Ep 26: The Impact of AI-Powered Platforms and Total Workforce Ecosystems with Ilyse Shuster-Frohman

[00:00:09] Hey, it's Bob. Thanks for joining me for another episode of Elevate Your AIQ. On today's show, I caught up with Elise Shuster-Frohman, co-founder of Mothership, and we delved into the evolution of work and the concept of a total workforce ecosystem. I first met Elise in a community of freelance economy advocates and founders, myself an advocate and Elise a founder. So I was excited to geek out on these topics with her. We explored the integration of AI in workplace technologies and workflows, the potential of fractional work, and the importance of comprehensive talent assessment.

[00:00:39] Our conversation touches on other important topics, such as leveraging former employees' expertise through talent communities and the challenges of adopting new workplace solutions. Elise and I also chat about the ethical considerations surrounding AI use, particularly when it comes to talent-related decisions. If you're curious about the growing importance and impact in the freelance economy and why it's becoming an essential component of your global talent strategy, along with some AI, of course, I think you'll appreciate my conversation with Elise. Thanks for listening.

[00:01:09] Hello, everyone. Welcome to another episode of Elevate Your AIQ. Today, I have with me Elise Shuster-Frohman from Mothership. How are you doing, Elise?

[00:01:18] Great, Bob. Thank you. How are you?

[00:01:20] I'm doing great. Thanks so much for being here.

[00:01:22] Thanks for having me.

[00:01:23] Very much looking forward to this conversation. I'm really impressed with what you've built with Mothership, and I want our listeners to hear all about it.

[00:01:31] But, you know, the bulk of this will be just your personal perspective and experiences of what you're seeing, what your clients are seeing, what your clients are asking for.

[00:01:41] You know, I think this is a really important set of topics around, you know, workforce ecosystems, freelance marketplaces for the future of work itself.

[00:01:50] So let's dig into it.

[00:01:51] But first, I thought you could just give our audience just a quick TLDR of your background and the impetus for creating Mothership.

[00:01:59] Thanks, Bob. Well, thanks for all the great compliments, you know, compliments to you as well for all the great work that you do.

[00:02:04] And, you know, you're so well-versed. And so, again, thanks for having me. I'm back at you.

[00:02:10] My pleasure.

[00:02:10] Yeah, of course. So my background is, you know, I hail from South Africa, so faraway land.

[00:02:16] So, of course, I've seen a few things and then immigrated to America back in 1996.

[00:02:21] And so that was a time where, you know, New York was ripe with flux and, you know, pre-Giuliani days.

[00:02:29] So it was just almost like being in South Africa, but just concrete fungal, you know, as opposed to, you know, as opposed to the real jungle.

[00:02:37] But there I just cut my teeth at, you know, FIT studying graphic design.

[00:02:42] I also have a marketing and communications degree.

[00:02:45] And I think, you know, if you think about a lot of what I do today, it's so tied to communications, really.

[00:02:51] And communication, Bob, is actually, you know, sounds like such a simple concept, especially when you deal with, you know, AI.

[00:02:57] But really, I always talk about connection and data connection.

[00:03:00] And really, that's communication to me.

[00:03:03] And so that's something that I never thought that I would necessarily translate in this arena.

[00:03:10] But, of course, I work for big corporates between New York and L.A.

[00:03:13] for all kinds of large enterprises from entertainment to one of the largest talent agencies out there, a United Talent Agency out in L.A.

[00:03:23] And so, of course, always managing people, teams, always just kind of seeing the breakdown and the silos and the issues around, you know, what was going on within the organization and what was going on within the individual.

[00:03:37] So I, you know, transitioned from there into opening up my own advertising and creative agency after working for all these large corporates that I mentioned, a few that I mentioned.

[00:03:46] And then bringing it all under one roof and creating this interface where essentially talent could be accessed by individuals, hiring managers, et cetera.

[00:03:56] And there was a huge flux in the market, a convergence going on at the time between what was happening with agencies and what was happening with corporations and how they were accessing talent and accessing project teams, so to speak.

[00:04:10] Right.

[00:04:10] And then also just seeing where technology was evolving and creating this direct connection and really what I call lifting the veil, taking down the Chinese wall, if you will, for lack of a better term.

[00:04:22] But really just breaking down the silos between those that did the work and those that needed the work done.

[00:04:29] And then, of course, it opened up this entire opportunity, which was to not just build very next generation technology that makes all of that happen, but goes so much further, but also creating what we call a total workforce ecosphere, Bob.

[00:04:46] It came to, you know, as the whole venture unraveled, you know, first we started out actually with a workspace concept, funnily enough, a micro workspace concept that we still have today.

[00:04:57] But, you know, of course, everything had to be tech enabled and that's where we built out our platforms.

[00:05:02] And then as we've evolved throughout rolling that out first as a marketplace and now as an actual SaaS product that can be white labeled within any organization, we've now built out this network opportunity that connects this ecosphere and that also brings workers and people together with all the things that they really need.

[00:05:21] And, of course, it's a giant vision.

[00:05:23] It's a massive undertaking.

[00:05:25] We've got foothold with placing people in every which way for large corporations, for a very large enterprise.

[00:05:31] And now with our technology getting deployed into these organizations as a white labeled solution, also having those organizations access our tech as an external solution and just seeing how market ready everything is right now for, first of all, that to operationalize.

[00:05:49] And then, of course, the additional ecosphere to operationalize behind it.

[00:05:53] Wow. That is a lot that you've put together over these last, what, seven or so years? Is that right?

[00:06:00] Yes, exactly. That's all the numbers.

[00:06:03] So when you say ecosphere, is that what you consider multiple ecosystems or is it more than just the sort of, you know, talent pools and things like that?

[00:06:12] Like how would you define the ecosphere?

[00:06:15] Right. Well, you know, well, our tech, you know, to start with is a total people platform.

