The a16z Show - Software is Eating Labor

Starting point is 00:00:00 The worldwide SaaS market is about $300 billion per year. The labor market in the U.S. alone is $13 trillion. What software is now going after, the prize that it's going after, is the labor market. Almost every software company has basically taken a filing cabinet and turned it into a database. But what's happening now is the whole thing is effectively done end-to-end. Software ate the world. Now it's coming for labor. At A16Z's LP summit, general partner Alex Rampel, who leads the apps fund, took to the stage to discuss why the real market opportunity isn't the $300 billion SaaS industry.

Starting point is 00:00:39 It's a $13 trillion U.S. labor spend. From filing cabinets turn databases to AI that actually does the job, Alex breaks down outcome-based software, new pricing models, and what happens when agents sell, support, and collect on their own. Let's get into it. I'm going to talk about how software eats labor. First, Mark wrote an essay for the Wall Street Journal a long time ago, about 10 years ago, how about how software eats the world? I guess the labor force falls within the world, so this is a natural follow-up. But if there's only one takeaway that I can leave with you today,

Starting point is 00:01:14 is that the labor market, this is almost obvious, is so much bigger than the software market. So the worldwide SaaS market is about $300 billion per year. Worldwide market cap is about $2.2 trillion. The labor market in the U.S. alone is 13 trillion, so much, much bigger. And it doesn't mean that the software market will suddenly be worth $13 trillion a year, but what software is now going after, the prize that it's going after, is the labor market. And I figured there's nothing better than starting a venture capital conference with a picture

Starting point is 00:01:45 of the world's most famous communist. That's Karl Marx right there. And if you've read Das Kapital, which I read back in college, if you remember, like the central tenant is that there's capital and labor and capital expanse. labor. They're two distinct things. But what's really exciting, this is almost like a chemical equation, is that the capital that you give us, we give to companies, what do the companies do with the capital, they buy GPUs or rent them, they hire engineers, they buy coffee, they give coffee and GPUs to the engineers, and then out-pop software that does the job of labor. It's like the

Starting point is 00:02:18 new E-E-E-E-E-E-E-E-E-E-E-E-E-E-E-E-Cquered. And we're seeing this happen at so many companies and these companies are scaling so quickly because they really are selling into clients or end users and saying, hey, we'll do this job for you. We're not giving you software. We're going to do a job for you. And that's the sales pitch. And obviously, like, this concept is not new per se. I mean, automation has been around for a long time. So, you know, seamstresses, the loom replace those jobs, but you still had somebody that had to operate the loom. Or steamships, sailboats and steamships obviously made that form of labor much more efficient, but you still need somebody to operate and shovel coal into the steamship and put the sales up on the mast. And then, of course, the printing press invented by

Starting point is 00:03:01 Gutenberg, that was a big innovation. And the steam-powered press allowed the LA Times to print out hundreds of thousands of copies of that newspaper versus somebody manually cranking one each time. And lastly, like the assembly line was a massive innovation in terms of replacing people that hand-assembled every gizmo. And now you have an assembly line, but you know, a lot of people worked on the assembly line. So again, this concept is not new. Like you could always take capital, make a machine, and then have more efficient labor on the other side. But what's happening now is the whole thing is effectively done end to end. And I want to take you through a journey of what the software market has always been, because I think understanding the past is the best window of actually

Starting point is 00:03:39 understanding the future and what's possible. So my thesis is that almost every software company has basically taken a filing cabinet and turned it into a database. And This is where the $2.2 trillion of market cap has come from. This is where the $300 billion in annual software revenue has come from. And the first example that I'd like to point to is a company called Sabre Systems. This is with two A's, if you've seen it. It's a company in Texas. But this was a joint project of American Airlines in IBM.

Starting point is 00:04:07 Back when IBM was the most powerful computer company in the world, technology company in the world, because, at least according to Chad, GPT, what would it have looked like to book an airline ticket in 1959? How did the American Airlines handle this? They probably had lots of filing cabinets with sheets like this. So Betty Owens calls up and says, I want to sit in seat 4A, talks to somebody on the phone. Oh, wait, actually, I want to cancel my flight. They have to erase it. No, actually, I want to sit in seat 2C.

