Welcome to SkyNet w/ Malcolm Frank

Skynet jokes aside — AI’s here, and it’s not just rewriting code, it’s rewriting work itself.

Joel and Chad sit down with Malcolm Frank, former Cognizant Digital President and current CEO of Talent Genius, to unpack how AI is shaking up business, recruiting, and the very definition of “human talent.”

From CEOs “POC-ing themselves to death,” to Accenture’s secret weapon, to why blue-collar workers might actually win this AI war — Malcolm dishes insight, sarcasm, and a little philosophy.

What happens when recruiters train their AI replacements? Why most companies are jamming in AI instead of re-engineering work itself AND what it means to be “agent powered” in the new talent economy

Buckle up it’s HR’s most dangerous conversation about the future of humans, machines, and everything in between.

PODCAST TRANDCRIPTION

Joel Cheesman (00:28.568)

It's the podcast your mother warned you about. What's up everybody. It is the Chad and cheese podcast. I'm your cohost Joel Cheeseman joined as always. Chad. So washes writing shotgun as we welcome Malcolm Frank to the show. He's former president of cognizant digital. He's an author, a thought leader and current CEO of talent genius Malcolm. Welcome to HR's most dangerous podcast.

Chad (00:50.286)

sexy.

Malcolm Frank (00:54.254)

Thank you, I've hidden the children and I'm thrilled to be here.

Joel Cheesman (00:58.732)

Good to have you, good to have you. So what did we miss in the bio that we should know about you?

Malcolm Frank (01:03.594)

not much, other than I think we all share Ohio roots. grew up in the Cleveland area, but, have been in, technology and technology services for far too long, but, that's, that's what I'm all about.

Chad (01:20.068)

Good to be a Buckeyes fan, my friend. It is good to be a Buckeyes fan.

Malcolm Frank (01:24.343)

yeah, at least...

Joel Cheesman (01:24.396)

Now, did you speak at Davos? Okay, so is this rock bottom for your career now that you, no? Okay. They don't invite me. I put in for it every year.

Malcolm Frank (01:27.437)

Yes.

Chad (01:28.628)

Malcolm Frank (01:31.614)

no, no, it's, it's, you, you have not spent time at Davos. So no, this is, this, this is, well, I know this is, this is a true joy relative to that. So.

Chad (01:35.684)

No, we have not. Thanks for rubbing that in Malcolm. Thanks for rubbing that in.

Joel Cheesman (01:45.854)

I think they gave me a bad address or something. I don't know. I don't know what's going on.

Chad (01:48.548)

It's not Davos, Iowa, jeez-men. No, it's not that one.

Joel Cheesman (01:54.008)

Davos with an I. Davos.

Chad (01:59.36)

Malcolm, right out of the gate. Let's just dig back into your, you've got some sexy titles out there, man. I mean, Cognizant, not a small company, right? Yeah. Advisor, I mean, but let's go back to Cognizant and we're going to be talking about Skynet today, AI, all that other fun stuff. Back in the Cognizant days, very focused on consulting, technology. When did those three letters really start popping up?

Joel Cheesman (02:08.554)

Advisor, board member.

Chad (02:28.404)

in conversation and when did you think it was real as opposed to just total bullshit?

Malcolm Frank (02:34.062)

Yeah, well, real versus BS was obviously when chat hit the market, you know, just about three years ago, but we've seen this coming for a long time. It's been, you know, a slow, slow, all of a sudden phenomenon with AI. And back at Cognizant, it was a wonderful experience. You know, it's when I got involved with the firm and then joined, we were at 10,000 employees and grew it to north of 300,000 and a Fortune 500 company.

Chad (02:40.653)

Mm. Yeah.

Joel Cheesman (02:40.877)

Mm-hmm.

Chad (02:49.431)

Mm-hmm.

Malcolm Frank (03:03.454)

And what was exciting about not just the growth, was fabulous. At one year, we were hiring 20 people an hour for the full year. That was the rate at which we were going. So it was tremendous demand, but it was also a wonderful position for me personally, because when you're in a consulting firm like that, we had as clients, the majority of the top.

Banks around the world, money center banks, majority of healthcare platforms in the US, the largest retailers, largest airlines. And so you start to see the patterns across all of these businesses and how they're getting transformed with technology. about a decade plus ago, we created the Center for the Future of Work that we thought technology is now transforming work at its fundamental level. And so

What skills do people need? What does HR need to look for? What are the workflows? And then how do companies really get outperformance with new technologies? So we were on the scent of this for a long time. A couple of colleagues and I wrote this book, What to Do When Machines Do Everything, which was a great title, but we were early because it was five years ahead of, exactly, exactly. we saw, it's.