[00:06:19] So there it's a nine module suite covering credentialing, search and match.

[00:06:24] So really just disrupting the old school way of hiring, replacing the resume and replacing the old school process of finding people first and foremost.

[00:06:32] Right. Let's create a network, search and match opportunity.

[00:06:35] And then we have a workflow module, productivity intelligence, you know, manage, you know, essentially AI management and also management intelligence as well.

[00:06:45] You know, that is all tracked and managed there.

[00:06:48] And then it goes through to payments, development, of course, upskilling, cross-skilling, reskilling.

[00:06:52] And then we get into mobility as well.

[00:06:55] And these are all within each organization.

[00:06:57] So each organization has their own workspace.

[00:07:00] Each organization has their own community of workers.

[00:07:03] Each organization is either engaging those workers every which way, if they're next gen and if they're really, you know, with it and, you know, maximizing the resources they have before they go externally to find more.

[00:07:15] But that's not enabled properly yet.

[00:07:17] Right. There's still so much waste, so much haste.

[00:07:19] And then it's, of course, not operational efficiency around running communities.

[00:07:24] So we start there.

[00:07:27] And that's where we're deploying these environments.

[00:07:29] Our external solution, our external marketplace catches everything when it leaves the four walls of that organization and allows for this internal, external opportunity where data breaks are not happening, where people are not just like checked at the door.

[00:07:44] Sorry, you got laid off and now leave our community, leave our talent pool.

[00:07:48] I mean, just because you're not employed there doesn't mean that it's in their best interests or in yours to completely leave their community.

[00:07:55] Right.

[00:07:55] There's a way to create stickiness and to create, you know, to continue the relationship.

[00:08:00] Right.

[00:08:01] Because you never know.

[00:08:01] And because there's a lot of reasons that I'm not going to bore you with today.

[00:08:06] But if you're interested, you can find out.

[00:08:08] But just to answer your question succinctly, that is where the ecosphere and the network, first and foremost, is most important.

[00:08:15] And then, of course, our workspace, the workspace of our clients, all the dormant workspace out there.

[00:08:21] We know there's plenty of it.

[00:08:23] And then at the same token, the supportive modules, the mentorship, the networking, the wellness, the support, the personal support.

[00:08:31] And then bringing that to the table from a consultative standpoint is something that, you know, we offer, but we'll offer even more so as we kind of, you know, really have these other pieces really built out and operationalized.

[00:08:43] But that is where everybody doesn't just need to get operationalized and networked.

[00:08:48] They also need to be supported inside and outside of the four walls of an organization for all the reasons that I just mentioned.

[00:08:55] Is it safe to say that you're getting a lot of clients who look at the complexity of everything you just described and they say, if only there was one platform that could do all of these things to reduce the complexity and the friction and the context switching and all of these things, right?

[00:09:18] I mean, it seems like you're taking the place of, like you said, those nine modules could be a significant undertaking, assuming you even had the budget to take on and implement all of those things, which I imagine not every organization does.

[00:09:36] That would be a multi-year implementation to even get it out there, let alone the additional time it takes for mass adoption, I suppose.

[00:09:46] You know, it's a great point, Bob, because I always scratch my head when I hear about the multiple years that it's going to need, you know, to do this.

[00:09:54] And, you know, but at the same time, you're right.

[00:09:57] You know, this is not a small undertaking.

[00:09:58] You know, it's not something that we should scoff at and not something that necessarily is simple.

[00:10:04] But, you know, with our platform, it's really about, you know, uploading an Excel sheet of your entire workforce and they will be credentialed and they will be onboarded into the system, into the platform.

[00:10:16] And they can be operationalized from there in a matter of minutes, depending on how much data you have.

[00:10:24] But really quickly, you know, this isn't a matter of needing to do it over a long period of time.

[00:10:29] I think what takes a long period of time, to your point, is just getting all the stakeholders to understand this whole new, what we call an expert system, as much as we call it an ecosphere.

[00:10:40] It's really an expert system for them to understand, oh, you know, this is like a whole other way of doing things.

[00:10:46] And then talking about operationalizing spend, first of all, there's a lot of rogue spend that's happening within these organizations anyway,

[00:10:52] because the hiring managers or the heads of these departments are already hip to these better, badder ways of doing things, these quicker, more efficient ways of doing things.

[00:11:02] So now internal stakeholders are trying to catch up and get things, you know, into place.

[00:11:08] And I'm a little bit surprised by why it would take so long and require so much.

[00:11:15] I think it's about perhaps unraveling relationships, perhaps unraveling, maybe some people feel bad that they brought something in that is now, that was very expensive, that now might be a bit obsolete.

[00:11:26] Or, you know, and of course, it also has to do with operationalizing the data, right?

[00:11:31] So what we do there is we allow for API opportunity, where they can bring it in first, they can operationalize it with their communities, they can API into these systems.

[00:11:40] They don't have to ever abandon these systems, they can keep them around.

[00:11:44] But day one today, I think they should at least be running it as a people platform for their community.

[00:11:50] And to wait a year or two really boggles my mind.

[00:11:53] Although, yes, it's a lot of what we see everyone needing as, not everyone, but certain organizations, especially large enterprise meeting as an expected timeline.

[00:12:03] But I think that that's perhaps perception, not reality.

[00:12:07] How do we change the perception?

[00:12:08] And what do you think about that?

[00:12:10] Yeah, I think behavior change always takes longer than we might anticipate.

[00:12:14] I mean, you have diverse audiences, sometimes there are people that need to be dragged along, or they want to see, you know, results for themselves before they, you know, a certain people manager takes it on for themselves, or you still have cultural things around.

[00:12:30] The inhibitors we've seen with talent marketplace adoption, in general, right?

[00:12:36] Like talent hoarding, and do we also change the, you know, the incentives for managers to see their employees, you know, thrive, even if that means having to leave and take on another opportunity.

