how to be a better partner, not just with technology, but with each other.

Kelly Monahan [00:03:35 ]:
Yeah.

Frank Cottle [00:03:36 ]:
And it’s not teaching us like here’s the rules and here’s the process for it. I think it’s not that kind of disciplined teaching. I think it’s the gained interaction that we’re trying to achieve. And as we try and achieve it with this technology or species, as I’m calling it, we also have to look at how we deal with people, not non AI, the non AI side of things. And if those things can grow together, will truly make advancements. If it grows, if AI grows purely as technology, then the geeks will continue to inherit the world and the rest of us will be left behind. People, the, the concept of the, the, the evil guy in the super high rise masterminding the way AI works will become our world. Dystopian world actually, as opposed to if we learned these things together. So that, that’s kind of my own crazy view.

Kelly Monahan [00:04:42 ]:
Yeah. I actually don’t think it’s crazy at all. I want to give you a real life example because that resonates so well with me, even just thinking about this as a form of species. And the way that you just described how AI can be used. So no surprise. I mean, things can get spicy in dialogue as you post something on LinkedIn or on social media these days. And so how I’ve been using generative AI because at the end of the day we’re still wired to be reactive and have our biases, as you just mentioned. And so I was getting in a bit of a debate the other day on LinkedIn on a topic. And so that’s where I use generative AI. I copied and posted the text that was being used and I said, tell me, what is the tone here? What am I missing? How do I open my mind to think differently about what this person’s trying to communicate? And I’ll be honest with you, I approached that so differently and I Actually learned a lot in that process of like, oh yeah, wow Kelly, here’s where your bias is. You know, and I, that was hard for me to do on my own without having a bit of that coach in some ways and hopefully I had a much more human dialogue as a result of it.

Frank Cottle [00:05:41]:
Well, you know, I think you’re right. When we talk about coaching, we talk about a learning partner is the way I look at it, it’s a learning partner. It does one thing. And I’ll use our own team at all work. We’re big fans of generative AI and it has taught us as journalists how to ask the who, what, where, when, why how questions more effectively, how to question and challenge the articles we’re writing as opposed to just get it over with, get it done, get the point made. Really is it the right point? You know. So I think in that regard it’s been very helpful. But that’s when you’re using it as a partner.

Kelly Monahan [00:06:29 ]:
Yeah.

Frank Cottle [00:06:30 ]:
Asking it the right questions. And you said we’re all reactive. Yes, we all react and sometimes in social media people react real fast. But I think if we are thoughtful in our reactions, there’s an old, old gunslinger saying fast is smooth, slow, slow, slow is smooth and smooth is fast. Ah, okay. You respond with more accuracy is the point. And I think when you have the time to, without taking a position, challenge artificial intelligence on its findings. Yeah, you can accomplish that sort of reaction, but thoughtful reaction or that’s, that’s the hope. And, and we all know that it’s early days. It’s such early days in this stuff and we could be completely wrong. You know, everything we’re thinking today could easily reverse itself and change in six months.

Kelly Monahan [00:07:37 ]:
Absolutely.

Frank Cottle [00:07:38]:
So I, I think that’s fun if those generative AI and human skills are driving themselves together.

Kelly Monahan [00:07:46 ]:
Yeah.

Frank Cottle [00:07:48 ]:
The decline in this current gen Z and pushing alpha need for college degrees in your business, which is started out as gig, as gig business and now it’s full fractional employment in highly degreed specializations oftentimes. How do you, how do you rectify that? Will I be better as developing my career to focus on having AI as a partner and learning how to augment my own creative capabilities through the factual and research capabilities of AI? Or am I going to be better as an individual seeking a classic degree and when I enter the workforce, how am I going to be judged? Who’s going to judge me? We degrees only hiring rule. We only hire degreed people. That’s terribly wrong. But we don’t know how else to do it.

Kelly Monahan [00:09:00 ]:
Yeah.

Frank Cottle [00:09:01 ]:
What’s your solution there?