Chad (04:08.461)

Mm-hmm.

Joel Cheesman (04:13.943)

2017, 2017, right? Yeah. Where do you keep the crystal ball, Malcolm? Where do you keep the crystal ball? And what does 2030 look like?

Chad (04:14.135)

Yeah. Yeah.

Malcolm Frank (04:22.878)

It's not a crystal ball. just what your parents told you. You're born with two ears in one mouth and use them in that ratio. when you pay attention, you start to see the patterns that are pretty clear. so it's finally come to the fore. And I think, you know, in the next five, 10 years, we're going to see radical transformation of just industries, how companies are structured and what individuals personally need to do. So it's going to be wild times.

Chad (04:51.725)

So here's the thing, and we just saw this MIT survey that came out that pretty much said that CEOs aren't getting the ROI and what it feels like. And when you dig into the survey itself, it seems like CEOs are trying to literally force AI, which literally is creating layers instead of shortcuts. And it sounds like they're literally just fucking everything up as opposed to.

having the people that actually are in those different departments go through process methodologies, what the current process methodologies are, and then the tasks that could be taken. doesn't seem like, and correct me if I'm wrong, it doesn't seem like we're going into this very thoughtfully, right? It's just like jam it in there and we'll make it work, because it's AI. And so some of the reports are...

AI is a bust. It's not working. CEOs really want to do it, but it's not working. What are your thoughts behind that?

Malcolm Frank (05:52.046)

Yeah, well, let's say the old expression, you first we define our structures and then they define us. um, but that is what most fortune 500 companies are today. And so people get caught in these workflows, the business structure, and then something like AI comes along, which, uh, they don't employ first principles thinking. So if you look at all of these failures, every company has been POC to death. Um, you get, I, you know, I sit on several boards and we.

Chad (05:56.676)

Yeah, I like that. Write that down.

Joel Cheesman (05:58.002)

that's good.

Chad (06:11.895)

Mm-hmm.

Malcolm Frank (06:21.675)

sit there and ask, just talk to me like I'm 12. What metrics that matter have changed as a result of AI initiatives? Are we driving more revenue growth, more gross margin expansion? Have our products been transformed? What about EBITDA? Are we finding efficiency in our different functions? And right now the answer to all of those is pretty much no. And that's universal. And it's because, Chad, just to your point,

folks are layering a new technology onto traditional structures and they're just hoping that good shit's gonna happen and it's not. And also if you look at the executive team, the executive team is not structured for this. And so pick on HR. That's, know, HR is all about talent management and humans and managing the people supply chain. So for the promotion cycles.

Joel Cheesman (07:05.741)

Mm-hmm.

Chad (07:08.525)

Mm-hmm.

head count.

Malcolm Frank (07:13.101)

And then you got the CIO who's responsible for technology, but they often turn into the SAP guy or the email gal. But just to pick on those two, when it comes to AI, it has to be the fusion of those because with agents, when you look at work and how work needs to be delivered, it's going to be delivered both through agents as well as humans in combination. But when one group understands the technology, the other understands the work, they can't come together.

in thinking that first principles thinking that if AI existed and we started this process, we never, never, never would have defined it the way it currently is. It would be structured very differently.

Joel Cheesman (07:55.192)

So Malcolm, when we see, you know, Klarna, Duolingo, very publicly say, we don't need people, the CEO saying I'll be an AI, you know, before too long, and then start backtracking on that saying like, well, maybe not, maybe we need some people. even saw Elon lay off everybody and then like beg people to come back and kind of develop, over at X. Is that kind of what you're talking about? businesses, businesses have thought.

Chad (08:18.307)

And the US government, by the way.

Joel Cheesman (08:23.498)

we can do it all in AI. wait a minute. We can't let's bring some people back. So your reality is people are going to come back. It's not like AI didn't work, but it's got to work now with a more human touch. Is that what I'm hearing? Okay.

Malcolm Frank (08:35.425)

Yes. Yes, correct. Correct. And it's, know, how do you build the processes that are based on that? But then how do you amplify the workers and how do you bring people in with the right skillset that matches the skillset and capability set of AI? right now that's all a mess. And another reason that these are all failing, 20 years ago, 25 years ago, we had the business process re-engineering.

Joel Cheesman (08:52.546)

Mm-hmm.

Malcolm Frank (09:01.975)

phenomenon. So this was Michael Hammer and don't automate, obliterate, all that stuff. And most of those failed as well. And the reason, and it's fascinating in hindsight, was that management teams would give those initiatives to folks on their teams and then they would scurry off. And at some point late at night over pizza, the teammates would all look at each other and go, we're, we're re-engineering ourselves out of a job. And then the wall of passive aggressiveness started to take over and

you're starting to see that with a lot of these AI initiatives as well.

