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a16zHow AI is Reshaping Labor Markets: A $Trillion-Dollar Opportunity Explained
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45 min read · 9,306 words- 0:00 – 0:42
Introduction
- ARAlex Rampell
Now you have software agents that are effectively doing what for 65 years had been human work.
- SSSteph Smith
You know, is that gonna increase software revenue 2X? It could potentially increase it 10X.
- DHDavid Haber
It's not even on the same kind of playing field.
- ARAlex Rampell
So all the data's here in the cloud, all the compute is in the cloud, and now you just kinda mix them together.
- DHDavid Haber
Many of these incumbents aren't gonna evolve.
- SSSteph Smith
Every time there's a new technology shift, we have to challenge every investment thesis that we thought was not gonna work, and so many of them now are going to work.
- DHDavid Haber
Moats still matter, and a lot of the moats in software today are, are the same that they've always been.
- ARAlex Rampell
It's, it's kind of both defense and offense for these companies to figure out what the hell to do. [upbeat music]
- 0:42 – 1:58
Historical Evolution of Labor and Technology
- SSSteph Smith
Alex, you wrote an article recently, Input Coffee, Output Code. But this idea of turning capital into labor, hasn't this always been true? What's new here?
- ARAlex Rampell
Well, it certainly has been true for a long time. If you watch some old movie about the Romans, you'd have all these Roman slave laborers or Roman, uh, soldiers that were rowing in unison on a boat, and then of course you got the steamship, and then you don't need these 50 people rowing anymore. Um, so clearly there has been this long period of time, this long historical arc of technology is in some cases augmenting labor. But it was always kind of the brawn and not the brains, right? It's like, uh, I have a bunch of people that are sewing clothes, and now I have the loom.
- SSSteph Smith
Right.
- ARAlex Rampell
But everything that was kind of what we would now call white collar, um, that hasn't happened before. And, and what I talked about was, uh, the three or four different eras of, of software, just storing information. So for the longest time, if I wanted to keep track of who was on my airplane, um, from the Wright brothers onward, um, I would have a filing cabinet with, it's like, oh, here's Pan Am Flight 192.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
And here's who's on it, and I'm writing down their name, and then, you know, they might call or send a telegram back in the old days of, "I don't wanna be on that plane anymore," then I erase it and then I refile
- 1:58 – 4:32
The Digitization of Filing Cabinets
- ARAlex Rampell
it. And one of the first examples of digitization of the filing cabinet was something called Sabre, and this was developed by American Airlines, I think in 1959 or 1960, in concert with IBM. And this was one of the first examples of taking this filing cabinet that really kept track of who's on Pan Am Flight or American Airlines, and putting it in a database. So now instead of having filing cabinets with lots of erasers and white-out, you replace the filing cabinet with a computer, and this in turn begot travel agents and travel agencies because now what was a travel agency and what was a travel agent? They had a thin client, a little computer, a terminal.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
That I, I remember, like, booking airline tickets with my mom in the 1980s. It's like you'd go into the travel agent, and they had a, like, a green screen computer that connected to a mainframe in Texas, which is where Sabre was. So the first realm of software was really kind of called from 1960 onwards, when computers became a thing, of take a filing cabinet, so it could be the HR filing cabinet, it could be the medical filing cabinet, it could be the financial filing cabinet-
- SSSteph Smith
Mm-hmm
- ARAlex Rampell
... and put that in software. So, and what was that? It's a database with a front end to actually go enter things. So Quicken famously did this in the 1980s for financial statements.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
There was a company called PeopleSoft that famously did this. It was the first HR filing cabinet, but put as software. Um, Sabre obviously did this for airline tickets. Um, email I would even argue did it for mail.
- SSSteph Smith
True.
- ARAlex Rampell
Right? It's like you have files of mail, and now you just have a, a filing cabinet, if you will, on your computer. But the, the actions that were done on the software were really the same.
- SSSteph Smith
Mm.
- ARAlex Rampell
So imagine an HR department that has 50 people working in HR. They might have one person that's in charge of the filing cabinets, and the HR person says, "Hey, get me, get me David's file, because I wanna talk to him about something," which is very scary.
- SSSteph Smith
[laughs]
- ARAlex Rampell
Uh, don- don't worry. Uh, but get me David's file. So the, the filing cabinet person, the gopher... This is what the filing cabinet person would often be called.
- SSSteph Smith
Really?
- ARAlex Rampell
The go for something. That's what it means. Gopher. There's the gopher that obviously Bill Murray tries to kill in Caddyshack.
- SSSteph Smith
[laughs]
- ARAlex Rampell
But then there's the gopher of the person who goes for something, right?
- SSSteph Smith
Right.
- ARAlex Rampell
It's like if you are a gopher at Creative Artists Agency, you are going and getting files.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
So that person went away. The filing cabinet went away. It was more efficient from a space perspective. But the 50 HR people are still 50 HR people today.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
So round one of software was really take the filing cabinet and put it, um, not as physical files, but as, as a database with a front end. Round two, which started arguably at, like, 1998, 1999,
- 4:32 – 6:43
The Cloud Revolution
- ARAlex Rampell
and this is what Salesforce did. Like, s- the idea of a customer relationship management product has been around for a long time.