Starting point is 00:04:35 Erase that again. Filing cabinets basically kept track of everything. It was pretty inefficient. You had a lot of people that worked the filing cabinets. You couldn't share information from one office to another because everything was domiciled in one filing cabinet. And Sabre changed the game by, putting it all on an IBM mainframe and then having lots of kind of thin client terminals that were used by travel agents around the world that could access that mainframe. And this is how

Starting point is 00:04:57 travel was revolutionized. Galileo did this for hotels. Amadeus did this for Europe. I mean, like big companies came out of this. And of course, the same process happened for sales. So I think somebody yesterday mentioned Glenn Gary, Glenn Ross, great movie. But if you remember, there were lots of business cars. You wanted to get the Glenn Gary leads. Those were the good leads. Those were pieces of paper. And for those of you that are old like me, you might remember a company called Axe Systems in the 1980s. This was one of the big CRM companies of the day. Goldmine followed that in 1990. And then Tom Siebel started Siebel Systems in 1993.

Starting point is 00:05:30 But all of these took the filing cabinets of sales, put them originally in kind of mainframes, and then Salesforce came in 1999 and put that in the cloud. But, you know, again, the same salesperson that accessed the physical file in a fictional movie said in the 1950s would now access a Salesforce record in 2010. Same process, just different medium. Manufacturing in inventory, this is another big one. So imagine that you're a product manufacturer. How many widgets do I own?

Starting point is 00:05:55 What's my inventory? What's my sales? IBM, again, at the forefront of this, but other companies, some that are around today, like SAP, started in 1972, Bond, J.D. Edwards, Epicor, Sage, I2. These are all big companies that basically digitized old-fashioned records. My favorite one, just to show how pervasive this idea is,

Starting point is 00:06:14 is there was actually a big business in library card catalogs. So libraries were, have been around for a very, very long time, library of Alexandria, right? Like, long, long time. The Dewey decibel system comes out. And when I was growing up, I'd go to like the card catalog and figure out, okay, they're all alphabetically sorted. And then eventually somebody created, started with this company called OCLC,

Starting point is 00:06:33 built a reasonably sized business and sort of innovative surcedynics of digitizing those card catalogs where now you enter into a terminal at the computer in the library and then you figure out where your book is, is it in stock? Legal case files, like every time I went to a law firm in the 1980s, it's like most of the square footage was filing cabinets. And companies like PC law, like a lot of LexisNexis and Reuters revenue comes from selling to law firms, digitizing things that would otherwise occupy so much square footage

Starting point is 00:07:02 in the nice Fifth Avenue offices of law firms. My parents were accountants growing up, and I remember going to their office. And again, there was no room for a little five-year-old to run around, because all filing cabinets. Intuit comes along with QuickBooks, digitized financial statements, Peach Tree.

Starting point is 00:07:19 This is a company from the 1970s, NYU, like lots of companies. Again, filing cabinets, filing cabinets. You get the drill here. My favorite name in the history of software is filing cabinets. The first electronic health records company was a company called Mumps,

Starting point is 00:07:32 which arguably is the worst name in the history of software. It somehow lost out to malaria or measles or something, but this was Mass General Hospital, and they wanted to replace their filing cabinets, and they came up with this programming language and database system called Mumps,

Starting point is 00:07:46 but Epic and CERN, or Epic is the biggest electronic health records company in the world, it was started in 1979. So again, and what they did was just digitize these massive number of files that every hospital system and doctor would have in their office. And kind of lastly here, HR and payroll. So actually, even before Sabre, automated data processing,

Starting point is 00:08:04 ADP was started in 1949. How do you keep track of time and attendance? You had your time slip, your time cards, how do I figure out tax withholding, all of these companies came out. And again, the progression was, I take the file, I put it in a mainframe, and then companies, like Workday was effectively PeopleSoft. It was the same team that started PeopleSoft.

