WorkWhile COO Simon Khalaf says the company’s AI-driven labor OS is reshaping the workforce — matching workers to jobs with precision.
Transcript
This is Monday Conversation, a PYMNTS podcast. Karen Webster sits down with the visionaries behind the trends for the stories shaping what's next in payments and commerce. In this episode, WorkWhile's COO, Simon Halaf, explains how the company's AI-driven labor OS is reshaping the U.S. workforce, matching workers to jobs with precision, delivering instant pay, and turning labor into a financial asset.
Karen Webster:Hey Simon, great to see you. Looking forward to getting all the scoop on your new gig as the Chief Operating Officer at WorkWhile. So thanks so much for taking the time.
Simon Khalaf:Karen, thank you so much for having me. Really appreciate it.
Karen Webster:It's an exciting new endeavor, but I want to start with my observation of WorkWhile. Tell me if I'm right or wrong. So the website says it's a labor marketplace matching hourly workers with capacity with companies in certain industries that need work. So it's a marketplace. I, however, see it as a platform that can really become infrastructure for thinking about how companies hire, staff, pay, and scale their workforce. Am I wrong?
Simon Khalaf:You're absolutely right. You're hired. What you just laid out is actually the two to three year, I'd say, vision and plan. But what we're talking about on our website is what we do today. But you're absolutely right. I mean, I'll start from the big picture, which is exactly what you laid out. Our GDP is 70% labor. 70%. And the hourly, we're starting with hourly, which is roughly a $5 trillion GDP in the United States, which if they were a country, their GDP would be larger than Germany. So it's a massive market that no one has really invested in. So you're absolutely right. The word platform is significantly better than the marketplace. And not only that, it is we want not just like I always think, which is the vision for FinTech is is to take the underbanked and bank them. We're taking it a step further. We're gonna give them the job, we're gonna give them the financial wellness, and some form of health wellness where governments have failed. That's kind of like the big picture. And we've got the economics to do it. And I'm happy to share.
Karen Webster:Yeah. So I'm excited to get to the ecosystem part because the platform implies, you know, you've got the worker, you've got the workforce, and you've got the businesses. And now you can create this ecosystem, which is very exciting. But I want to park that for a second. I want to get to the fact that you are able to underwrite labor, in my opinion, in many ways, the same way that FinTechs are underwriting sort of the underserved consumer to give them access to credit. Because you're able to advocate for a worker and match them better than a typical staffing agency would be able to do. A name on a list, I've got time, you need a body, let me match it up. You're doing something different using AI. Can you explain how you do what you do?
Simon Khalaf:Yeah, absolutely. I love the word underwriting because it's exactly what we're doing. So at the core of WorkWhile' s a massive AI engine that has been labeled AI way before AI was cool. I've been on the board of WorkWhile and I was behind the founding team in 2019. And when we went out with the vision, what AI can do, and do, people thought we were crazy. Seriously, they said, you are crazy. That will never happen, especially in a highly regulated market. So let me give you some stats. And I'm back from where we are to why, which is AI. So today, WorkWhile h as become the 26th largest employer in the United States.
Karen Webster:Wow. That's amazing.
Simon Khalaf:And I'll give you an easy number to remember. Okay. How many people do we have in talent management and acquisition?
Karen Webster:I don't know, zero, one.
Simon Khalaf:Yes. Zero. You're brilliant. Zero. Wow. Talk about efficiency. How many people do we have screening candidates? Zero. You bet. Zero.
Karen Webster:So you are the Sam Altman
Simon Khalaf:vision. Yes, a flavor, a flavor. A
Karen Webster:flavor of that, yep.
Simon Khalaf:Right. So our product is not a robot nor a software agent. Our product is a human and humans are very hard to predict, very hard to predict, right? I mean, we're made out of bits and numbers and blood circulation and everything. We're very hard to predict, but we've done an amazing job at it. And I'll credit our data science team, which I call them, each one of them is a $10 billion higher. And we hide them, we don't let them talk to anybody. So here's what they've done. They have predicted... the, the show rate to a job. Yeah. Less than 4% error. Wow. Which is an industry that is 40%. So 10 X.
Karen Webster:Well, yeah. I mean, you're right because there's, it's tight churn. It's unreliable.
Simon Khalaf:Yes. Yes. So our churn is an easy number to remember as well. Okay. Zero.