- SSSteph Smith
Yeah.
- ARAlex Rampell
Where a Rolodex is an actual physical thing where you'd put every business card, organize them alphabetically, and you'd find the person that you wanna contact that way. Salesforce put that not in software, but in the cloud.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
So what, uh, QuickBooks had done for a long time, or, uh, something called Great Plains Software had done for a long time, NetSuite did in the cloud.
- SSSteph Smith
Right.
- ARAlex Rampell
Zendesk put email support in the cloud. So it was still software, but instead of having a giant mainframe in your compu- in, in your office somewhere, you now had it in the cloud, which is much, much easier. You don't have to have, like, a dedicated IT team to go, like-
- SSSteph Smith
Mm-hmm
- ARAlex Rampell
... worry about your server, like, exploding in flames if your, your office building burns down or something. So it, it's more secure. So everything that was kind of software 1.0 then became software 2.0, which is in the cloud. Um, and that played out from, call it 1998 to maybe 2010. And then that grew a little bit with the insertion of financial services, because the way that I like to think about this is how many restaurants need and will pay tens of thousands of dollars a year for software? Like, Pan Am needed this in 1960.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
But does a restaurant with one location, are they going to spend $100,000 on a server and pay for software? Like, no-
- SSSteph Smith
Yeah
- ARAlex Rampell
... in 1960, no in 2000. But when the idea of bundling and payment processing became a thing in other financial services, now the market became big enough-
- SSSteph Smith
Mm-hmm
- ARAlex Rampell
... for restaurant software to exist. Because, and this is where Toast came from.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
Toast is a $15 billion company that does this, or ServiceTitan. Again, what's the software market in 1965 for HVAC contractors? Zero. What's the cloud software market for HVAC contractors? Zero. But once you bundle on these other things, it becomes big enough. So, um, but the point that I'm getting to is that the same 50 HR people that worked in 1960 are the same 50 HR people in 2024. The same email support team in 2024 was the phone support bank in 1985, was the letter-writing, you know, typewriter support team in 1965.
- 6:43 – 7:39
AI and the Future of Labor
- ARAlex Rampell
What's exciting about AI is that it's taking this filing cabinet and now allowing actions on the filing cabinet, and that's what I think is really revolutionary because you can actually ask the software filing cabinet application, like Workday, "Hey, I want to add a dependent," and now Workday will do all the work involved with that, and Workday can charge a premium for that. So why is it input coffee and output code? The whole idea is that you now have software engineers that can build products on top of these digital or digitized g- cloud-based filing cabinets that now do the job that the end user of that software product did in 1960, 1970, 1990, 2000, 2010, 2023, 2024. But 2024, 2025 onward, now you have software agents that are effectively doing what for 65 years had been human work.
- SSSteph Smith
Yeah, and that
- 7:39 – 12:29
Economic Implications of AI in the Workforce
- SSSteph Smith
sounds really important, so I wanna underscore that. You kind of went through the eras. You have the non-software era, then you have software, then you moved into cloud, then you have this financial services-enabled cloud era, and now we're in this new era. Can you talk about how, as we chart through these different eras, the scale maybe in this new era is fundamentally different?
- ARAlex Rampell
Yeah, it, it's tr- completely different because it's really comparing wages to software. [lips smack] And to kind of take a, an example from a completely different field that also has no software market, um, there are about 4.7 million registered nurses in the U.S. Average wage for a nurse is a little over $120,000 a year, um, so it's, it's a high-paying profession. And that means that the annual nurse, not software market, but wage market is over $600 billion a year.
- SSSteph Smith
Wow.
- ARAlex Rampell
Which is a lot.
- SSSteph Smith
Yeah.
- ARAlex Rampell
And the worldwide software budget, uh, software market is under $600 billion. Not just America. By the way, th-that nurse figure is just for the U.S. Of course, there are nurses in the UK, and France-
- SSSteph Smith
Yeah
- ARAlex Rampell
... and Angola-
- SSSteph Smith
Of course. [laughs]
- ARAlex Rampell
... like every country on Earth, right? The labor market is enormous, but what is the dedicated software market for nurses? Like, probably zero because nobody took the time to develop software. And you could try-
- SSSteph Smith
Mm
- ARAlex Rampell
... developing software, but it's just there's no, there's, there's no budget.
- SSSteph Smith
The economics didn't make sense.
- ARAlex Rampell
Exactly. If every hospital in the U.S. currently has a nursing shortage and they wanna hire a nurse, or maybe you're in Minneapolis where there's a, a giant Somalian, uh, expat community and you need nurses that speak that language, how do you find them? And-
- SSSteph Smith
Mm-hmm
- ARAlex Rampell
... tr- like, it takes three to four years to actually get trained as a nurse. Now you have a software product that can deliver, not everything that a nurse does. Of course it can't be a phlebotomist. It can't, uh, perform CPR, but it can call you the night before your colonoscopy and say, "Don't eat food." And it can say that in 45 languages, and it can actually have-
- SSSteph Smith
Sure
- ARAlex Rampell
... a conversation with you. So that's a labor example. Or I want somebody... Like, going back to financial services land, um, NetSuite is used by, I think it's, uh, 70% of companies that go public are on NetSuite. It, it's some very, very large-
- SSSteph Smith
I'm sure I've heard a podcast ad with that exact number. [laughs]
- ARAlex Rampell
Yeah, it, it's, maybe it's higher. It's so-something on that order of magnitude. It doesn't... I-if I'm wrong by, by 10 points, it doesn't, uh, belittle the point.