Kelly Monahan [00:09:03 ]:
Yeah, you know, I think this is such a complicated question and I think it’s something that we’re seeing play out in real time. So again, this is for me, I’m going to just share my personal bias. I mean, as you know, I spent 10 years in formal education. So I’m a huge fan of education and, you know, degrees and institutions. But if I’m going to take a step back and put my researcher hat on and what I’m seeing in the data and the shifts that’s happening, I do worry our educational system has lost its way. And the purpose of education is to learn how to learn, to be able to have those skill sets, to be able to understand the world around you and then obviously go out into the real world and apply that. I think for the last 20 years or so we’ve really accredited a lot of business degrees and business programs that have taught people how to be generalists. But the reality is it hasn’t kept pace with all the advances. Like you just said in AI, we don’t even know what the world of work is going to look like in six months. That’s daunting to an education institution who is trying to keep pace. So to me, I think the question educators have to ask themselves, you know, if you’re going to go get a college degree to go become a generalist is probably not going to keep you future proof and employed. That degree is going to become quickly less valuable. But if you go to college and you get an education to learn how to learn, to ask those thoughtful questions, those five questions you even just addressed of the who, what, where, how, how do I understand the world around me?

Frank Cottle [00:10:24 ]:
Don’t forget why and when and why and when.

Kelly Monahan [00:10:27 ]:
Probably the more important ones of that, you know, I think that is where education still holds a tremendous value in our society. However, as I look at the data, the majority of executives are telling us today they aren’t necessarily looking at degree as that first filter. They’re looking for the experience and the skill and the credential for that skill. And I think that is where the world is rapidly changing. And what you just said is what I hear from Chros all the time as they try to make this pivot to skills based hiring. What’s the new filter? A degree is an easy filter, right?

Frank Cottle [00:11:00 ]:
That is the hard part.

Kelly Monahan [00:11:01 ]:
That is the hard part. I don’t know if we have a good answer for that. Upwork is different because we have a freelancer platform and we have the rating system and there’s a sense of transparency and clients are able to rate freelancers. And there’s a sense of accreditation happening in real time on our platform as freelancers demonstrate their skills. But when you start thinking about full time employment, what is that translation and how do we make sense of that? I think that’s a burning question that still needs to be addressed, hopefully sooner rather than later.

Frank Cottle [00:11:29 ]:
Well, you know, we’re, we’re through another company we own. We’re tied very closely to IBM’s Watson. Oh sure, AI system. We’re all inter interactive with that and those filters and, and it’s all it, we’re tied to the hiring processes that are used and all the algorithms that are used in that for setting up meeting rooms for, for the hiring processes the large companies use. And those filters, nobody has them. Funny. My dad, I come from an old ranching, farming, food production family, California, originally from Texas, where I live now. And when I went to college, my dad said, I don’t care what you major in, I don’t care what you do in college, just learn to make decisions. That was it. He says, that’s what college is for, is for learning how to make decisions. And yet college teaches you to go work for somebody else. Yeah, you know, that’s what it teaches you. And sadly, I got kicked out of my first college. I was asked, I was actually asked not to return. There’s a difference between that and getting kicked out. I was asked not to return after two years and I had to explain to my dad when I came back, I said, yeah, I kind of lost a quarter’s worth of credits and I’d been actually living in the Bahamas and doing some commercial diving. And she said, have you got really good grades? And I said, yeah, but they, they stripped all my credit for the quarter. And I said, you know, he says, and he’d been paying for all this, you know, and he said, well, did you learn anything? And I said, yeah, decisions have consequences.

Kelly Monahan [00:13:19 ]:
I love that I had to really.

Frank Cottle [00:13:22 ]:
Think that one up, you know, and he just looked at me after all this, you know, this horrible thing that I’d done as a kid, he looked at me and he said, well, remember it. And he walked away. That was his total lecture on the topic. And I really think that the purpose of becoming educated, if you, if you look at the great philosophers, the great teachers throughout history, they’ve all been focused on helping us to learn how to make good decisions, whether it’s the great stoics or any philosopher, any philosophy it’s about making religion, it’s about making the right decisions. College doesn’t necessarily teach you that. But there is no filter.