Karen Webster:Wow. A lot
Simon Khalaf:of zeros. A lot of zeros. So there's no churn on our platform because we can, uh, With more than 72 hours, notice our fill rate is close to 100%. And from zero to one hour, zero to one hour, notice our fill rate is over 50%. And I'm not talking gig. I'm not talking gig as in go pick up something. I'm talking you've got a six-hour shift. Oh, shoot, somebody didn't show up. WorkWhile I need your help. 50% of the time in half an hour or less, we have somebody who's trained, knows how to operate a forklift or knows how to mix a drink or knows how to become a barista, right? And we get them trained as they're going to the shift.
Karen Webster:That's amazing. So you must have density in the verticals, in the geographies. And that takes, I mean, that takes time to build.
Simon Khalaf:That takes time to build, yes. So we have achieved density through ramp. So this is a great question. And there's two types of density. One is W2 employees, which is we are the employer of record. And then there's others in which we work with third party contractors. So and what we have done, right, is what I call micro labeling of skill. So I'll give you an example. I consider myself a cook. Actually, I am a cook, a cook, but I cook some So to all staffing engines, you are a cook that worked at a certain company. To us, you're a cook that knows how to cook with lamb, with Mediterranean spices, who has worked under an umbrella with a Viking oven for three hours and working with one or two sous chefs. And the list goes on and on and on.
Karen Webster:Very specific. That's why you get the show upgrades.
Simon Khalaf:You got it. That's why you don't have the show. You got it. You got it. So our team has, if I look at the core engine underneath WorkWhile, the first one is a matching engine. Call it the best dating site, right? Between a job and a human. The second one is a show prediction engine. Would you show up to the date? Right? The third one is a pricing engine, which no one can gain, which is how much should I bonus you in order to take that job, right? Yes. And then I'd say a training algorithm that ingests insane amount of manuals and on the fly create training. And I'll give you examples of that. And last but not least, an AI-enabled, I hate to call it a screener because that's rude to humans, but But think about it as a talent acquisition manager that be able to extract the skills you're good at and your cultural fit with a job.
Karen Webster:And that's how you can do it so quickly because it's all very much real time as the model is working through the filters,
Simon Khalaf:the criteria. And continuous. You're being interviewed nonstop. 24-7-365. Your skills are being updated. We reinforce you. On top of that, we do instant pay at no cost. We give earned wage access, not at 40% APR, at zero. We use our own working capital. We give free telehealth care. And I'm going to give you a stat, which I'm so proud of. It's already on my Twitter feed. We have saved 48.5% of the folks who use our telehealth have avoided the trip to either urgent care or ER.
Karen Webster:Wow.
Simon Khalaf:Saving the government a lot of
Karen Webster:money. For sure, yeah.
Simon Khalaf:And we do free upskilling and training. Why? Because our incentives are aligned. The better our labor is, the more money we make. Exactly. So the reason why we are efficient in training is because we use LLMs to understand the manual. Let's say today, if you want to go work in a warehouse, they'll give you a 200-page manual that tells you, hey, this is how you operate the forklift, including how do you change oil, how do you change the wheel. What are the chances that the forklift is going to need oil change in a two-hour shift? Almost zero. So skip that chapter. So we do just-in-time manual and the machine generates a quiz. And that quiz is progressive. Like if you try to trick it, it will recognize, right? And it says, okay, you're certified. Sorry, not certified. Our own certification, right? But if we send you to an industry certification, it's like on Twitter, you get the check.
Karen Webster:Wow. So Simon, is your business model different because you are providing a skilled worker that is going to show up, that is going to be trained to take care of whatever that job is, and therefore you can command a premium price for that?
Simon Khalaf:We're actually not even asking for a premium price. So we are transparent. So our take rate is anywhere, depending on the state, anywhere between 12% to 20%. So that's our take rate. But we can show you that we save you 35%, more than 35%. So zero percentage We pay for time off. They don't pay for time off. We give our people sick days. We don't charge the company for sick days. We eliminate absenteeism. We eliminate churn. We eliminate the need for working capital because a lot of those folks have to pay every week and they collect net never. And then also we eliminate what I would call training and we eliminate HR overhead. So all of this adds up to about 35% of that industry. So we actually save everyone with the exact same quality, like take to the bank between 15 to 17%.