Starting point is 00:08:23 They put it in the cloud, but the same process was there. The people that looked at your time in attendance slip in 1940 were the same people that looked at it in 2015, but now the medium was not paper. It was not mainframe. It was cloud. And the reason why I mention all of this is because nothing has actually gotten that much more efficient because the filing cabinets were read by humans, the digital records are read by humans, right? It's like, this woman here, whatever

Starting point is 00:08:46 she's doing, looking at helping a customer with customer support needs or something, once upon a time would have looked at a piece of paper, now is looking at a computer. And the reason why this is so important to understand is because the whole business model of software has to change. It has to change. This is what I call as homage to Starbucks here, the tall, Grandi Venti model of SaaS. If you go to any SaaS company in the world, You go to their landing page, it probably looks like this. This is a company called Zendesk. It's now a private company.

Starting point is 00:09:16 It was taken private by Premier and Helmand and Freeman a few years ago. And this is a $2 billion ARR company that sells seats. So the most popular, like the Venti package is you get the sweet professional $15 a month. But we've talked about in the last couple days how now AI does a really good job answering customer support queries. So how many seats do you need if every one of your agents is 9,000 times more price? Imagine that you have a thousand seats. Imagine that I've got a thousand people working in my customer support call center. I pay each one fully loaded $75,000 dollars a year. So that's $75 million a year in cost for people. Well, what's my software cost? Well, it's $1,000 times 115 times 12. It's about $1.4 million a year for the software. So the people cost is so much higher than the software cost. And this could go one of two directions for a company like Zendesk. If it turns out that AI can answer all the questions, how many seats do you need? zero. You don't need a single seat left. The AI answers everything, and then Zendesk is charging per seat, so they would go from $1.4 million to $0 in revenue. That would be very bad. On the other hand, I mean, look at the math. If each human is answering 2,000 questions a year, right now, you're fully loaded cost as the company that uses Zendesk as your system of record for answering customer support, it's about $37 of human cost and $69 cents of software cost. The cost per answer is $38. I mean, this is rough company example.

Starting point is 00:10:44 Maybe Zendesk could charge $5 million here. Like, hey, don't spend $75 million a year on support anymore. Spend $5 million a year on support. Just pay it all to us. Don't pay us $1.4 million. Pay us $5 million save $75. So Zendesk is really at the precipice if it's like their revenue could go to zero

Starting point is 00:10:59 or their revenue could $3.X. And like, where is it going to go? I don't know the answer. They don't know the answer. I've been talking to their CEO. They're piloting outcome-based pricing in New Zealand right now. So New Zealand holds the answer to all of our questions. So stay tuned. And just to give again another example of just how much bigger

Starting point is 00:11:17 these labor or quasi-labor markets are, like the $13 trillion of wages that we talked about, you know, software revenue is very small. If you just take one category, like just one particular profession and take the example of nurses just because we have a portfolio company in this space, nurses in the United States of America earn about $650 billion here. They're about four and a half million registered nurses. That's bigger than the entire worldwide software market. And it doesn't mean that the nursing software market will be this big, but it means like this is the pool that you're really playing against. And the reason why I wanted to start with the filing cabinets is like this is going to start moving to outcomes. Like the software is going to go from being the

Starting point is 00:11:56 filing cabinet to effectively operating on the filing cabinet. And what does that mean? Well, you know, take the first example. If I have the filing cabinet for travel, you know, maybe the software can rebook flights or I want to book a trip for 75 kids at my son's high school and, you know, to talk to an agent? I don't need to talk to an agent anymore. I just talk to the software company. I talk directly to United Airlines, you know, AI, and they do the entire thing for me. Sales, I mean, this is kind of obvious. You know, Salesforce charges per seat per month. Salesforce should just sell for me. I don't want to pay for a thousand seats. I want to pay for customers. Like, hey, go get me customers because you're the backend for that anyway. Or survey all of my customers, do a 30-minute phone call

Starting point is 00:12:36 with every single one of them, see how they're doing. Are they happy? Are they going to renew with me? Yes or no? You know, what about manufacturing? Well, imagine that I make widgets and there are these things called tariffs that are happening. I'd love to figure out what my tariff exposure is. Let me just ask my ERP system, research that for me. Or I want you to do an audit or call my suppliers and see if they're going to still be able to ship me their things on time. Library card catalogs as crazy as this one is. You know, what if my book is overdue?