[00:12:49] It could be, you know, the integration of skills, trying to shift to, you know, skills-based hiring and skills-based organizations.

[00:12:57] I think there's always, there's always something.

[00:12:59] I mean, you spent time in large organizations, as I have, and it's just seems like there's, you know, there's the behavior change, there's competing priorities, there's sort of tug of war for budget sometimes, right?

[00:13:10] You've got one pool of money that everyone could be fighting over.

[00:13:16] And you've got to handle, you know, the must-dos before the should-dos.

[00:13:20] But I do think there's a lot of things that you can't anticipate, and nothing moves as fast as you would like the bigger the organization gets, it seems.

[00:13:29] But I liked what you were saying about the talent, you know, just because you have to make, you know, an uncomfortable decision about talent based on economic, you know, circumstances or business performance, et cetera.

[00:13:41] It doesn't mean that that person should just be kicked off the island, right?

[00:13:46] This person was loyal.

[00:13:47] They were a great teammate.

[00:13:49] They had leadership qualities.

[00:13:50] They checked all these boxes, and, you know, circumstances changed, and now they need to find something else to do.

[00:13:56] Well, there's no reason why you shouldn't maintain some professional, you know, relationship with them because you never know how the pendulum may swing the other way or the circumstances were such that, you know, you're going to spin up a new project or build a new product, and this person would be perfect.

[00:14:14] I mean, that's part of having a dynamic workforce ecosystem, right, is being able to understand when you've got sort of a utility player whose time.

[00:14:25] Hey, this is William Tencup, work to find.

[00:14:28] Hey, listen, I'd like to talk to you a little bit about Inside the C-Suite, the podcast.

[00:14:32] It's a look into the journey of how one goes from high school, college, whatever, all the way to the C-Suite, all the ups and downs, failures, successes, all that stuff.

[00:14:42] Give it a listen.

[00:14:43] Subscribe wherever you get your podcast.

[00:14:47] And then, you know, I think that's a great thing.

[00:14:52] I think that's a great thing.

[00:14:58] So I think people lose sight of that in talent acquisition in general because I see the struggle with even candidate, you know, rediscovery, let alone employee sort of rediscovery and tapping into alumni networks and things like that.

[00:15:12] Right. So the talent acquisition cost on that is massive.

[00:15:15] So we talk about spend and everybody protecting spend.

[00:15:18] And the problem is no one, everyone has never spent more than they do today, in my opinion, on a lot of unnecessary things that are, you know, overcomplicated as to why they can't, you know, be dismantled for something simpler, right?

[00:15:33] Right. But, you know, the and I talk about this a lot, the redundancy, the inefficiency of spend.

[00:15:38] And now we've got rogue spend and it's just spend, spend, spend right all over the place.

[00:15:42] But the point is there's a knowledge effect to that.

[00:15:46] Right. So I love your hopping galaxies T-shirt, as I told you on the beginning of our call.

[00:15:49] But it's a great analogy for what we're talking about right now.

[00:15:52] Right. That, you know, these the talent is hopping around.

[00:15:55] Right. And so what a bad strategic decision to, you know, and I was just actually before this interviewing John Healy, actually, on my podcast.

[00:16:04] So sorry, everybody, if I'm wearing the same outfit.

[00:16:08] But, you know, but at the same time, you know, what we were going to bring up there, we talked about a lot of things, but we talk about what the individual owns as their data.

[00:16:19] You know, we have a credentialing module.

[00:16:21] It goes with the worker.

[00:16:22] It's actually a data wallet that the worker can keep, replaces their resume and it tells a whole, it's a whole three-dimensional persona of the person.

[00:16:29] You know, so that's their data, right?

[00:16:30] That's what they own.

[00:16:32] They came with.

[00:16:33] They also come with a certain amount of knowledge to an organization.

[00:16:37] And then together with the organization, they gain more knowledge.

[00:16:41] And the organization oftentimes invests in that individual and they both contribute, right?

[00:16:47] I mean, of course, it's a fair trade.

[00:16:49] They're getting essentially paid for their knowledge, right?

[00:16:52] But the knowledge is not completely transferred to the organization.

[00:16:56] When that person leaves, guess what?

[00:16:59] But the knowledge that you invested in them to achieve and that you essentially gave them walks out the door.

[00:17:07] The point is, what a bad investment, right?

[00:17:09] Like, why would you want that knowledge under any circumstances unless it is, of course, you know, somebody was fired or there was a real issue or there was, you know, something that was obviously you couldn't come back from.

[00:17:20] Why would you want to completely disconnect from not just that individual for the talent acquisition cost, that you might have to go find them again, or for all the other expertise that can bring your organization even on a consulting basis, on an IC level.

[00:17:33] I mean, there's so many other ways to leverage this amazing individual to, you know, stay close to them.

[00:17:40] And then at the same time, to also leverage the amazing knowledge that you have passed on and not just let it walk out the door to actually be able to still have it be something that you could leverage ongoing.

[00:17:54] And I think that's very valuable if you agree.

[00:17:56] Yeah, no, absolutely.

[00:17:57] I guess it brings up an interesting point around how that knowledge is captured and potentially disseminated.

[00:18:03] But even today, you know, as people think about how to implement, you know, generative AI within their organization, there has been a, I guess, it'll probably be an ongoing debate about knowledge work in general, right?

[00:18:18] And if you do have people, let's say for argument's sake, that you do have a lot of people who don't just have a lot of knowledge, but they document that knowledge.

[00:18:27] Now that's training data for the AI, right?

[00:18:31] And so I think there's this flip side of this knowledge equation about having that tacit knowledge, the institutional knowledge, and that knowledge transfer, the knowledge sharing with the rest of the organization.

[00:18:43] And now you can basically, you know, codify that.

[00:18:47] And what are the implications of that for the future of knowledge work?

[00:18:51] And how does that adjust the needs that I have when I do go look for talent, right?