Joel Cheesman (09:36.248)

And we're seeing that I think in recruiting as well. I think there's a lot of fear, a lot of uncertainty, doubt. Talk to me about the current state of recruiting, the future of recruiting. assume agents are a major part of that. We're not going to get rid of all of our recruiters, but I want to hear from you what that looks like.

Malcolm Frank (09:53.794)

Yeah, it's a I'm very optimistic about AI with recruiting, but it will be completely transformed. So recruiters will always be around because at the end of the day to switch jobs, switch careers, it's very emotional. And how do you carry somebody through that process? A bot's never going to do that. However, we're seeing through the whole cycle to start with sourcing. We have our own platform that does this where you can cut about four weeks off just the sourcing alone. So instead of having

teams doing the death march through LinkedIn and looking for people that fit, you can find them instantly. We go through seven and a half million profiles in tech and we're able to see exactly what are you looking for? What are the skill sets? And we're able to match those folks and then grade them. And so on the sourcing side, that frees up a lot of cycles for a recruiter. So that's number one.

Number two, we're able then to match all of the agents in the market. So to say, well, if I were to consider what role would AI play in this job, you can pull in the agents as well. And then that creates a different list of humans. That's, if the agents are gonna be doing this much of the work, then what is the profile that I need with other people? So it's not just though the skills piece of it. The second, which is fascinating is, what's the old adage? You hire for skills, but you fire for personality. That somebody's just a bad cultural fits.

Chad (10:56.099)

Mm-hmm.

Joel Cheesman (11:17.368)

Mm-hmm.

Chad (11:17.603)

Mm-hmm.

Malcolm Frank (11:17.677)

You know, the team doesn't like them so forth and so on. AI is also extraordinarily good at determining cultural fit. And whether you're an advocate of Myers-Briggs or Hogan or disc or any of these, particularly for senior people, the more you blab on, on platforms, the more you've written or have you spoken on YouTube, you just put that into an AI and the AI will then really quickly determine.

Hey, what that person's personality profile is and are they going to then fit with this team? you can also remove a lot of the risk out of that cultural fit by understanding the career trajectory somebody has had, what is their velocity and specifically where have they worked? And I lived in New York for a long time and it was well known back in the day that GE and IBM remember when they were both great companies, but,

Joel Cheesman (11:49.09)

Mm-hmm.

Chad (12:11.297)

Yes.

Malcolm Frank (12:12.662)

They were headquartered not that far apart from one other, maybe 10 or 15 miles. And, it was very well understood that you could not get an executive out of GE who would be successful at IBM or vice versa. They just had different managements, philosophies, cultures, systems. And so that happens all the time with recruiting and AI can mitigate that dramatically.

Joel Cheesman (12:15.608)

Hmm.

Malcolm Frank (12:37.27)

where once you understand what your company is all about or the division that you're hiring somebody into and what role you can say, hey, what are the fishing ponds where somebody is gonna be really successful to bring them over? Because consciously or unconsciously, they've grown up in a similar system, have a similar cultural norm, and they're gonna work in this group.

Chad (12:57.859)

So, kind of feels like on the hiring and development side of the house that here in the US over the past 40 years, we've just gotten it wrong. We, for a great example, you just brought up IBM. IBM fired thousands of people and now they're hiring back thousands of people because they have quote unquote different roles, right? Those individuals obviously were already culture fits. And if we would have focused

on employee developments, then there's the prospect of not having to go through that onerous and expensive process of firing and hiring. So when are we going to get to the point when we are actually investing back into our employees as opposed to just throwing them away like, you know, recyclables, throwing them in the bin and looking for somebody else to actually take their position? Because this has changed. I remember

Joel Cheesman (13:54.296)

Like my Johnny Manziel jersey, right in the trash. Johnny Manziel jersey.

Chad (13:59.828)

But I mean, when we were going through high school, we literally had, you know, there were vocational programs that were embedded in the schools and in the community programs where the companies work directly with academia per se, right? That's just not happening anymore. So what's it going to take?

Malcolm Frank (14:19.244)

Boy, that's a super rich question. There's so many aspects of it. So let me try to pick on a few. The first is the economic incentive that for most companies, it's cheaper and far more efficient to do the IBM thing, to let certain people go and hire others off the street than it is to go through the process of training those folks up. So it's just better, faster, cheaper. And that's a reality that we all have to deal with. And that's been compounded post-COVID with virtual work.

Chad (14:36.129)

Mm.