Kelly Monahan [00:14:11 ]:
Yes.

Frank Cottle [00:14:12 ]:
So I guess that’s one of the challenges we have to face. I don’t know if AI can actually provide a filter when you talk to somebody. Great AI skills, really, what are they? Well, I can. It’s hard to ferret this out. It is, it really is. So I’m challenged by that myself and I don’t know how you all are solving it. Do you have any down the road insight into that?

Kelly Monahan [00:14:39 ]:
You know, I think it’s going to be probably a billion dollar question for us to figure out from an economic perspective. Because at the end of the day we’ve assumed that if you have a degree to your point that there’s. That constitutes a generalized skill set that we’re signing off on irregardless of even. I mean Google found this out really early on. That degree was actually not a great predictor at all of success within their organization. So I think what’s hard about this is it’s contextual. What makes, what’s going to make me successful here at UPWORK versus maybe Frank, if I came to work for you within your organization might require a different skill set. And so I think the hard part about this, this cannot necessarily be generalized. It’s really context specific as we start talking about skills and how those are applied. And you’re exactly right. I mean, I think as we start talking about generative AI, what we’ve learned on our platform. When generative AI became mainstream in November 2022, we had a set of, let’s call it 40 to 50 skills that we thought encompassed the work that was going to be done on our platform. Today we now have over 200 skill sets that are getting deeper and much more specific of what is this?

Frank Cottle [00:15:46 ]:
I would have thought it would go the other way. I would have thought there been a refinement from the broad funnel.

Kelly Monahan [00:15:53 ]:
Sure.

Frank Cottle [00:15:53 ]:
Rather than an upside down funnel.

Kelly Monahan [00:15:56 ]:
Well, the reason is because of all of the category disruption we’re seeing. So what someone needs. Let’s just take our writer in your business. I can see that in our business. Yeah. And we’re getting smarter in order to get the matching right as well. We’ve got a. It’s called upworks Mindful AI Uma. It’s allowing us to understand, okay, the type of skill sets that an AI marketer needs are very different. The type of skill sets that a software engineer needs that are different than someone who’s A journalist or a translator who’s now using AI. And so we’re getting much smarter around what those differences are and where they matter. And so I think that’s still a lot of discovery. And I do think AI should begin to help us detect patterns and those skill sets that clients are looking for that, you know, workers are signaling. The question’s going to be then what do you do with all that information to actually make better decisions?

Frank Cottle [00:16:44 ]:
Going back to your original point, there are two types of two groups that are hiring in the world. Generalizing here, of course, there are large scale businesses and then there are independent smaller companies. The predominant that needs fractional support or part time or remote or full flexible. Started with the smaller business person. I need a personal assistant. Okay. And it went on from there and now it is, it’s the, the two groups are merging overall. However, artificial intelligence within the large HR systems hiring processes screens the hundreds and hundreds, if not millions of resumes before a person ever sees them. Now. Yeah, and the contextual issues that you’re talking about are all up to the decision making of that algorithm in the artificial intelligence. So how do you rectify that little dilemma?

Kelly Monahan [00:18:01 ]:
Oh, I think it’s going to be a really, it’s going to be a tricky issue for HR to figure out because at the end of the day there’s still a human who’s made decisions on the parameters within the algorithm that’s biasing or swaying the decision making of.

Frank Cottle [00:18:15 ]:
That’s removed. That’s two or three times removed. The algorithms that are being purchased by the, the services that are being purchased through technology companies by the HR departments of other large companies. There is no person in the HR department doing the interviewing process themselves. Generally that affects or can affect the filtering in that algorithm.

Kelly Monahan [00:18:47 ]:
Yeah, well, this is why I think HR has to be so talented in statistics and it cannot be a black box. To your point, if it’s two or three times, if the HR department’s not building their own algorithm to account for the context and make those decisions themselves. And to your point, they’re buying it twice removed from in a workday or some other big HR system. I just think there’s a sense of responsibility and accountability that HR is going to have to own and that is going to be required. A sense of technology literacy that I don’t necessarily know if AI or AI that HR has had to have before. And I just think, you know, if I’m a CEO or I’m, you know, running a company and I, my HR person can’t Tell me the way that the algorithm’s tuned or the filter, the way that that’s weeding out. There needs to be an audit process as well. Did we weed out a certain demographic or type of candidate? Is there some sort of bias? These are all new functions and tasks that I don’t think HR has done before.