[00:18:56] So I know I kind of completely switched gears on you there, but I do think it's important to think about as you go out and you try to figure out, well, I've got this set of tasks that today we call a role.

[00:19:09] We're going to write up a job description for that role.

[00:19:11] But based on the tasks, if I break it down into tasks, and then I look out across that ecosphere of what is the optimal way to actually execute those tasks based on the context and the workflows that those tasks are a part of and things like that, then I get more granular and hopefully smarter about how I actually execute some of that work.

[00:19:35] And it may be through, you know, a full-time employee, it may be through a contractor or a freelancer, or maybe there's an AI agent that can handle some of those things.

[00:19:46] Right. And so knowledge, intelligence, right? It's the same thing.

[00:19:50] And then I always come back to, well, it's also data, right?

[00:19:53] And so, I mean, we have workflow tools on our platform.

[00:19:56] So you can, you know, so the credentials, matches, workflows, pays, develops and mobilizes, right?

[00:20:03] So you're catching all of that intelligence within the platform as it's internal to your organization.

[00:20:09] You know, with Mothership, we have it external with our people.

[00:20:12] And, you know, of course, there's a lot of compliance and risk around all of it for all of us as well.

[00:20:17] But the point is that it does, it brings up a great point, one that I think about a lot as to who really owns intelligence.

[00:20:24] And I think it's going to become something that's going to be a much bigger thing, of course, as, you know, our platforms are machine learning and large language model backed.

[00:20:34] But they also have a built-in ethical construct, which we take very seriously, right?

[00:20:38] And, you know, we have to do it that way.

[00:20:41] But at the same time, we have to also define and start to define the ownership of IP more than we ever have before.

[00:20:50] And the IP is not just tied anymore to a document.

[00:20:54] It's tied to the person, right?

[00:20:56] This is where the intelligence is literally in someone's head, not necessarily just in a file anymore.

[00:21:03] So we track the files.

[00:21:04] We track all of that.

[00:21:05] We track all of that, of course, so that there is some, you know, the guardrails.

[00:21:09] There are guardrails around that kind of IP.

[00:21:12] But this intelligence IP, you know, the network creates guardrails and some sort of trackability and we'll get more intelligent with that as time goes on.

[00:21:21] But the question of ownership, Bob, I find that to be really interesting just as it pertains to AI in general.

[00:21:27] I mean, you know, our clients can, of course, build their own LLMs and their own intelligence.

[00:21:31] But again, it sits with the people and people move.

[00:21:35] And who's to say what's not the people's and what is the organization's?

[00:21:39] The delineation of that, I think, is very interesting.

[00:21:42] I think it's going to get a lot more complicated, don't you think?

[00:21:46] I mean, I'm glad you brought up the responsibility pieces because, of course, I was going to bring that up at some point.

[00:21:52] But in this case, I think it's really fascinating and difficult to ascertain where you draw the line based on these micro contributions,

[00:22:06] potentially to different projects that are under different entities.

[00:22:12] Right. If I'm freelancing or doing fractional work and I'm splitting my time across five organizations and I'm just trucking along and I've got these workflows and I'm just popping ideas and thoughts and knowledge into these different things.

[00:22:28] I mean, you actually need, I guess, similar to traceability and the observability of data as it goes through these algorithms and these AI tools.

[00:22:38] Similarly, you could have the need for the traceability, similar level of traceability for intellectual property as it flows through.

[00:22:46] I mean, that could get, seems like that could get ugly.

[00:22:49] Right. Exactly.

[00:22:50] And that's where I think law firms are quite worried about how this is all going to play out.

[00:22:56] And, of course, they're having a lot of debriefings and, you know, there's a lot of roundtables going on, Bob.

[00:23:03] You know, everyone's having a roundtable now to, like, you know, figure a lot of things out.

[00:23:07] Right. I mean, this is like epic stuff.

[00:23:10] This is just really evolutionary in my mind.

[00:23:12] Right. And so this is, you know, I would say giant leap for mankind.

[00:23:15] Right. It's a really giant leap.

[00:23:17] Right. Of course, we've got all the space lingo, the final frontier.

[00:23:20] You know, we go there.

[00:23:22] But that's really the gravity of it.

[00:23:25] But at the same time, hopefully not that serious.

[00:23:28] And I don't think so doomsday.

[00:23:29] Right. I do.

[00:23:30] I always believe there's good that comes out of the bad.

[00:23:32] So even if it looks like it's bad, I really ultimately think it'll be good.

[00:23:36] But I think that the fact that everyone can access such knowledge and such intelligence,

[00:23:42] I think, is going to serve us more than it's going to hurt us.

[00:23:45] And I think that's the ultimate thing to keep in mind.

[00:23:48] Right. That we will figure it out.

[00:23:49] The parameters, the guardrails.

[00:23:50] Maybe we've been holding on to things too tightly to, you know, not to our benefit.

[00:23:56] Right. And so I think that's going to be interesting.

[00:23:58] Yeah. No, I think that's a really, really good point.

[00:24:00] I think we've been maybe over-legislating or over-litigating on some of these things.

[00:24:06] And people have been sort of nitpicky, just the nature of this society that we live in,

[00:24:12] at least in the United States.

[00:24:13] But I do think that the recent developments around like these AI agents and this,

[00:24:19] what people call this agentic workflow is really an interesting concept.

[00:24:24] And I do see tremendous potential for that, especially as we move away from this sort of

[00:24:32] fascination with individual productivity.

[00:24:34] And we really start talking about, you know, where much greater value can be obtained,

[00:24:39] you know, by stringing these tasks together with some level of intelligence,

[00:24:44] as well as just to support decision-making and not just, you know, sort of task execution.

[00:24:51] And I wonder how you think about that in the context of mothership and how, you know,

[00:24:56] talent is sort of pulled in and out of different projects and stuff.