Malcolm Frank (14:48.944)

you remember back in the day, if you change jobs, it was a big deal because you had to move from Columbus with your family and moved to Pittsburgh and selling the house, taking the kids out of school, so forth and so on. That was a big, big ordeal and you had to be right. today, what do you do? You leave employee a on a Friday and on Monday, you know, you have a different laptop and you got zoom going and boom, you know, it's, it's, so there's no life friction with that change of employers. So.

Supply and demand, that's something that's really happening. That efficiency runs counter to what you're describing. Second, if you look at HR, most HR has lost its muscle. It's, there's been, I've seen this a lot with HR, with finance, with IT, that in the last 20 years, they've been hollowed out. It's just this every year in budget cycles, hey, give me 5 % more, give me 5 % more. And at some point, you know, you really get down to the bone. So,

Chad (15:30.071)

Mm-hmm.

Malcolm Frank (15:47.435)

The Crotonville model doesn't exist at most organizations, but let me pick on a company that's done it really, really well. And that's a firm that I competed against forever, which is Accenture. And you look in IT services, most companies are a one trick pony, meaning that we have these big technology cycles and a hot vendor will nail client server, but then they won't be able to transition to internet. And then that firm, the internet firms won't be able to transition to cloud.

and the big question now is who's going to transition to the AI model. But the point is Accenture has been able to navigate through all of those and specifically because they do what you describe. But here's the thing. It's well known. If you work inside Accenture, sometimes it can be difficult because you're trucking along and you develop a certain skillset. And then the HR or your boss shows up and says, thanks, lumpy. That was great for the last four years, but now you've got to transition.

You got to do these new things and we're going to mandate that. And if you don't, you can leave, but we do want to reinvest in you. So they're able to move faster internally than the market does externally, but it's because they're great with strategy. They understand where things are going and then they invest in their people. But I raised that because that case is that that's rare. Most firms do what you're describing.

Chad (17:01.251)

Mm-hmm.

Chad (17:14.785)

Malcolm, how did you know Joel's code name? Code name, Mompe.

Joel Cheesman (17:15.084)

No one's named Lumpy anymore.

Malcolm Frank (17:19.478)

Hahaha!

Joel Cheesman (17:19.852)

Lumpy. That's good. That's good. That's good. So watch. So.

Malcolm Frank (17:22.977)

It's remarkable what you find in AI.

Joel Cheesman (17:25.912)

So, Malcolm, yeah, AI has gotten me pegged. Malcolm, I want to pull on the thread there of recruiting. And by the way, there's a lot of sorcerers that are really happy that they're going to have a job in the future. I assume you don't think that all recruiters will survive this new future. So curious what percentage sort of come out of it? Do new job titles get created? Are we re-skilled? Do they just go become salespeople? Like what?

Chad (17:49.923)

What do they do? Yeah.

Malcolm Frank (17:51.585)

WELLY

Joel Cheesman (17:54.176)

What in terms of the profession do you see shaking out?

Malcolm Frank (17:57.152)

Well, let me start with a general statement that AI, as it sweeps across all professions, is this catalyst. If you're great at what you do, you're going to get become greater. If you stink and mail it in, you're going to get worse. And so it's just creating that dividing line. So those sources and recruiters who are just doing rote things that are pushing paper, they're in trouble because those capabilities.

You know, are going to get continually eaten by AI. It's those that are great is what I was referring to earlier. it's how do you really have that human touch? How do you reach out to the person and say, Hey, I know that you've been doing this for the last seven years, but man, you know, let me talk to you about this team. Let me talk to you about this opportunity. This company is really going places. And I know it's scary right now, but take the leap. Let me, let me, who do you need to talk to? it's.

That is going above and beyond. That's having a very high EQ. So the people that do that well are going to get turbocharged. So it's going to turn into this barbell market. The ones that get left behind, that's a tough, tough question.

Chad (19:14.211)

So the ones that are turbocharged, it almost feels like that they're going to be training the AI. It just seems like a never ending loop, right? So it's like, first, you're going to get rid of the C players. Then the A and B players are going to train the algorithm and then you can get rid of the B players. And then at that point, you get to the point where you can prospectively get rid of the A players. Have a little human touch ever here, ever now and again.

do you think that is, that's pretty much the process or at least the goal for most of these LLMs?

Malcolm Frank (19:50.576)

is it the goal? Yes. and we're going through this Cambrian explosion of agents. And so you get all of these. You know, agent firms that have either gone after vertical or horizontal processes and they're trying to automate as much as they can. But I'm really have mixed, mixed mind on this. It's I remember, remember we all had the Pete or at least those of us of a certain age can remember our first PDA experience. You remember the Palm pilot or the app that.

Chad (20:05.176)

Mm-hmm.