Frank Cottle [00:19:41 ]:
Doesn’t that I’m going to say some probably insulting things. Mark Twain. Lies, lies and damned lies. Okay. Give me three numbers and I can win any argument. Okay. I think data in hr, when you use it in that format gives you the mean average outcome, not the exceptional people that you need for an exceptional outcome. Because that’s what data does. It averages, it reports, et cetera. So I’m concerned and I told you I would argue about some things.

Kelly Monahan [00:20:26 ]:
This is great. I love it.

Frank Cottle [00:20:28]:
I truly would be concerned if HR became a statistically driven decision making process even more than it already is through these algorithms that are the filters to the foundation of the process and that that would cause the future of work as we look at the changes coming up. To get turned. I don’t want to say vanilla but you know because I actually like vanilla. But to get turned into to a mean average that didn’t have a way of identifying exceptionalism.

Kelly Monahan [00:21:09]:
Yeah. So yes, I’m going to push a little bit on this because I think this is actually a super important dialogue. So when I was at Meta I was within their people analytics group.

Frank Cottle [00:21:18 ]:
Your background is amazing information you found.

Kelly Monahan [00:21:23 ]:
Yes. And I’m going to give Alexis Fink a shout out. She was my boss and she runs the Society of Industrial or Psychologists. Now this was a concern. Is to your point what AI is really good at is displaying the dominant discourse of what it’s trained on and absolutely. To raise whatever’s mainstream and dominant within that. What we were focused on and what I mean HR has to be good at statistics is not to necessarily know the averages. AI has got that covered in spades. What I mean by attorneys know statistics is they need to understand outliers and variations and standard deviations to identify exactly what you’re just saying what the AI algorithm is missing. And that’s what we started really fine tuning in our data when I was at Meta is moving away from just looking at the mean because the mean isn’t saying anything interesting.

Frank Cottle [00:22:09 ]:
It’s.

Kelly Monahan [00:22:09 ]:
And to your point it may even be perpetuating biases. What’s interesting and what we began to really uncover some fascinating insights is when you begin where’s the variation happening? Where do we see wide Variation, because that means there’s going to be individual differences and human differences that we need to go spot and begin to study and look at. Where are the outliers who didn’t make it through the filter? Why? What’s interesting about them? And that is where I think it becomes really important for HR to have more than just a baseline. Oh, here’s how you calculate a mean or a median. I’m talking one step further to really begin to master these AI tools. Because if HR professionals don’t understand this and we don’t start exploring these differences in variation, we are at risk of just perpetuating the dominant discourse. And I actually don’t know if that’s what the world of work needs right now.

Frank Cottle [00:22:59 ]:
Let’s swing around to the skills necessary and the skill gaps that are necessary that freelancers and the evolution of freelancers as a workforce rather than just a freelancer. It is a true workforce now on a global basis. And technology that we’re talking about knows no boundaries. So all of that goes away. What are the gaps that are being filled in and who are using this growing workforce that’s really refining us? It’s a self correcting, self refining workforce in my view. It is the outlier that has become the norm. How is, how is that benefiting the worker and the companies as we evolve into the future of work and what skill gaps are being filled?