[00:25:01] We've always led with being a total talent organization for that reason, right?

[00:25:05] I mean, some people go very niche into just 1099 ICs.

[00:25:09] Some people go very deep into W2ers, contingent or full-time.

[00:25:14] And then, of course, there's the whole SOW thing.

[00:25:16] So we do it all, right, because we have a construct to do that and we have tech to do that

[00:25:21] and we have operational efficiency to do that.

[00:25:23] But we do it with purpose because oftentimes, Bob, it's the same person.

[00:25:27] And as the years are going to go on even more so, it's the same person.

[00:25:32] And then, of course, for that turnkey total talent solution for the client, for the talent,

[00:25:36] right, it's like, you know, those siloed systems, those niche solutions that now everybody has to

[00:25:40] reapply to be involved in that marketplace that just handles this kind of hire, right?

[00:25:45] And that's also where the network effect comes in is that those guys can all come to the table.

[00:25:49] They can all be part of the ecosphere.

[00:25:51] But, you know, it still needs to be, I think, part of a central system, a central solution,

[00:25:56] an expert system that's at least centrally accessed, right?

[00:25:59] And centrally, you know, standardized, right?

[00:26:02] Which I think really helps everybody to not have to relearn tech every single time they're

[00:26:07] trying to engage somebody, right?

[00:26:08] And then at the same time, not have to redesign their resume or redesign their persona for

[00:26:14] every single marketplace, right?

[00:26:16] And for every single job, you know, application.

[00:26:19] Also, as I always say, they don't even have to apply to jobs.

[00:26:21] They can just be discoverable on the network.

[00:26:24] So I think that, you know, the total talent opportunity for us is something that, you know,

[00:26:28] we care about because it's about everybody being able to get a job every which way, globally,

[00:26:33] at any time.

[00:26:34] And then, of course, the whole supply thing is what that was born from, right?

[00:26:39] It was also about, hey, guys, you know, like there's just not enough real, like there's

[00:26:43] not enough people and skills out there to do, you know, just niche point solution things.

[00:26:48] Like we really need to, you know, be sustainable and recycle, for lack of a better term, what

[00:26:53] we have and really just diversify skill sets, get more, you know, before we think about, you

[00:26:58] know, machines and robots and all the things that, you know, I think we need anyway,

[00:27:02] because humans only want to go so far and should only be expected to go so far.

[00:27:08] I think humans have been expected to be machines for too long.

[00:27:10] And that's a whole separate topic.

[00:27:12] I'm going to cover that as well.

[00:27:14] But, you know, outside of just the fact that they, you know, that we need this, you know,

[00:27:18] machine, if you will, you know, modus operandi for certain tasks, for certain things that

[00:27:23] humans are just broken over, right?

[00:27:26] At the same time, we're really not utilizing all the amazing things that humans are able

[00:27:31] to do. And that means that a person can be an IC and a full-time worker and perhaps a

[00:27:36] contingent worker all in the same week, sometimes even in the same day, Bob.

[00:27:40] And what that means for them is not only that they're able to not be bored and do different

[00:27:46] things and, you know, utilize, you know, the whole brain, right?

[00:27:49] Not just, you know, a part of it, right?

[00:27:51] And utilize all their skills, but the market is able to access all of this richness of

[00:27:56] supply and operational efficiency all around.

[00:28:00] I love that.

[00:28:01] And I think that that's obviously something that we've seen as a problem and it's not

[00:28:05] necessarily tied to birth rates.

[00:28:07] Right, right.

[00:28:09] I...

[00:28:09] Before we move on, I need to let you know about my friend, Mark Pfeffer and his show,

[00:28:15] People Tech.

[00:28:15] If you're looking for the latest on product development, marketing, funding, big deals

[00:28:21] happening in talent acquisition, HR, HCM, that's the show you need to listen to.

[00:28:28] Go to the Work Defined Network, search up People Tech, Mark Pfeffer, you can find him anywhere.

[00:28:36] Totally appreciate and respect that perspective.

[00:28:39] I think similarly in terms of how...

[00:28:42] Well, it goes back to human potential, right?

[00:28:44] And your human potential is not your perfect fit for this job that somebody made up the

[00:28:50] title and somebody decided that this is the best way to describe the work that's going

[00:28:55] to be done.

[00:28:56] Not necessarily thinking that, you know, in a month, this job is going to change or morph

[00:29:02] and that we've got other things that need to get done and then we're going to have to

[00:29:05] open another rec.

[00:29:07] It just seems so logical to me to sort of decompose some of what we consider, you know,

[00:29:13] roles today and then find a way to, like you said, maybe in the morning in working with one client

[00:29:20] on a design thinking workshop.

[00:29:22] In the afternoon, I'm running a lunch and learn on AI, you know, readiness and upskilling.

[00:29:29] And then in the afternoon, I'm doing, you know, product strategy.

[00:29:33] So that's the best way to utilize.

[00:29:35] And I mean, you want me to bring my whole self to work?

[00:29:38] I'll do that, but I'll do it in pieces.

[00:29:40] And that work will be for multiple, you know, employers, basically.

[00:29:45] And it's an earnings and spend choice, Bob.

[00:29:48] You know how it is, right?

[00:29:49] Some people, you know, you and I have worked in corporate where it's like, no raises this

[00:29:53] year or, you know, no more heads are open.

[00:29:55] So you're just like limited, you know, that, that, you know, we'd call it the glass ceiling,

[00:29:59] but really it wasn't just for women, right?

[00:30:02] This was like about everyone has a limit, right?

[00:30:05] Like the organizations have a limit to how much they want to spend on a certain hire.

[00:30:10] And so, you know, the people that work for them are limited by how much they can earn,

[00:30:13] right?

[00:30:14] So there's a lot of animosity around that.