Chad (20:17.283)

Oh yeah, Paul and Pilot, yeah. I had a Sony Clia. I don't remember that one. Yeah, that's off.

Malcolm Frank (20:18.859)

the Apple Newton and you

Whoa, whoa. That's pretty cool. it's, it's, you know, transitioning from Blackberry to Apple was super hard for me. But the point is, is had someone, a little angel come to you and I don't know, 1996, 97 said, let me explain what the iPhone is going to be and what a Mac book is and what zoom is. And when the internet really flourishes, you would pause and go crap.

Chad (20:43.107)

Mm-hmm.

Malcolm Frank (20:52.159)

Those, you know, that four hour work week is going to be marvelous. I mean, what, what am I going to do with the rest of my time? And instead, you know, what are we all doing? You know, we're, here. We are, we don't have any time.

Chad (21:01.121)

Here we are. Returning to the office? Yes, all that stuff.

Joel Cheesman (21:04.002)

Yeah.

Malcolm Frank (21:06.631)

Exactly. I think there is a line of argument where AI is going to eat all of the work, but there's another that we always find new things to do. We always get those new layers of productivity. And so I believe that that's what's going to occur with folks who adapt.

Joel Cheesman (21:23.224)

Yeah. We have a lot of vendors, uh, listen to the show and you're a vendor as well. was at a luncheon recently talking to a recruiter who basically said the tools that they use most are, you know, Microsoft based open AI based Google base. was not a lot of sort of HR tech specific, um, technologies. And you see on a regular basis, you know, uh, open AI releases a chat sort of open source chat bot. And so just curious your thoughts on.

Is the future a mix of big tech and, and, and niche vendors and HR does, is it a one, you one winner, one big loser? I assume you're a fan of the HR tech space because you're CEO of a company, but defend the HR tech against some of the big boys. How are they going to differentiate? How are they going to thrive?

Malcolm Frank (22:11.947)

Well, there's an internal fight going on in large companies, and it's the end user versus procurement. And so what you have is the end user, that HR professional, is saying, I need something that does XYZ. And then procurement says, no, you don't, because we have too many vendors in here. And so we've got to go through vendor consolidation. And what's also happening with AI is that the lawyers show up.

Chad (22:36.237)

Mm-hmm.

Malcolm Frank (22:39.667)

And the lawyers are like, what about hallucinations? What about security? What about this? What about that? And what has occurred is that the market leaders better known as Microsoft and Google and AWS have made that sale with those folks, whereas smaller, more nimble firms just can't. And so we're seeing this incredible bifurcation that in large companies, you are stuck with the usual suspects, but independent recruiters.

HR professionals are leveraging this new tech at an incredible rate. And so it's interesting, you know, it's in other cycles, big companies who move faster with tech, but with AI, it's just the opposite we're seeing because it's so cheap and so powerful and you don't get with the stasi of procurement holding things up. that's, you know, those folks can move a lot faster.

Chad (23:27.576)

Mm-hmm.

Joel Cheesman (23:32.642)

Yeah. So see a lot of the bigger companies in our space, the work days, the SAP's gobbling up a lot of these sort of smaller tech players to, think, take on the Microsoft's and the bigger companies. that your take as well?

Chad (23:32.663)

So it's.

Malcolm Frank (23:39.467)

100%.

Malcolm Frank (23:44.233)

That's correct. And they're also trying to protect their moat. And there's a whole question of what's going to happen with the SaaS business model. So watch the birdie, buy more SaaS, watch the birdie, buy more SaaS. And that's going on in that sector.

Chad (23:55.619)

You

Chad (24:01.315)

I think we've seen acquisitions with Workday. Obviously, they've been gobbling up a bunch of AI players, and then obviously SAP as well with smart recruiters. It seems like because we've seen over the years, we're talking about AI being this, let's say for instance, Microsoft Co-Pilot, the CIO saying, we're using that. I don't care what you say, HR. It's been the same thing with the ATS.

Malcolm Frank (24:24.234)

That's right.

Chad (24:27.095)

The ATS, they were like, no, no, we we've bought a HCM, it's called Workday. And there's a gift with purchase, they call an applicant tracking system. And that's what you're going to use. Yes, it's shit. We totally get it. But it feels like I could be wrong, but it feels like that there's a cycle that's happening. Workday bought success factors jobs to web years ago, that is tech dead is pretty much died. Now you've got paradox coming in there, you got sauna coming in there. It feels like

for work day, as I think you guys were actually alluding to, is like they're really getting it because they understand that to be able to fend off Salesforce and some of these, and ServiceNow and some of these very, very big platforms away from their moat, they really have to get their shit together so that the CIO gets not just some gift with purchase, but they get a really good piece of tech.

it almost feels like we're starting to learn maybe. I don't know. Or maybe it's just a cycle and shit's going to go downhill.