Karen Webster:Wow. How is this changing how CEOs and those who are making these hiring decisions are thinking about staffing now? Because I would imagine this is provoking conversation throughout these organizations where you've got density and you've got a footprint to kind of rethink how they how they have a workforce inside their business?
Simon Khalaf:That's an absolutely great question, Karen. That's why we're not a $10 billion company yet, because we're asking humans to change behavior. It's very simple. And I share with the team here that in 2001, which is 24 years ago, Every company in tech that wanted to build anything would refuse to host their stuff. They would start buying computers from Dell, going to like an ex-business or one of those hosting companies. They rack servers. They plug them together. And that's six months before they write a single line of code. And you tell them, why don't you use like Digital Frontier? Oh, no, no, no, no. Our technology is our asset. Today, you spin up an instance on Amazon. It took 24 years for engineers, the most sophisticated, like the brilliant, the most brilliant people, the most progressive, to accept that you don't own your hardware. You don't need a hardware, right, in order to build a tech company. Can you imagine going to a CEO and saying you don't need labor? So what do I have, right? I mean, right. However, I can mathematically prove to you that we can beat any organization labor. When you look at the restaurant industry, 130% churn. Why are you recruiting? Our time to fill is in hours. Their time to fill is an average of three weeks. Then
Karen Webster:the turnover
Simon Khalaf:is 90 days. Even in tech, in the most successful company, churn is 15 to 20% annual. Restaurant industry is 130. Retail is somewhere between 80 and 90. Our model works for every industry. However, it's going to take time. So that's why we have focused on retail, warehousing, 3PL, hospitality, events management, and then we will add more industries as we mature as a platform and as we have all the proof points to demonstrate the validity of our system.
Karen Webster:Yeah. Don't you have a lot of interesting data on labor trends and sort of the ebbs and flows of these various verticals? I mean, aren't you predictive in that sense as well?
Simon Khalaf:We are, we are. I mean, I post on Twitter, right? I've made it, I mean, I'm kind of like working as the economist, although my data science team says don't do anything like that. So, but yes, absolutely right, Karen. If you look at it, Our community, the 83 million Americans, they're swimming in debt and they're underemployed. They are underemployed. The Feds is not taking into consideration underemployment, which is the Achilles heels of our economy. So I'm happy to share stats, but it's on my Twitter feed. So we have lost, in terms of GDP production, $600 billion of employment. So people, let me explain what I mean. So the average numbers of hours, worked by an individual American has dropped over half an hour per week. That's equivalent to $600 billion of GDP production. And the participation rate has declined, as in people decided not to work. So when we say unemployment is steady, that's I'm not going to use an expletive. It is actually not relevant.
Karen Webster:It's an inaccurate picture.
Simon Khalaf:It's an inaccurate measure of the wealth of our community, number one. Number two, the debt stack is building up and up and up. We can show you that 16% of every penny generated by 83 million Americans is going to debt service. We're worse than the federal government. Right now, the federal government generates, our GDP is about whatever, 30 trillion. The federal government generates about 8 trillion. They pay $1.2 trillion in debt service. So an average American worker is generating roughly, call it 60K, But unlike the federal government, our workers pay taxes. So the take-home is about $40,000, and they are paying roughly $6,000 to $7,000 in debt service between payday loans, earned wage access, which is the biggest scam in fintech, and credit card fees at 29% APR. So now let's talk about it. If you look at it, I mean, you're aware of our relationship with Marketa. So today I consider WorkWhile the world's first and most successful neocredit union. I don't want to make money from FinTech. I don't care about the basis points. Take it all. I make 1,200%. Why do I need to worry about 96 basis points? This is an investment in our workers. It's my honor to pay people on time. It is my obligation. It's the most important asset I have, right? Imagine on a daily basis, daily basis today, if I log into my portal, I have on every instant where the sun is out, I have 173,000 people working for me. Why would I screw them. I will pay them instantaneously.
Karen Webster:You want to pay them instantly. And your point about the debt service, it does then interfere with their ability to consume products and services in the economy, which is a problem too. And we see that in the numbers. We see them are numbers, your numbers. But talk to me about this ecosystem, because if you're a platform and you have a workforce, and it's a critical mass of people that people would like to be able to not just serve, but find an attractive audience to bring offers to and other related services. Are you thinking in terms of platform and ecosystem built around the workforce?