[00:30:16] There can be a lot of issues around that, you know, you know, a lot of things get stolen

[00:30:20] because of that, you know, people are just really just trying to earn more within a construct,

[00:30:25] trying to get water out of a stone, so to speak, Bob, right?

[00:30:28] So this just opens that up where it's like, it stretches everybody to the point where they

[00:30:33] become unlimited earners.

[00:30:34] They don't have to just rely on this one source of income.

[00:30:38] And the corporation doesn't have to have the pressure of being that one source of income

[00:30:43] that is constantly feeling like they need to be stretched beyond what they're able to

[00:30:48] give.

[00:30:48] And so I think as long as it's comfortable for everybody, this just gives that extra room

[00:30:53] for, you know, that unlimited possibility and taking away those limits that have, I think,

[00:30:59] been a source of frustration for both sides.

[00:31:01] Oh, I love it.

[00:31:02] I had a question for you about the way that you sort of assess and vet talent on behalf of

[00:31:10] some of your clients.

[00:31:11] And part of it is acknowledging that what you've built basically takes the place of not just

[00:31:19] multiple sort of technology solutions and tools, but also potentially multiple entities, meaning

[00:31:28] you don't necessarily need an employer of record to bring in, you know, international talent.

[00:31:34] You don't necessarily need a vendor management system to bring in, you know, whatever type

[00:31:41] of, you know, VMS you're using to pull in folks through staffing agencies.

[00:31:46] And you don't necessarily need to also have an internal marketplace and a freelance marketplace

[00:31:53] that maybe you use to supplement, you know, for your workforce with short-term projects

[00:31:59] or whatever.

[00:31:59] So you've basically amassed, you know, one solution that bridges all that.

[00:32:06] But when it comes to the talent itself and the fact that they don't need to submit resumes

[00:32:12] anymore because your profile is there and you've done some pre-vetting, I'm just curious

[00:32:16] about the assessment of both hard or what we used to call hard and soft skills.

[00:32:23] So that could be technical skills, cognitive skills, you know, behavioral assessments.

[00:32:28] I'm just curious about how that might work because today, not only do you have that fragmented,

[00:32:36] you know, sort of ecosystem or ecosphere, but you have inconsistencies in the way that

[00:32:41] talent is vetted.

[00:32:43] You're a hundred percent right.

[00:32:44] And so some people think, oh, this is super important, you know, and then other people

[00:32:48] think, no, no, this is really important.

[00:32:50] And the truth is it's all important because it all makes up the person.

[00:32:54] So we designed it very, very carefully and it took us, you know, time to really, and we

[00:33:01] learned a lot, Bob, also just from doing, you know, the business that we do today and

[00:33:07] that we've been doing along the way, right?

[00:33:09] Just kind of seeing like, what's, you know, what are, what's really important in the process,

[00:33:13] you know?

[00:33:13] So we had a front seat at the table, if you will, to really say, okay, this is really

[00:33:18] what makes a difference here.

[00:33:20] This is really what, you know, and there's such a life sciences side to all of this, right?

[00:33:26] At the end of the day.

[00:33:27] And I say, there's a, there's a data science to this, right?

[00:33:30] This is really what we need to, you know, the lens that we've designed this from and

[00:33:35] that we've looked at this from.

[00:33:36] So, you know, we take in hard skills, soft skills, culture fit, we go very, very deep

[00:33:44] and wide and we have multiple sections to our credentialing module.

[00:33:49] People can go as far with it as they want.

[00:33:51] We, we obviously, you know, encourage people to complete the whole thing.

[00:33:55] And then once you complete it once, it just will update in real time and attach to any system

[00:34:00] and attach to any process so that, you know, you don't have to keep updating it.

[00:34:04] But the point is, you know, you want to give employers a full picture of yourself.

[00:34:08] You want to, because it's going to help you to find that right match.

[00:34:11] So this is where it gets compared a little bit to dating.

[00:34:13] And, you know, I think we should have like a mothership dating app one day when we have

[00:34:17] some bandwidth, you know, maybe we can solve that too, Bob, but we got our hands full here.

[00:34:21] But the point is, you know, that stuff's not sophisticated yet either.

[00:34:25] I mean, this credentialing module can actually tie into those systems too.

[00:34:28] Why not?

[00:34:29] Right.

[00:34:29] It can attach to, you know, Bumble and whatever else, you know, because again, it goes with the

[00:34:33] person.

[00:34:34] It goes with the person.

[00:34:35] And so what a great thing.

[00:34:37] I mean, we love it from even a personal security standpoint.

[00:34:40] This isn't just about work for us, right?

[00:34:41] This is about really getting to know someone.

[00:34:43] So hard skills, soft skills.

[00:34:46] Of course, all the verification of all of that is major, right?

[00:34:49] People might see themselves one way.

[00:34:51] And then, of course, you also want to make sure that the market can quantify that and

[00:34:55] also agree with it from a work standpoint.

[00:34:59] Institutional information, super important, you know, education, et cetera.

[00:35:03] But the sections are a little bit, you know, too many to mention.

[00:35:06] But, you know, of course, DE&I is part of it.

[00:35:09] But what we've really done is designed a process that essentially takes in all the data points

[00:35:14] of a person, hard skills, soft skills.

[00:35:16] And by soft skills, I mean also the life sciences side of the individual.

[00:35:20] Yeah.

[00:35:21] No, I think that's great.

[00:35:22] I do think that, you know, the more information you can provide in an honest way, you're that

[00:35:30] much more likely to have a sort of win-win successful and long-term relationship.

[00:35:35] So to me, these like lazy apply, you know, AI tools is like the antithesis of that.

[00:35:44] Like these people are applying to jobs.

[00:35:45] They didn't even know they could be getting calls back from the employers.

[00:35:49] They didn't even realize that they applied to these jobs.

[00:35:52] And they're annoyed.

[00:35:53] They don't even want to be contacted.

[00:35:54] Yeah.

