Recruit Holdings Co., Ltd. (6098) Earnings Call Transcript & Summary

Hello, everyone, and welcome to the Recruit Holdings fireside chat at the Goldman Sachs Communacopia Technology Conference. It's a great pleasure to have Hisayuki Idekoba, CEO of Recruit Holdings here today. My name is Minami Munakata. I cover Holdings and Internet entertainment here at Goldman Sachs. We have about 35 minutes for today's session, inclusive of audience Q&A at the end. So with that, Deko-san, thank you very much for being here.

Thank you for having me.

Thank you. So let's get started. So Deko-san, indeed, it began as a job advertisement business, but pay more, get more suggest what employees pay for today is much closer to an actual hiring outcome. So could you walk us through that evolution and how you personally define what indeed is exactly selling.

What need is the exact sitting? So we're selling basically hires. We're setting hires. That's a very important part. And basically, AI technology helped us to make sure that we're delivering qualified candidate. That is the most important part. I'm going to give you a good example. In the past, indeed, it was more like a search engine, meaning like we were charging $1 for this quick, 1 for this quick, 1 data for this quick. It doesn't matter who is clicking it. right? Meaning, like if this quick was done by the person who just graduated high school, just grace it at university, whatever, for 33 years of experience, 20 years of experience. we were charging 1.1.1. So as a result, sometimes employers said, "Oh, we allocate a bunch of budget, we got 200 applications, but quality was not great. But now with AI, we have a plate technology to detect, okay, how qualified this candidate is, who is quicking this? Who is cricking that? Who is clicking this? And we are charging, let's say, the same $3, we're charging $2.7 for 20 years experienced person and probably 0.1, 0.1 from these 2 rigs. As a result, when employers are out getting more budget, they can get qualified candidates sooner. So what's happening is there are so many positions, amples are striving to fill -- when they increase the budget, they can get qualified candidates, not just the quantity of the candidate. That's the big evolution we've been doing for the last 18 months.

Yes, you were selling better experience. So and I think you started to disclose U.S. ApgaKPI. So U.S. grew 35%, while indeed a job posting declined 4%. I get a constant question whether that is sustainable at this level. Yes. Should we expect the U.S. project to slow down from Q2 it?

I'm so focused on the long-term innovation. So -- what I believe is right now, it doesn't matter inside the graders, which employers have 50 people, 100 people in their talent acquisition team. or outsourced, which is staffing agencies or recruiting agencies, importers paying a lot to them. What they're doing is tumor beam is checking thousands of resumes -- if they're qualified or not, and also even if they're qualified, most of the time, what they're doing is they're sometimes reaching out to them, like, "Oh, do you really have drivers right? That's the manual repetitive tasks human being rigors are doing every day. And 5 years later, 10 years later, I really, really want to automate these manual repetitive tasks. And that's our goal. And if we can do it, so what we're doing is really almost like an AI company, right? -- we're -- we have a lot of 2-sided marketplace data. And we are training our model to detect which candidate is a great qualified candidate for this job. -- this specific employer. And so if we can do it, I think it doesn't matter. We should be able to monetize our body because that's the work which is -- there's a cost associated with, right? $350 billion market, 65%, 70% of this $350 billion HR market is the manual cost, human labor cost. And I think people are worried about AIs, changing people job or whatever, like but I think we should automate these things to boost actual productivity of all employers, that's our goal. And so short term, what I've been focusing on is more like -- I'd be very careful about employer satisfaction, print satisfaction and the speed of the change. Because this AI changes so fast, the speed of the change is so quick. So we're delivering value. I've been very careful getting a good feedback from employers, but I've been very careful, okay, is this too fast or not, too quick or not. So that's the balance. I'm very careful, but that's more like my short-term focus.

Great. So let me ask something about your comment about user satisfaction. So take rate is still under 1% implied levy headroom. But you also said you will saw monetization if the value is not there, -- how do you get whether indeed is expensive or cheap? So how much of the value created should indeed capture.

Of course, compared to other like recruiting agencies, which are usually charging 15%, 20% of our Cory, which is very expensive. So most of the time, employers, what they're doing is, okay, this position has been open for 90 days, 120 days. That's the -- most of the time they reach out to recruiting agencies, softing agencies, can you help to fail this position. And so what's happening right now is what we are -- I think most of the time -- we -- I haven't seen the situation is more of the time to fill, meaning like cost per hire is, of course, 1 measurement, most of the time, like large enterprise customers, like monthly budget clients are thinking, okay, what's the cost per hire. But think about it. the cheapest cost per hire, meaning if you can wait 180 days, it has the cheapest cost higher. You can, of course, wait the position to be open and no budget out get it. And if you can wait 180 days, you might get some candidates. You might be able to fill this position. That's the cheaper cost or higher. What's happening right now is if we can deliver qualified candidate in a day or in 3 days, they're happier. That's why they prefer to pay 50% more, 100% more to get the qualified candidate faster. And that's why we're asking them, "Hey, you should try it, you should try it. And it's not only premium sponsored jobs. So -- when we think about AI innovation, which is like happening everywhere, for example, AI sourcing, recruiters, human lead recruiters are checking resumes, online, LinkedIn, indeed, whatever, reaching out to job seekers. But 90% of time or 95% of the time what they're hearing back from job seekers are, "Oh, thank you for reaching out to me. But I'm not actually looking for job right now. And -- but our AI sourcing knows Okay. Job seekers are active checking jobs within 30 days, which jobs seekers are opening e-mails, which jobs because are checking the notifications. So that's why it's so we are charging too much. But actually, what's happening is we're delivering good value and they're happier. That's what we're seeing right now.