Simon Khalaf:Yes, yes, absolutely. So we've announced our partnership with Marketa around FinTech and the ability to do instant pay, as you can imagine. So we will be adding a lot more banking services to become a full-fledged banks and launch what I would call the interest-free loan economy. Wow. So yes, so we have the right to play. Right now, 33% of our community banks with Chime or Cash App and the other 67% is distributed among 4,300 banks and credit unions. So we are the entity that redirects the paycheck. So that will all be on the Marketo-powered bank very soon. And the growth is over 100% year over year in terms of labor participation. Excellent. So then we have a relationship with Curai Health to offer free telehealth. So we're paying Curai out of our own pocket to do health stuff. imagine that we will be introducing everything an employer offers today through what I call the law of scale. Like if you go and buy life insurance as an individual today, let's say it's $59 for 150 grand. If you go buy it as a group, it is 39. So I will make only $2 and sell it at 41. And Everybody wins.
Karen Webster:Well, what's interesting is that you're making all this very portable. It doesn't matter what company you work at today, tomorrow. It could all be very different. But the benefits are consistent. The pay is consistent. And I think it really is reimagining the employer-employee relationship at scale in real time.
Simon Khalaf:Darren, you use terms that fascinate me. If you look at the first slide of WorkWhile, it is called, your phone number is portable. Why aren't your benefits? benefits. I mean, this is exactly what it is. It's a portable benefit stack that like, okay, let's be honest. In the United States, you don't have a job. You don't exist. You cannot get a loan. You cannot get financing. You can barely get a phone plan other than prepaid, right? Let's go then on and on, right? Which honestly, our government actually, I mean, even social security is bankrupt. I mean, let's just call it what it is. I mean, because we keep printing money in order to show up. So if you don't have the money, we print it. Which means the US dollar has lost 9% of its value since February 26th. I've got the numbers. 9% of its value pegged against euro or commodities. 9%. No one talks about it. If somebody walks into your house and takes 9% of your jewelry, what would you do? You would scream.
Karen Webster:Yeah, I would scream. I would not
Simon Khalaf:be happy. That's correct. We lost 9% of our savings today, but no one actually is unlike the stock market, no one is looking at the day-to-day FX. Excellent. So the point that I'm making is it's a good thing that the private market like us can offer these services to the workers at scale. Because, I mean, I hate to compare ourselves to governments, but I think we're doing a better job by creating a highly, highly efficient marketplace, although it's a platform. Kind of like how Adam Smith has envisioned it. And I'm gonna use his term. It is the labor. The invisible hand. The invisible hand, right? I mean- I mean, exactly. I mean, if you look at it, I don't believe JP Morgan or Morgan Stanley. Look, they're great companies, but they have a product for the 1%. They don't have a product for the 99%. It's not that they are bad people. They decided to go after this market, but there's a vacuum for the other 99%. No problem. I'll fill it, right? And I go back to Adam Smith. It's through labor and not gold and silver that all the wealth was purchased. Labor is the most important commodity that humanity has ever built. It's not stocks. It's not crypto. It's not anything. It is not even gold and silver. It's labor because labor can generate wealth.
Karen Webster:For sure. Absolutely. Well, yes. And I think we agree on that. But I was going to ask you who you've disrupted, but there's lots of roadkill. I mean,
Simon Khalaf:it's a great question. It is a great question. So parts of it I'd say it is internal HR, as in folks that have built teams in order to expand labor. That's, I'd say, the number one entity we have disrupted. The second one is the incumbents, which is the likes of Ronstadt or ADECO or what have you. Manpower, yeah. Right, manpower, right, exactly. That's the second category of disruption. And then you have what I call the sum tech enabled companies such as InstaWork and 1.0, but that's a very small percentage, right? And that's pretty much it. But I'd say the vast majority of who we're disrupting is internal teams.
Karen Webster:But you're also, because you've got this critical mass of workers that are incented to remain a part of your platform and will continue to grow you're also disrupting the FinTech financial services ecosystem because you're providing a product that is aligned with their ability to generate income for their families and their family.