Kelly Monahan [00:23:59]:
Yeah, I love this question. Frank and I actually got a book coming out called Essential. And we talk about this because it’s essential leadership competencies and capabilities right now that we believe are necessary to navigate the future of work. And the very first thing in the problem that we talk about is a skills gap that almost every executive, if you ask any CEO survey today, you know, what’s the top three concerns? It’s been this for a while, but, you know, we don’t have the right skills in our organization to get ahead in the future. We just saw that within our upwork research too. Almost 50% of executives today say they don’t have the right AI skills right now within their workforce. And it’s interesting to me because I think in the IT world we talk a lot about tech deck, but we don’t in the HR world necessarily talk about the skills debt that’s within our organizations today of people who have acquired these degrees, these skills that are no longer relevant. And I think this is a really big issue. And if you look at some industries in particular, you know, especially some of those essential industries, whether that’s construction or healthcare or Retail, we don’t see Gen Z gravitating towards them. And we have a, you know, a great tsunami happening where we’ve got baby boomers retiring at much faster rates than we do of new entries now this.

Frank Cottle [00:25:11 ]:
To reverse that trend.

Kelly Monahan [00:25:13 ]:
And Frank, I’m so impressed with that. I think we need more Franks out there doing this. And but here’s the reality. It’s only, this is what we talk about in the book. It’s only a skills gap if you’re ignoring the freelancer market, if you’re ignoring the fractional market today. It’s only a skills gap if you begin to look at this through a traditional full time employee model. We do have enough talent, we do have enough skills. They’re just not looking the way that the majority of executives expect them to look. And this is especially true as we start going down to the Gen Z and the Gen Alpha coming up. They’re looking at corporate America and they’re really second guessing. Is that what I want my career to look like? Is corporate America going to keep my skills relevant enough? Is there enough emphasis on me as an individual in my development? You know, the layoffs that are happening around us in mass and the tech category in particular is only perpetuating this narrative that Gen Zers today are telling us. I actually feel safer managing a portfolio of work, you know, whether that’s still having a full time job and becoming a fractional and offering my services as a freelancer. And so I think we’re at this profound time right now where the supply, the Gen Zers and Millennials even are telling us they want to work differently. They know the world of work is changing too fast. The majority of employers aren’t keeping pace and so they want to change the social contract. They want the flexibility, the autonomy and even sometimes in some cases the higher income that’s coming by working in a fractional way. But our executives and the way that we hire is still very much wired to really think about the market and the talent market as full time workers. And to me I think there needs to be a big mindset shift here if we’re going to actually solve the skills gap. Because it’s self inflicted in my mind. Leaders are self inflicting this by ignoring the alternative talent pool that’s out there.

Frank Cottle [00:26:57 ]:
You know, when you were at Meta, Meta was growing, is still growing. Yeah, fabulously. And that sort of thing. Meadow was building a lot of office space. Yeah, a lot of buildings, a lot of office space, that sort of thing. So they had maybe without Being in their direct employees, 5 or 10,000 part time workers that they hired as contractors to build an essential element of their company. And that was plumbers and electricians and drywallers, all the people involved in those trades. So when we talk about the future of work, candidly today, if I were to have the choice of going into business finance, that had a technology edge, yeah, I think I’d build a construction company or a plumbing company. I think I’d become a, a plumber. I would learn the skills because that is fractional work. It’s on demand. It is harder and harder to find. I can find anybody to build an app for me. I mean, apps are like belly buttons. Everybody’s got an app. Okay. So that’s easy. It’s really hard to find a good plumber. Really hard. So our trades coming back and when you look at the work that you guys do, how embedded are you are looking at the trades? Angie’s list, if you will, versus just the white collar side of things. Because I think more and more people are going to be necessary to support everything, the infrastructure that we have. And really the tradesmen that become artisans are necessary. And so there’s a path from intern or from apprentice to tradesperson to artisan. There’s a path there as well. Well, do you think that’s part of what we should be looking at when we talk about AI or when we talk about, in the larger context, freelancers, or should we just keep talking about white collar freelancers?