[00:35:55] It's so stupid.

[00:35:56] We're just feeding this monster, this dysfunctional, you know, process that has existed forever.

[00:36:02] And we're not using technology.

[00:36:04] This is where I get hung up on how we're using technology to solve real problems.

[00:36:10] And those kinds of solutions just don't.

[00:36:13] They just perpetuate a lot of the nonsense and dysfunction that we see in talent acquisition.

[00:36:18] So I'll digress on that point.

[00:36:21] But I do think, you know, everybody wants, you know, a healthy, you know, relationship.

[00:36:26] And if the best thing for both parties or all parties is for you to just work fractionally on a project or to be, you know, in the office versus remote.

[00:36:38] I mean, there's all kinds of things that you can hash out so that you're contributing your best to potentially multiple projects for multiple clients.

[00:36:50] As long as you're in it for the right reasons and as long as you're, you know, contributing value to the project and to the team.

[00:36:57] So, yeah.

[00:36:58] So I totally respect and appreciate that perspective.

[00:37:02] Just more generally with some of the latest technology.

[00:37:08] I mean, obviously, generative AI is sort of at the center of that.

[00:37:12] I was just curious how you use it, not necessarily embedded into, you know, the Mothership platform, but just you personally.

[00:37:21] I mean, how you use it as a founder running a startup and maybe even in your personal life, how you're, you know, upskilling yourself and using it to be more productive or to, you know, make better decisions.

[00:37:36] Thanks, Bob.

[00:37:37] You know, it's a great question.

[00:37:38] I use AI when I need to, but, you know, honestly, I've been a little frustrated at times when I have used it.

[00:37:45] That's why I can't wait for, you know, I mean, our advanced AI is called Supernova and it's something that will be really fully born with our expert system.

[00:37:55] And as we get, you know, global adoption, you know, like we really need, you know, that level of intelligence to get there.

[00:38:03] And we've already, you know, got all these inroads for that product, but that's the product that I really look so forward to tapping into because truthfully, the AI, and this is where general AI to me is great as assistive.

[00:38:18] You know, it's great for, you know, just kind of maybe like, you know, spitting out an email or spitting out a letter that, you know, maybe you just feel like, oh my God, I just can't write this up today.

[00:38:27] You know, let me just prompt the system and get something that at least is a framework.

[00:38:30] But honestly, Bob, I don't use that as much as I would like to because the times that I have really utilized it, I found it to be not intelligent enough.

[00:38:40] Honestly, I think it gives a good framework for here's something written or I get emails all the time, you know, and I could tell when it's written by AI.

[00:38:48] Right. And it kind of like, instead of, you know, it dummies it down.

[00:38:52] I mean, there's certain things that make it great.

[00:38:54] Right. Where it's like, oh, it'll cite all these things about you that, you know, the person couldn't possibly know, you know, if they're going to write this at scale to this many people.

[00:39:02] Right. So that'll cite my background and what I've been doing and what have you.

[00:39:06] And so it really does give this personalized touch to the communication.

[00:39:10] But the point is that we're humans are intelligent enough to know it wasn't coming from you.

[00:39:17] Right. This isn't like you really did.

[00:39:18] The impressive part of that would usually be that this person did their homework.

[00:39:23] They did the homework. Right.

[00:39:24] To tell me. And so now that gets lost a little bit, but, you know, still having those data points and that detail there is a huge time saver.

[00:39:33] So I would always, you know, love to utilize it more in that way.

[00:39:37] I'm just really hell bent on being an original.

[00:39:42] And that's where I observe it.

[00:39:45] I work with it.

[00:39:46] Of course, we, you know, we're very entrenched with, you know, AI here at Mothership.

[00:39:49] But at the advanced kind is really what I really see the most value in outside of general.

[00:39:58] Although I think, again, the assistive part shouldn't be snuffed at by any means.

[00:40:03] I would say I have not had consistently great results from a lot of the tools that I've played with.

[00:40:10] So I understand where you're coming from.

[00:40:12] I'm also not like a sales and marketing person.

[00:40:16] So it's not like I have a lot of outreach and drip campaigns coming out of my CRM, at least not yet.

[00:40:23] But one of my hesitations is like, it just seems like it's going to sound so impersonal on top of potentially robotic in a way.

[00:40:32] Right.

[00:40:33] So I can do the, you know, what we used to call a mail merge and say, you know, dear Elise and whatever.

[00:40:39] And I could say, oh, how are things in Miami?

[00:40:42] And, you know, yeah, you can just insert, you know, keyword here.

[00:40:46] Right.

[00:40:46] But it's not the same.

[00:40:48] And, you know, the recipient will often, as you have, see right through it.

[00:40:54] And it's just, I don't know, how do you, I guess everything is about balance.

[00:40:58] Right.

[00:40:58] How do you balance efficiency?

[00:41:01] There's only so many hours in the day with technology and yet somehow still make it feel, you know, personalized and customized.

[00:41:10] And so I think it really just goes back to what your use case is.

[00:41:14] I mean, I do, you know, if I use some of the terminology, literally, I mean, co-pilot, everybody could use a co-pilot.

[00:41:21] Right.

[00:41:22] In theory, if it alerted you to things that you forgot about or gives you a perspective that you hadn't considered, you know, like a thought partner or, you know, brainstorming partner and things like that.

[00:41:35] But in terms of just writing things or summarizing things, I think we have a long way to go with some of those things.

[00:41:42] In fact, if I put the transcript of this recording into a couple different AI tools, the output's going to be very similar.

[00:41:51] So there's not even, you know, uniqueness within a particular platform, meaning a particular LLM, like a lot of the LLMs based on how they're trained.

[00:42:01] They're going to put things into similar contexts and frame things a similar way and whatever.

[00:42:07] It just, it is already starting to be a lot of sameness, I guess.

[00:42:13] Right.

[00:42:14] It's not individualized.