Malcolm Frank (25:26.932)

Yep. No, it's no, no, That's what you're describing is absolutely occurring. So no question about it. And I think that Workday has been very smart about that. But they're taking a page from history. During the cloud movement, we saw the same cycle. It's interesting when you bring up IBM. Had somebody asked 15 years ago, who's this thing cloud is going to be dominant, is going to create trillion dollar vendors, who's going to win? Would it be the bookstore? Would it be the search company?

You know, would it be the Xbox company or would it be the dominance, you know, enterprise technology firm is, but the same thing occurred where big blue tried to create those blockers. And what happened is there was renegade it. And so you had the person in the Tacoma office just said, you know what? I need this compute. I'm just good. I can't wait. I'm just going to slap down my Amex card and get it instantly through AWS. And the rest was history.

Chad (26:01.965)

Yeah, big blue, yeah.

Malcolm Frank (26:25.866)

I bring that up because the same thing's starting to occur again. And let me give a cognizant example that we had centralized HR. in my group, there were years where we would have to hire about 42,000 people a year, both with our growth and with our turnover. And it would make your hair hurt. But in order to do that, I'm sorry. I'm sorry.

Joel Cheesman (26:47.276)

That was a free chat, by the way.

Chad (26:48.483)

Thank you. Thanks, Lumpy.

Joel Cheesman (26:52.866)

Malcolm is an equal opportunity offender. That's nice. Lumpy and curly over here.

Chad (26:54.634)

Malcolm Frank (26:57.354)

Well, it's a, I'll give you a decide. was, I was trying to find, this is total non sequitur, now that you brought that up, but prepping for the show, I found the limitations of AI. So for those of us that are worried about Skynet and the rest, I just asked Grok and Deep Research, how many times has Chad dropped an F-bomb on this podcast? And neither could answer the question.

Joel Cheesman (27:00.043)

You

Malcolm Frank (27:27.304)

But Grok was pretty good. Deep research just said, I don't have the transcripts, don't know. Grok said, well, they've done 1,300 hours, and he does this many per episode. And he does use that word, and therefore, this is a guess. But anyhow, so I found the limitations of AI.

Joel Cheesman (27:41.474)

Our best guests.

Joel Cheesman (27:47.32)

It's good to know that humans have to still listen to the show. If they really want the deep insights, they actually have to listen. They can't just ask Grok what it is.

Chad (27:47.509)

And it's Chad Chad is the limitations

Malcolm Frank (27:54.215)

Exactly. You're the bulwark, but getting back to renegade AI procurement versus centralized, we ran into this problem that our internal recruiting teams, our centralized recruiting teams would try to hire folks. And then we would bring in the business units and say, Hey, I found these great candidates for you. And the business unit would go, you're killing me. These folks, they're all wrong, wrong, wrong, wrong for these reasons. And so they would want to go out and start to do it on their own.

We're starting to see the same thing happen because when you look at these sourcing tools, they're so powerful that those end users are just saying, you know what? I can just spend the 500 bucks. I can spend a thousand bucks, use one of these, source my candidates, and I could actually grade those candidates vis-a-vis what HR is providing and make the best decisions. So Renegade AI spend is something that I think is, it could start to challenge

the workday model the same way that Renegade Cloud Procurement was hitting the IBM model.

Joel Cheesman (29:00.056)

And speaking of renegade spend, biased recruiting seems to have tempered down a little bit, but it's still a thing. Give us your take on, this a net positive? Is it a net positive for diversity, equity and inclusion? Is it a net negative? What do you see politically happening? It feels like we've seen a slowdown in regulations on the local and state level around this. What are your thoughts?

Chad (29:26.701)

Feels like.

Malcolm Frank (29:29.45)

Yeah. I saw two polls that blew my doors the last month. One was asking employees, would you prefer a human manager or an AI manager? And 38 % said I would prefer the AI. And then when you double clicked, they're like, well, why? It was trust. It was, I think it would be objective. It would treat all of us fairly. And they're saying, you know, I see my human manager being full of bias.

Chad (29:45.667)

That's huh.

Malcolm Frank (29:59.178)

pretty capricious, likes people and others, or just as a human being is not consistent, or as a human being is just a suit. They're not that talented. Why should I take their advice? And on the flip side, I saw this morning, this is in the UK, you could Google both of these, a poll, which was the opposite of that, that managers were saying, yeah, I'd rather manage agents than young employees. So it's...