Kelly Monahan [00:29:25]:
You know, Frank, I think that’s such a wise question. And I think it, to me as a researcher, it’s becoming the heart of what I’m beginning to think about. Because if we do look at the labor markets, to your point, there’s an imbalance right now. If you talk to white collar workers, they seem to be struggling to find a job today. And yet if you are a consumer and to your point, you want plumbing, electric work, construction, we know how hard that market’s becoming to actually find talent to come in and service that. And I think what part of the problem is that? Because we’ve done this dichotomy and binary of either a white collar worker, you’re doing computer work, knowledge work, or you’re a blue collar worker doing some sort of physical work. We’re missing what’s actually becoming the fastest growing category, which is gray collar work, in between that relies on some sort of trade industry expertise, discipline. So, you know, whether you’re in healthcare or construction as example, you know, there’s a particular skill Set that you need to understand that only comes from either physical labor or some sort of apprenticeship or trade training. But then what is happening is you see the white collar profession, this knowledge worker, really being able to work alongside technology is being required more and more so in what we traditionally have separated as blue collar work. And so doctors as an example, are working more and more alongside robotics. Plumbers are working much more alongside cameras and various technologies that are coming onto board. And so what I’m looking at, what I think is most exciting for the freelancer market is that gray color category. And that’s what we actually see rising on our platform. So as a perfect example, what we saw is one of our fastest growing categories right now is specifically construction, project engineering and management, where people are coming in, hiring freelancers that are still able to do some of that computer work, still able to execute that work in a remote flexible way.

Frank Cottle [00:31:10 ]:
Project management, primarily because that is harder to do across borders. It’s harder to do not locally, but it is able to be done at least to some degree, not locally. So I can see that the actual trades I really have a hard time seeing.

Kelly Monahan [00:31:34 ]:
Agreed. The actual physical labor part of that, I agree with you.

Frank Cottle [00:31:37 ]:
Also deploying all variety of technology. I mean, you know, 40 years ago if you had a plugged up drain out in your yard, the plumber would walk up there and say, yep, tree roots, I’m pretty sure, and he’d dig it up. Today they’ll put a sophisticated camera system down the drain and say, yep, tree roots. And they’ll still dig it up, but they’ll know it’s tree roots and they’ll know where they are and they’ll be able to remove them more effectively. So probably terrible analogy, by the way. Probably terrible.

Kelly Monahan [00:32:14 ]:
You know, I think it makes sense. I mean, I think Frank, what would I would be so happy about? You know, I think for so long all these specialized skill sets has resided within the tech industry. You know, everyone wanted to go work in tech and at the end of the day we’ve made maybe life more convenient. But what I hope I begin to see happen because of the imbalance supply and demand, is those people with those tech skills or who have had this training start to look into whether that’s construction or healthcare or other industries that need this talent that actually I think will make our infrastructure better, our society better. And so I just, I hope to start to begin to see this swing, especially in the younger generation, to apply those technical skill sets in different domains.

Frank Cottle [00:32:55 ]:
We can hope.

Kelly Monahan [00:32:56 ]:
That’s a hope.

Frank Cottle [00:32:59 ]:
We’Ll find out soon enough, probably sooner than we think, especially if we’re watching for that data, you know, because we have a mantra in the company that says get the data becomes information which allows for knowledge, which creates action. Yes, get the data. That’s the foundational thing. So your statistics are data, we all rely upon it and everything. But in your own research, and you guys do a tremendous amount of this, your own background is amazing in that. What surprises did you find? What things you went, holy cow, I never expected that. Did anything come up skill wise, a new job description entirely for a new type of job that people should be thinking about or some overarching issue? You know, we didn’t know the sun caused radiation. Huge. Huge.

Kelly Monahan [00:33:55 ]:
Yeah. Well, I’m going to tell you, the one thing that’s continued to surprise me is, you know, as I think about, you’ve been, you know, well ahead of your time here of just thinking about flexible work and the true future of work is how much a leadership’s mindset is getting in the way of actually realizing this for larger organizations. So we’ve done a lot.

Frank Cottle [00:34:14 ]:
What drives that mindset? Perception of shareholder value or boardroom pressures for outside issues that have nothing to do with business?