Simon Khalaf:That is correct. So, I mean, if I look at FinTech, I mean, at the end of the day, FinTech has built three very successful products. The first one I'd say is by and I'll pay later, which is technically a marketplace without the invisible hand. So it is effectively... the retailer is paying for the interest on behalf of the consumer instead of a discount using an underwriting algorithm by Max Lefkin or sorry, by Affirm, by Afterpay or Aquano. Okay, so that's one very successful product disrupting the credit card industry. The second one is earned wage access, right? Which is honestly, I mean, that's what I call cash app. and shine. The only value proposition they have is you got your paycheck a couple of days early and also I'm going to extend to you a short-term loan at some prohibitive APR and by bypassing the APR. Very successful products. People love them. Same thing with Revolut, by the way. Now, the third successful product is using tech to improve the life of the CFO through taking expense management and AP and making it seamless, which is the likes of Fran and also taking AP and optimizing the loans against receivables. Those are the three products that all of us in FinTech, I'm putting crypto on the side because crypto is still hype, right? Those are the three core great products. And underneath them, you have Stripe on the acquiring side, right? And Agile, and then you've got the likes of Marketa on the issuing side. That's And then you have Visa and MasterCard who build the rails. I mean, it is, I'd say, the benign tax of the ecosystem, but it works. Excellent. So that's FinTech. I mean, really, if you sum it all up, that's what FinTech is all about, right? So we are not getting into the expense management side and whatever. However, with partnerships, we will offer the free EWA and we will offer the buy now, pay later. Honestly, I mean, paying for is interesting, but it's the gimmicky, regulated, you can pay with your credit card, that kind of thing. Honestly, we don't need it. I mean, we are going to give you money, and you can pay later. You can do whatever you want with it. It doesn't have to be. Now the question is, will we be able to create the full service, what I call co-op? The credit union is within our reach because, Well, the loan will be collateralized against future labor. So it's either earned labor, which is easy to collateralize, right? The second one is the self-assignment of future wages, which is not through a court order, through a self-assignment, right? That's the collateral on the loan. So once we're done with this, that's where we'll use a GenTech to build what I call an exclusive wealth, and shopping management experience for the masses. Like a personal, like think of, think of like, like the good old employment at IBM and GM and GE, like they used to get Costco-like services. Like you get a card and you go shop at that thing and you got everything. Those were the
Karen Webster:days, Simon.
Simon Khalaf:There we go. Yes. They're coming back through AI, right? So the thing is that, Karen, this community has proven to be amazing. They just want a job. They want to work. They want to progress. They want to improve. And we're treating them like we treat royalty because our objective is aligned. They're not a risk to us. Like they are a risk to Chime. They are a risk to Cash App because they're underwriting them. They have no clue what jobs they have, when they're going to pay, right? With us, not only we have visibility into into where they're going to be working, we have a 93% predictability on which job they are going to have in two weeks. And that's what we're underwriting.
Karen Webster:And how many of those jobs they're likely to get over the next months and years. So you've got some predictability with your model to be
Simon Khalaf:able to- That is correct. And it is almost at 100% until we saturate. So we have not reached saturation in any market. We are demand constrained- versus supply constraint. I mean, it's very simple. You look at the average American, right? That's the average. Forget unemployed, employed, whatever. Everybody, right, has an extra half an hour to work on a weekly basis. Now take the significantly underemployed. I mean, today you look at, today, I think a lot of people are trying to explain the election, sorry, the Democratic primary in New York City, right? saying Gen Z is angry because 9% of them are completely unemployed and about 21% is underemployed. Underemployed mean they studied more than what they're earning or they're not getting enough hours. So that's why we believe that, I mean, we have a lot of workers who actually only work nine to 10 shifts just to save money to go on a
Karen Webster:vacation. Right, yeah, it's a different version of a side hustle. It's
Simon Khalaf:a
Karen Webster:side hustle, yes. Congratulations on the new opportunity, the fundraise that went with it. And I look forward to staying in touch as you work toward fulfilling what it is we just talked about, all those great things. Thank
Simon Khalaf:you. Thank you, Karen. I really appreciate it. And I mean, we love what you've done with payments. And honestly, like embedded finance is the future of finance. And there's nothing more embedded than embedding financial services into a job.
Karen Webster:Absolutely. Really, really wonderfully said. Thanks again, Simon. We'll talk soon.
Simon Khalaf:Thank you.
Narrator:That's it for this episode of the PYMNTS podcast, the thinking behind the doing. Conversations with the leaders, transforming payments, commerce, and the digital economy. Be sure to follow us on Spotify and Apple podcasts. You can also catch every episode at pymnts.com/ podcasts. Thanks for listening.