Joel Cheesman (30:24.824)

You

Chad (30:26.145)

Well, I mean...

Malcolm Frank (30:28.677)

It's it's, yeah, it's, you know, we've all been there, at least I've been there, you know, it's a minute of feedback and then 59 minutes of therapy. But it's, it gets Joel to your question that those are people saying, I trust the AI more than I trust the human in that dynamic. So, you know, it gets back to recruiting. Are we worried about bias in AI based sourcing and recruiting? Of course.

Chad (30:35.436)

Mm-hmm.

Malcolm Frank (30:57.427)

but you're presuming that bias never occurred in human-based sourcing or recruiting, and it was rampant, completely rampant. The difference though is that you can manage or mitigate the human-based bias much more easily than the AI-based bias. That's the big, big question. it's, you know, if the AI, I'll give an example, a very early AI implementation, this was with

Chad (31:06.851)

Yeah.

Chad (31:14.812)

yeah.

Malcolm Frank (31:27.465)

two big banks, I won't name who they are, but this is at the dawn of AI, using it to figure out credit worthiness. And they were seeing FICA scores and the rest are a bit misleading and clumsy. And so can we look at individual by individual and understand, are they going to pay back their car loan? And it was based on what their educational background was, what their major was, what classes they took and what sequence, what were their grades when they moved to the big city.

Did they live large, meaning they got an apartment that was 50 % of their salary or did they skimp and, you know, live in a worse neighborhood, but it was 20 % so forth and so on. They took in all of those variables. And what happened was the systems became predatory lenders within 24 hours. In fact, one of the clients, his, the customer, he said, pull that thing out of the wall, just like shut it off. Um, and so.

Joel Cheesman (32:04.312)

Mm-hmm.

Malcolm Frank (32:24.935)

That's where the AI started to work on a different set of ethics, shall we will say, than we have negotiated as an American society. So when that starts to occur within recruiting, and you don't have good governance or legislation against that, you think we have conspiracy theories today, what is it gonna be in three years time when people say, I know why that person didn't get the job?

And it's going to be because some code was auto-generated somewhere in the cloud that powers this AI. It's a big concern.

Joel Cheesman (33:00.012)

Mm-hmm.

Chad (33:04.085)

Yeah, we definitely need guardrails, but the thing is we need to know the definition of what the guardrails are, which means we have to be monitoring constantly, right? And I do disagree to some extent because, yes, there was definitely rampant bias that happened just with humans. Big difference though, it couldn't scale, right? Because humans don't scale well, but you put that into an algorithm, boom, bias explodes, which could be actually a good thing because if you are monitoring,

Malcolm Frank (33:09.257)

That's right.

Chad (33:33.077)

you have the indicators where before it was a very small sample size. Now you've got a huge sample size to work off of and you can start to create guardrails around that if you're managing it, right?

Malcolm Frank (33:42.759)

Yep. If you are, but Chet, you're onto something really important that a lot of these firms that are global companies. So what works in society A is a real violation of something in society B. And so

Chad (33:53.827)

yeah.

yeah, Europe versus the US in many cases. Yeah.

Malcolm Frank (34:00.356)

Exactly. So let's just say the company's headquartered in, let's say, San Francisco. And it's got operations, I won't name places, but let's just say very conservative places around the world. that's going to, those policies and those rulemaking frameworks are going to just run into the gears of that local society and be very counterproductive. And I'll just give a simple anecdote. We created a social platform internally once.

Chad (34:05.442)

Mm-hmm.

Chad (34:17.027)

Mm-hmm.

Malcolm Frank (34:28.883)

just thought, let's do Facebook internally, same capabilities, and it'll create community and real bonding of employee experience. And so we had some Americans putting up photos of gay marriages. And as an American, you're like, wow, that's awesome. What a beautiful ceremony. It's good for them. And we had employees elsewhere around the globe that were very offended by this. And it blew our doors as American managers.

Joel Cheesman (34:53.356)

Yeah.

Malcolm Frank (34:58.729)

you know, those types of sensitivities where you just think in your mind, like, this is just like a law of thermodynamics. It's like, you know, can't be argued. You're like, crap, we really stepped in it. And so trying to centralize those policies through AI and the phoom, throwing them across a global platform is pretty dangerous. Whereas it's been hundreds and hundreds of micro decisions

human to human to manage those on a global platform.

Chad (35:30.209)

Yeah, so you're gonna have to silo that.

Joel Cheesman (35:31.564)

Are you keeping on the Mobley versus Workday court case? Any predictions or thoughts if it goes one way how it will impact our space? No.

Malcolm Frank (35:37.758)

Yes.

Malcolm Frank (35:42.983)

No, it's, I've learned a long time ago, don't predict politics, don't predict court cases. So I really don't know.