Starting point is 00:13:04 The librarian shouldn't be calling me. The library card software company should be calling me saying, hey, buddy, return the book. or order more books because this one's very popular. You know, Ben's book is selling out. Order more copies of that. Legal case files, like a lot of software companies that are popping up in this space, it's no longer the system of record for time and attendance. Like, draft me a contract.

Starting point is 00:13:22 Like, do that work for me. You could start billing out, again, unclear how the pricing model of this is going to work, but start billing for that. Accounting and bookkeeping, you know, AR aging summary. Like, this concept has been around for a long time. I have a lot of companies that owe me money, A lot of clients that owe me money.

Starting point is 00:13:40 In 1940, I'd look at the printout and say, I'm going to call these customers and hopefully collect for them or send the guy with the crowbar or do something. In 2000, I'd look at the QuickBooks thing and do the same thing. Now the software company can go call, like QuickBooks is going to start calling customers of their clients and say, hey, you owe me money, please pay me back. And I can accept a payment on the phone right now. Health records. So if you saw me limp off stage, I sadly had Achilles repair surgery about three months. ago, I don't recommend it. The day after my surgery, I got a call from Stanford Hospital saying, you know, Alex, on a scale of 1 to 10, what's your pain level? And I said 11, and they said very funny.

Starting point is 00:14:17 And I said, no, it really is 11. And an AI nurse can't do CPR, right? An AI nurse can't attend to a gunshot wound victim. But an AI nurse can totally call a mid-40s patient like me and say, how are you doing? Is there anything we can help with? You know, do you have a fever? Oh, you do. You should go to the hospital right now and stuff like that. And again, these are the outcomes, these are the operations that can be performed on if you have my medical record, that's what you do with it. And charge for that, charge $20 for that outbound call. HR and payroll, how do I do a reference check? How do I make sure that on your resume, you said you worked at these three companies? You know what? Workday should call those three companies and say, did Alex really work there? Explain benefits, help with enrollment.

Starting point is 00:15:01 Workday could probably triple their revenue if they start doing this because they're already the system of record. So if you know the story, story of Airbnb. Airbnb famously started by somewhat scraping Craigslist. Craigslist is this horrible site from the mid-90s that has not changed since the mid-90s, and they have lots of listings for apartments, and you go look at an apartment and like half the time it's a scam, half the time it's already been booked, or it's been relisted every single day, and they basically put them in a better interface and called it Airbnb, and that's how they got started. And this is one of the most exciting things that we're seeing, which is here's a real ad on Craigslist, because since I have so much

Starting point is 00:15:36 copious time due to my set Achilles injury. I used to run every day, a bike every day. Can't do that anymore. So I hang on Craigslist looking for jobs. Not for myself, of course. And here's a job for plaza lane optometry. They're hiring a front desk receptionist. And they've had this job opening for six months. It's been hanging out there for six months. The job, like you have to now say in California how much you're going to pay, it's $45,000 a year. So supply and demand, if they probably said we're going to pay $100,000 a year, they would have filled this job. They're paying, they need pay $45,000 a year to make this work within their cost model or something. If you look at the job responsibilities, if you can read this, like the first one is like open and close the shop, lock the door,

Starting point is 00:16:16 AI can't do that. But a lot of the other job responsibilities AI can completely do. It's, you know, argue with insurance company. Call patient the day before their appointment to prevent no-shows. If somebody doesn't show up, that's a big, that's a big opportunity cause for the optometrist. And if you were to look at the optometry market and say, is that a good software market? You would say categorically no, because Plazaelaima optometry probably spends $500 year on software. They probably have a Microsoft office license. They probably have a website with Squarespace or Wix, and that's it. So they probably spend $500 a year. So in this new world, and again, we're seeing a lot of companies doing this. They peruse Craigslist. They look for a job listing, and they're like,

Starting point is 00:16:57 hey, Plazaelaan optometry, I want to apply for the job. And, you know, the optometries like, okay, that sounds great. Tell me about your qualifications, where you've worked before. It's like, I know this sounds crazy, but I'm a software company, and I can't close the doors and do this, but I can do these other eight things. Can I give you a demo? And at first, the optometrist is like, no, I want to, oh, okay, I'll try it out. And by the way, it's $20,000 a year, which is much less than the $45,000 a year that you were going to pay for a human that you can't even hire. So this is happening right now, and it's incredible. And again, like the software spend small for these people, the effective of labor spend much, much higher. And this is what's massively growing the market for a lot of these