Kelly Monahan [00:34:26 ]:
Yeah, I think it’s probably a combination. The reality is a combination of factors. Certainly short term pressure is part of this, but I think it’s an outdated way of thinking about contractors in the freelancer market. Because to go back to your perspective or what you said earlier about Meta, they think about contractors of, oh, that’s our food service, that is our construction, you know, not necessarily part of their core capabilities, where it’s, oh, we’re going to bring freelancers in who are going to help us from a software engineering perspective with product development, you know, help us from a financial aspect. And what I see happening in the data, and this is becoming just year over year, a pretty profound difference is if when we ask executives what’s the first word that comes to mind when you think about freelance talent, I can almost now begin to predict some of their performance if they answer the words such as fractional, contract, efficient, cheap. Those sorts of transactional words really, I think dominate a lot of executive hiring and the way that they think about freelancers. Now we’ve got about 23 to 27% of executives that use different words and they use words like creative, skilled, talented, human. And we see these very human, innovative type words come up to describe their freelancer talent. And that to me is explaining so much of the difference. We’re seeing today of companies that are getting ahead and they feel like they are prepared for AI or they do feel like they’re prepared to navigate the next six to 12 months. Have an extremely different mindset when it comes to freelance talent compared to the majority of peers. And I think they’re missing out. And as part of that, I think they’re beginning to fall behind when it comes to their own confidence of having the right skills within their organization to navigate the future.

Frank Cottle [00:36:08 ]:
Okay, you brought up a bunch of interesting words for two sides of an argument there. I’m going to throw up one, two issues that we see out there in the world and I don’t know if we even have time to address this or not. So I’m going to take a risk here. Return to office. We can’t manage our culture without everybody being in the same room at the same time. And we want our corporate culture to survive. Wait a second. Freelancers, corporate culture, how does that all lie together? Everything. We’re talking about corporate culture, corporate culture. No, wait a second. It’s. You’ve just cut the cord to corporate culture with freelancers. Okay. And people are so focused on corporate culture they have to drag everybody into two hour commutes and all sorts of silliness to have to be in the office. Because if I can’t see you, I don’t know what you’re doing. We’re talking like work theory that’s a hundred years old. And yet some of the biggest organizations, U.S. federal government, now, biggest organizations in the world, are demanding this. Where does that take it all? You’ve got five seconds to answer that.

Kelly Monahan [00:37:28 ]:
Okay, Frank, I’m going to answer this.

Frank Cottle [00:37:31 ]:
You can’t answer that. But that’s a question for us to end on. A question.

Kelly Monahan [00:37:36 ]:
Yes.

Frank Cottle [00:37:36]:
As we look towards the future of work, how do we rectify these things? And then I’m going to ask you if we can have another session at a point in time and deal with that or if we do a, an in depth article on that and really tackle that issue of the impact of freelancers and distribution of workforce relates to culture versus return to office culture and which is actually stronger and allows for those creatives that you were talking about, people that are self driven rather than whipped.

Kelly Monahan [00:38:17 ]:
Yes, Frank, I think that’s. I’m going to throw one more question out that we can explore and a follow up here. Whether that’s written or audio, I think so much of it comes down to the question of do people, do leaders think that people inherently want to work and do they trust them to work as adults and where and when.

Frank Cottle [00:38:37]:
I would start with trust.

Kelly Monahan [00:38:38 ]:
Yep.

Frank Cottle [00:38:40 ]:
And then I would ask the second question because what relationship can you possibly have without trust?

Kelly Monahan [00:38:50 ]:
That’s right.

Frank Cottle [00:38:51]:
And it is these. Forget employers trusting employees. Do employees trust the employer?

Kelly Monahan [00:38:58 ]:
Two way. Love that.

Frank Cottle [00:39:00 ]:
Let’s see. We’re going to euphemistically refer to our next layoff as a performance based analysis for continued employment. What a word salad. That’s a pile of stinky poo. Okay.

Kelly Monahan [00:39:19]:
People see right through that.

Frank Cottle [00:39:20 ]:
And yeah, so the trust has to go both ways. And I think honestly that that’s something that is been very hard hit recently for any number of good reasons where trust has been challenged overall. Gosh. Thank you. Thank you so much. I really appreciate it and we look forward to the opportunity of speaking again.

Kelly Monahan [00:39:49 ]:
I would love it. Thank you so much.

Frank Cottle [00:39:51 ]:
Take care.