Joel Cheesman (35:51.714)

Fair enough. I'll let you out on this. We've talked a lot about white collar, knowledge-based jobs. Just what's your take on AI's impact on blue collar folks?

Malcolm Frank (35:59.913)

Um, look, it's blue collar folks. That was the transition a hundred years ago and we should really pay attention to it. So I think from a blue collar perspective, if you're an HVAC, if you're, you know, I can go through the whole list. They are not, they're going to be amplified, but not automated. So that's a great, great place to be. But you look a hundred years ago, I actually go 125 in 1900, the story of the ice man versus the farmer versus, um,

versus the Teamster.

Joel Cheesman (36:29.944)

versus Maverick and Goose. different.

Chad (36:32.488)

Yeah

Malcolm Frank (36:32.529)

Yeah, exactly. No, is. You're like, see, but that's exactly it. No, Joel, you're see, but it's your quip is exactly the point that in the year this blows people's minds, at least blue mind. It's it's in nineteen hundred that there were over one hundred thousand icemen in the United States. These were people who would harvest ice in New England and in upstate New York, stick them on boats and then they would float them down so people could keep their food.

Chad (36:37.773)

saying volleyball, yeah, beach volleyball.

Malcolm Frank (37:01.129)

You know, in major cities up and down the East coast. And then there was industrial automation and that job went to zero because there was this box that you plugged in the wall and that job went away. Farmers were, it took 40 % of the U S workforce to feed ourselves in 1900. And today now that's 1%. So that job just, but then you look at Teamsters, there were, I don't know, like 3000 Teamsters and now there's 1.4 million. So.

It's that's what's going to happen with jobs is that some are going to get automated away. You know, some will be a fraction of what they were previously, but then others are going to boom. and so to think that's not going to happen again, just shows a really limited imagination. But if those that are safe to answer your question briefly, you go through the trades and it's, I, it's going to be a very good place to be for the next 20 years.

Chad (37:56.708)

So Malcolm, last one for me, my friend. You're a really smart dude. What the hell are you doing in the talent acquisition, the talent segment for God's sake? mean, what the hell? And tell us a little bit about Talent Genius because you've got a reason for it, right? You've thought this through. So tell us a little bit about this.

Malcolm Frank (38:16.848)

Yeah. You know, I always wanted a job I could never explain to my mother, I guess. But I have a real passion for this because I think that if you look at the history of good societies, now it depends on how you define those, but it's where there's economic prosperity, it's the societies that have gotten this right, that technology is going to do what technology is going to do. But how do you transform and get the models right?

against that. And so I get bored with all the stages of economic history where that's happened. But right now, what we are going through for the next 10 years is going to be the most violent shift that we have ever experienced. when I was talking about like farm to factory, society, took a good two generations to manage that. We're going to have to manage this one in a very abbreviated window of time. So

Chad (38:47.457)

Mm-hmm.

Chad (39:08.611)

Mm-hmm.

Malcolm Frank (39:13.636)

That's the passion. And I couldn't think of anything more important to do, at least personally. And that's why we created Talent Genius. We are trying to put AI on the side of the people. And so to help them understand what are my skills, what are the agents that are coming after me, what are the agents that I could partner with, and then how can I move forward to really prosper. And we've created a platform within that called Agent Powered that every job...

is anybody who's going to be successful white collar moving forward is going to be agent powered. You're going to figure out what are the agents that I work with where I can become 5x, 10x what I was previously. People who do that are going to do really, really well. And we came up in the industrial era with this notion of horsepower. How do you explain the power of a machine? So we still use it. Today, if you drive a big pickup truck like a Ram 1500 with a Hemi,

Chad (39:43.811)

Mm.

Malcolm Frank (40:07.9)

that has whatever it is, 395 horsepower. But we're now seeing that if you're a designer, a developer, a marketer, a sourcer, that if you're using agents, you now have the full-time equivalent power of three, four, five. And so we're trying to help people become agent powered where they can turbocharge their capabilities. And instead of worrying about AI, get really enthused about the new doors that it opens for them.

Joel Cheesman (40:35.158)

It's not about the nookie. He's doing it all for the people, everybody. That's Malcolm Frank. He's CEO at Talent Genius. Malcolm, for our listeners and viewers who want to learn more, where would you send them?

Chad (40:38.691)

Hahaha

Malcolm Frank (40:39.848)

you

Malcolm Frank (40:47.474)

just go talentgenius.io.

Chad (40:50.785)

easy.

Joel Cheesman (40:51.928)

That's another one in the can. Go Bucks. We out.

Chad (40:54.21)

We out.