Starting point is 00:17:35 obscure industries. So I just thought, rather than me talk, I want to give you an example. This is one of our portfolio company's Happy Robot, which serves the freight and trucking space. So listen, this is a negotiation on the phone conducted with a prospective client and AI. Yep. All right. So this is Joliet Illinois today between 6am and 2 p.m. delivers Monday between between 6 AM and 4 p.m. I have 700 on this one. Would you like to book this load? Gee, I'm going to need 800 for this one. I can check on that. So we can't do eight at this point. Any chance you could come a bit closer to the load board rate? I could do with 775. That's really my lowest.

Starting point is 00:18:19 I understand. So no chance you could do any better than 775. How about 750? Let me see. Okay, I was able to get you 735 here. So that's a closed transact. Who's the robot and who's the human? This is like the new Turing test. I'll let you guys quiz me afterwards on that with your own theories.

Starting point is 00:18:48 Here's another example. This is a company called Salient that does collections. So if you have, if you're a lender, if you're an auto lender, you know, you have to collect loan, you have to collect repayments on your loans. and Salient serves a lot of auto lenders in this country. And here's another call from that. Currently, your account is 51 days past due for $825.35. Would you be able to make a payment today?

Starting point is 00:19:13 I wish to say in Spanish. As I mentioned, his account is 51 days with a month of atrazado of $825.35. He would like to realize a pay-old today with your account? So the cool thing there is that Salient speaks dozens of languages. So it speaks tagalog, it speaks Vietnamese, Mandarin. And again, like, this is a really important point.

Starting point is 00:19:37 It's not just about cost. Cost, like, this is where people are getting this wrong. It's not like, oh, AI is going to take all the jobs because humans are too expensive and AI is cheaper. AI does a bunch of things like intermittent demand is a big one. Imagine that I'm Black Friday retail. I'm a retailer, and people know that, you know, sales are much higher around Black Friday.

Starting point is 00:19:57 So I would have to hire tons of cashiers or if I'm an online retailer, hire lots of customer support people to go answer queries and whatnot. And then what do I do on January 1st? Do I fire them all and then rehire them in November? But actually, I should probably hire them in September because they have to train them. Kind of tricky. And there are a lot of other countries that have intermittent demand issues. I mean, United Airlines, if they have bad weather over Chicago, which of course never happens,

Starting point is 00:20:24 they can't just hire and train 10,000 people overnight. but again, AI very, very good at that. The other example is there are a lot of demoralizing jobs out there. What is a demoralizing job? Well, Collections is kind of a demoralizing job because you go call people and say, hey, you're overdue. About half the time, and I've listened to some of these calls, there are lots of expletives on the other side, right?

Starting point is 00:20:46 So it's like, hey, you owe me money. It's like, F, you never call me again. It's like, call back again. Hey, you owe me money, F, you never call me again. The human would get kind of tired of that. It's not a fun job. AI doesn't get bothered. So again, demoralizing jobs very, very good.

Starting point is 00:21:00 Regulatory certainty. So go back to this. I co-funded a company called the firm. We got trained every quarter on UDAP, unfair deceptive and abusive practices. So there are lots of laws that mandate what you can and can't say to a customer. So imagine you're calling a customer to say, hey, you owe me money. The customer says F you. And then you have somebody on the other end who's had kind of a bad day.

Starting point is 00:21:22 And you can't blame them. It's like FU back customer. They're going to get trouble for that, right? And you have more certainty when you can program effectively a robot to conduct the entire call end-to-end, much more so than people. And my favorite example here is somebody who studied, you know, I speak Russian, Japanese, and a smattering of Spanish, and spent way too much time learning that stuff. Language is languages. I mean, it's just fact that a nurse, an AI nurse, like, what if I only spoke Farsi? Does Stanford have any Farsi-speaking nurses that can call me about my pain level?