So you've got a positive feedback from boss, large enterprises as well?

That's a good question. Big large enterprise have very complex tech stack most of the time, so -- and also it's depending on what level of people we're talking to, like Head of HR or CFO, or COO or CEO, so because -- this time, this is more like an AI change. So that's why we're having more or more meetings with CFO, COO, CEO because most of the time, CHRO is thinking more like HR way. But CFO or CEO is thinking, okay, how to use AI to improve productivity dramatically. So sometimes this top down is happening. So we're trying to have more and more meetings with CEOs.

You also mentioned for large enterprise, it takes some time to make some final decision, right? They needed to test something first, right?

Yes. Actually, at the very beginning of this year, we couldn't have a good growth from the enterprise clients. But finally, we're getting good growth from enterprise clients. It took time, but I think -- of course, these are AI products. Most of the time, we need to go through their Regal and compliance processes. It took time, but we're getting it.

That's great. So let me switch gear a little bit. So indeed, hiring labs view is that demographic, not AI will be the bigger force of the size of the labor market leading to structural shortage through 2040, but likely not the consensus in this room. What informs it, and what does that will do to your monetization?

Mentor people ask me like, hey, do you think AI will have like 20% unemployment rate. AI is replacing human being jobs. Our research showed that for the next 5 years, the impact, especially I'm talking about U.S. market, but the impact of aging workforce is much bigger than AI impact. We are losing experienced skilled baby boomers every day. And these people -- but that's why the impact is not the same for all industries. Think about a percentage of engineers, which are like 60 years old or like a prime 6 years ago is different. So what's happening is, for example, like electricians, you can find existing jobs, which is paying more than [ 200,000 ]. It's so important everybody to build a data center to hire electricians. And that's why also like the construction workers, if you want to hire skilled workers, it's very -- I think it's happening even today. So we're going to do 6 million workers in the next 5 years, 6 million workers. That's almost 4% of the U.S. labor force. And our current employment rate is 4%. So I would say, it sounds weird, but the AI change, AI replacement is too slow to catch up this -- the aging workforce change. aging workforce is for sure happening. That's why our [ competitors ] are struggling to fill positions. And I think the competition is getting worse every day, and that's why they're struggling to fill skilled work positions.. That's why they're happier to pay more. I think actually, the vacancy cost, everybody is underestimating vacancy cost. Actually, I've been talking with some trucking driver trucking companies. Some CEO told me like they have more trucks than drivers, that's the challenge. So that's why most of the big trucking companies are running TDL drivers, license school. They're trying to have their new drivers -- so anyway, so I think I understand that people are worried about AI and job relationships. But the reality is, okay, I'm going to give you 1 more example, software engineering job. Everybody said software engineering jobs will be automated by AI, and everybody will lose jobs. But what we're seeing is last 12 months, increase of hiring demand for software engineering jobs. Why? When we dig deeper into the details, you can see a lot of new job titles, which is AI FX managers, AI compensation designer, AI prompt designers. So what I'm saying is the AI change is not like one-to-one change, meaning like, okay. This AI can replace this person's job. No, it's not happening. Human being is doing many tasks. And one of the tasks or some of the tasks were automated by AI, so it requires a lot of change or a lot of lead designing for the leadership team or CEOs. That's what's happening. That's why I'm very positive that AI is not a job killer, it's more like a job lead designer. That's how I'm thinking. Maybe I'm totally wrong, but from our data point of view, I think I -- that's our view.

Interesting. So if we face more severe shortage of the labor force, the monetization will be accelerated or you will change the monetization model or Indeed?

It's going to be definitely a tailwind for us yes. But I feel bad you said that competition staff, you can make more, I feel bad. But that's the market and competition, what's happening today.

Great. And also a growing number of companies are reporting in AI talking cost cutting into margins. So how are you managing your overall cost to keep investing AI? And how does that factor into the midterm ambition you said last quarter of greater than 50% of margins. .

Yes. We're managing the AI cost separated into two parts, which is external AI cost, meaning like external AI cost job seeker is using AI, employees are using AI. And internal costs, which our employees are using AI. And external AI costs we're lucky, ,we're investing a lot into AI, but we are able to monetize these AI costs. It's -- we can leverage the AI cost to monetize it. So I don't -- I'm not so worried about this part. Internal AI cost, we need -- I need to make sure all the AI investment costs into our employees has to be justified really well. So I need to keep checking almost like every month as the productivity is getting better. The typical numbers that are revenue part one employee, is it going up. So that's how we're checking. And as you guys know that the open weight model is getting really good. And I feel like we're -- of course, we're spending a lot of money for AI, but most of them are more like electricity and the computing power, automotive, I think. And we're very fixable to have -- based on the latency, we can have open wave motor or old model -- and I'm also worried about AI investment cost.

That's great. So we cover a lot of interesting topics. So I'd like to open it up to the audience. If you have any questions, please feel free to raise your hand. Please go ahead.