[00:42:15] And that's where I'm such a proponent of human intelligence being so spectacular.

[00:42:22] Right.

[00:42:23] And that's where I always talk about supernova being really about artificial super intelligence.

[00:42:29] Right.

[00:42:29] Where this is like human intelligence and, you know, you put that together with a machine.

[00:42:34] Okay.

[00:42:35] Like now you've really got something.

[00:42:36] But like just, just as a machine, because, you know, humans are downloading new intelligence every second.

[00:42:42] We've got, we've got a, an unlimited source for our intelligence.

[00:42:46] You know, there's, there is a limit to the machines and they're going to, they can, you know, essentially absorb some of what we pass on.

[00:42:53] Right.

[00:42:54] But they don't have that, that higher power connection or that source connection, if you will.

[00:42:58] Right.

[00:42:59] So that's already just a huge limitation, no matter how much you feed them.

[00:43:02] Um, that's just a limitation that in microseconds, we're downloading new, we're downloading new, we're downloading new.

[00:43:09] Right.

[00:43:09] And, um, and then I think, you know, once we start to merge human capabilities with robotics and with machines, that's where I, I call it superhuman.

[00:43:20] And I think it's something that really is going to be possible.

[00:43:22] Um, and that's, I think leaps and bounds more powerful than even, you know, just anything artificial, right.

[00:43:30] Or just purely artificial.

[00:43:32] Yeah.

[00:43:32] I did a lot of work around collective intelligence and collaborative decision-making in my IBM days.

[00:43:40] And this was a little bit before even IBM Watson and the, you know, predictive AI and, you know, the sort of AI that was at the end of an analytics, you know, trajectory, as opposed to an automation.

[00:43:52] And I still contend combining human intelligence, whether that's individual, you know, intuition and creativity plus AI or it's collective intelligence plus AI.

[00:44:07] AI has a, has a role to play, but we can't lose our minds and we can't lose our critical thinking when it comes to, you know, the output of AI as you and I have both been critical of, but where does it fill the gap?

[00:44:23] If it's going to sit in on a meeting, what role is it playing, right?

[00:44:28] Is it playing someone who's, you know, missing from the meeting?

[00:44:31] Is it playing the role of the end user of whatever this, you know, maybe product team is, is concerned about?

[00:44:38] I mean, you've got to use it in, in the right way.

[00:44:42] And I think some of this ties to the transformation that is about to happen if it hasn't started already at a lot of organizations, right?

[00:44:51] If you're going to get mass adoption, then people need to be literate about what a AI can do.

[00:45:01] How to use it responsibly and ethically and fairly.

[00:45:04] And you've got to think about the skills that you gain in terms of, you know, prompting it and, you know, eliciting appropriate responses and just knowing how to get the right answers by asking the right questions, essentially.

[00:45:21] And you've got to have the right, you know, mindset about it because just like anything, we saw this with the early days of chatbots, right?

[00:45:27] They didn't know anything.

[00:45:29] You fed them a bunch of information and it was very, you know, structured and rigid and rules-based and there wasn't much to it.

[00:45:36] And so if you tried to deploy that in your HR service center or customer service center or whatever, you probably got a lot of pushback because it didn't answer 98% of the questions that people had.

[00:45:47] So I just think we need to be really deliberate and careful, but also start now because this is not a transformation going back to, you know, the multi-year, you know, projects.

[00:46:00] This is one of those things that's going to take a long time, no matter what tools you're using, what LLMs you're using, what maybe you're building your own small language model and doing other types of experimentation.

[00:46:12] But this is why I encourage everyone to just get started because there's a lot to unpack and understand and it's moving, things are moving quickly.

[00:46:21] Right.

[00:46:22] And so I liken it to textbook learning versus practical on-the-job intelligence, right?

[00:46:28] Like, we all know, like, we were, we came out of college with a certain amount of knowledge and, of course, you learn that from, you know, that theoretical training, right?

[00:46:38] And then now with, you know, platforms and systems like ours and others that are getting more of that practical intelligence, that's more that advanced arena where you're now getting, okay, now this is not just a, you know, like an intern level or junior level higher, right?

[00:46:53] This is now getting into those mid-senior levels, but it comes with experience.

[00:46:58] For sure.

[00:46:59] For sure.

[00:47:00] So I know we kind of covered a lot of this already, but just thinking about this concept that I call AIQ, you know, what advice would you have for our listeners just in terms of what to look out for and, you know, where to focus?

[00:47:44] Right.

[00:47:45] Whether you're on tech or whether you're doing it off tech, do it.

[00:47:49] Collaborate.

[00:47:49] Don't think that you're just, you know, tricking your workforce by, you know, usurping their knowledge.

[00:47:55] You're really leaving, as I always say, the most intelligent people in the arena off the table when you do that.

[00:48:02] And I just think the more that we collaborate and we work together and, you know, we decide how to do this ethically together.

[00:48:09] I think having those conversations is important.

[00:48:38] And, you know, not just because you want to get left behind, but just because we have sustainability issues.

[00:48:43] You know, we really have mental health issues and the, you know, it's all too much for the current workforce and the current construct.

[00:48:51] So don't wait for things to break, you know, get ahead of it, get involved and see down the line, fix them now.

[00:48:57] Excellent.

[00:48:59] Excellent.

[00:49:00] Well, Elise, this has been great.

[00:49:01] Enjoyed talking to you.

[00:49:02] This is always a very informative conversation and greatly appreciate your perspective.

[00:49:09] So thank you for spending some time with me.

[00:49:11] Thank you, Bob, for everything and your perspective and for having me as well.

[00:49:15] Absolutely.

[00:49:15] See you soon.

[00:49:16] All right.

[00:49:17] Thank you again.

[00:49:18] Thanks everyone for listening.

[00:49:19] Thank you.

[00:49:20] Bye-bye.

[00:49:20] Bye.