Starting point is 00:21:54 what if I only spoke Mongolian? Like, now they do. An AI nurse, an AI collections agent, an AI negotiated. All of these things can be done in dozens of different languages instantly. And you just wouldn't hire a human for that. You can't get somebody in Iowa that speaks Serbian

Starting point is 00:22:10 on demand, intermittently, with the demoralizing job and so on and so forth. You know, AI does great. And it's also very important that AI expands the market. And this is why I wanted to start with the story of filing cabinets because there was no software company for compliance. because this is actually a fact from the Bureau of Labor Statistics.

Starting point is 00:22:28 The fastest growing job in America is manicurist pedicurist. I can't do that. The second fastest is compliance officer. So compliance officer, you don't need software for compliance officers. If you're a city bank, you need more people. And no company has popped up effectively doing software because it's like the software market's kind of small, the people market's very large.

Starting point is 00:22:51 Now you can roll into city and say, I will do compliance for you end-to-end as a software solution, pay me $10 million a year, and on your software product that kind of tracks everything. Because before they would just get more Microsoft Office licenses or collections. Like there is no software company for collections. There are collections, people at collections firms. Now you can actually enter, potentially with the wedge of voice, and this is going to get commoditized quickly, and we realize this,

Starting point is 00:23:18 but you can backfill into a software company with real software revenue, real software margins, real software retention. The other thing that you're going to start seeing us do is there are a lot of non-AI companies that now work because of AI. So because of my said very sad injury, I'm a big cyclist, as I mentioned, my garage looks like this with a lot of bikes that aren't being used. I hope to use them again in the future. Why isn't there an Airbnb for bicycles?

Starting point is 00:23:46 Why hasn't somebody built that? Well, I'll tell you why. It's a very bad idea. That's why nobody's done it. And why is it a bad idea? Because the central tenant AI, AI, not AI, it could be in 2000 BC. it doesn't really matter. If your customer acquisition costs plus your cost of goods sold is greater than your lifetime value, do not proceed. That's not a business. But now with AI, you know,

Starting point is 00:24:07 imagine that I wanted to start Airbnb for bicycles. Well, how am I going to go get the people that have spare bicycles in their garage? Am I going to hire a bunch of like, you know, expensive Stanford kids in Palo Alto and have to give them 20 different flavors of coconut water and, you know, cater to their millennial needs in order for them to work in the sales operation in Palo Alto? No, I'm going to have an AI sales rep call everybody, and the cost per AI sales rep per year is a few hundred bucks, not $100,000, no coconut water necessary. Well, what if there's an emergency? Well, you know, now there's a 1-800 number that you call that's an AI rep that can do everything, call the police, call whatever. And, you know, lastly, like, how do I screen this person do a background check?

Starting point is 00:24:43 Is the bicycle good? Is it stolt? Like, whatever you would need to do this, this silly business that we're not going to fund. AI can do this as well. So you actually have a whole category of business, which was like it would have worked, except for this pesky customer acquisition cost or pesky cost of goods sold. And, of course, AI, you can vibe code your way into one of these businesses. is anyway. So, you know, massively expands the size of the market. The non-AI market, given the AI infrastructure, just allowing, you know, KAC to come down, COGS to come down for now. I mean,

Starting point is 00:25:15 every company is going to start using these tools. So, you know, it will become a version of the Yoga Barakot. It's so crowded. Nobody goes here anymore. But now a lot of companies kind of prosecuting, sometimes older, new ideas that just wouldn't have worked five years ago. And this is a global opportunity, right? I mean, like the U.S. labor market big. It's $13 trillion a year. The worldwide labor market is so much bigger. And our job on behalf of your capital here, our labor on behalf of your capital,

Starting point is 00:25:41 is to find the best companies that will make software look small. So thank you very much. Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating or review, and share it with your friends and family.

Starting point is 00:25:59 For more episodes, go to YouTube, Apple Podcast, and Spotify. Follow us on X at A16Z. and subscribe to our substack at A16Z.substack.com. Thanks again for listening, and I'll see you in the next episode. As a reminder, the content here is for informational purposes only. Should not be taken as legal business, tax, or investment advice, or be used to evaluate any investment or security

Starting point is 00:26:21 and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see a16z.com forward slash disclosures.

The a16z Show - Software is Eating Labor

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