- SSSteph Smith
Yeah.
- ARAlex Rampell
But, [lips smack] uh, the key thing is you always have people that are paying you late. Like, you'll look at your accounts receivable and you'll see, wow, like, a bunch of customers owe me millions of dollars, and that's what you'll see when you look at your financial statements. And then again, this is where humans take the operation on that information. I have teams that are in collections that will go call you and remind you to pay, or I'm gonna cut off the product. That's an operation that can now be done within NetSuite.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
Um, they, they haven't done this yet, but I'm sure they will. And versus charging for, like, the filing cabinet, now they can say, "Well, we know that you wanted to hire five collections people. We know that you pay those collections people $80,000 a year with benefits and everything else. We know that it takes a year to train them. Now our software product can do that, not for $80,000 a year, but for $2,000 a year."
- SSSteph Smith
Mm.
- ARAlex Rampell
And that's incredible. So it really is augmenting... I mean, the, the question will, is actually how will the customer think about this? Will they really say... 'Cause o-once they start paying NetSuite 10 times more than they paid NetSuite last year, they're like, "Wow, my software budget has ballooned. I gotta cut my software spend." Or will they say, "Wow, I'm saving so much money, um, because as opposed to these five job openings that have, you know, I'm waiting to pay $400,000 a year for these five collections people, now I can pay $10,000 a year to NetSuite, and I'm paying more for software but less for labor"? And that, that part, it's very, very new, but a lot of the hypergrowth that we're seeing in this category of company is because they are really moving into the labor market-
- SSSteph Smith
Yeah
- ARAlex Rampell
... and less the software market. And, and that nurse example is kind of a prime example of that.
- SSSteph Smith
Definitely. It'll be very interesting to see the appetite. If you think back to the App Store early days when people were so, uh, reticent to pay 99 cents for an app w- for arbitrary reasons but just because it was what they were used to paying. So I wanna talk about, uh, pricing and whether companies are adapting and also consumers. But super quickly as we round out these eras of clouds, maybe it'd be interesting to just have you touch on how the previous eras have actually set us up for this one, right? You mentioned things like PeopleSoft or Quicken or Zendesk and all these companies that are capturing data. How are we uniquely set up now because of the previous eras?
- ARAlex Rampell
Yeah. So I would argue that if we just went straight to AI in 1960, like, this just wouldn't have worked because you still need human input to go, like, collect the customer information, put it there. Like, we have everything built out Where right now, um, this isn't an API, but if I wanna go answer a customer question, the question's already on the computer, it's already on the internet, it's already in a database. Like, all of these things have set this up to be the ultimate platform,
- 12:29 – 17:37
The Role of Systems of Record
- ARAlex Rampell
so-
- ASAngela Strange
Mm-hmm
- ARAlex Rampell
... th- this is why we love investing in what I would call systems of record. And a system of record is just something that has every single piece of minutia that runs a business. And it could be the strangest business that you can imagine. Like, if I'm running a laundromat, there is actually dedicated laundromat management software. All of these systems of record that have popped up for all sorts of different businesses and all sorts of consumer use cases, like the fact that now the mainstream form of communication for many, many adults and children is texting and email. Like, it's not voice, it's not calling your parents that you haven't talked to in a long time. It's all in the cloud. Now you can perform these operations. So, you know, I, I would almost say there's been a 60-year period of digita- digitization of physical things, putting them in the cloud so you actually... You know, why, why is the cloud part important? Well, again, if this were the mainframe era of the 1970s, how would you get the AI to go, like, that's in some Google server somewhere, like thousands of servers. How would it actually have access to all the information that's in some server basement in Indiana? Like, that, that's really hard to do. So all the data's here in the cloud, all the compute is in the cloud, and now you just kinda mix them together. So, um, the fact that systems of record for so many different types of businesses and so many different kinds of consumer use cases are now widespread, and, you know, hundreds of billions of dollars of company market cap has been created from these systems of record, either horizontal or vertical. And a vertical one would be something like a Toast that vertically runs a restaurant, and a horizontal one would be like a Zendesk that just does customer support software in the cloud, but it does it for every different type of company.
- ASAngela Strange
Building on that, if you take the Toast example, like, start with the cloud wave, move to the financial services wave, it was initially a hypothesis that these vertical SaaS companies would make a lot more from financial services.
- ARAlex Rampell
Mm-hmm.
- ASAngela Strange
Fast-forward to today, 80% of Toast revenue is payments, insurance, like all sorts of financial services versus software. And so as we think the next wave is gonna be, you know, if you're operating Toast, or one of my favorite examples is Mindbody, which runs, you know, fitness studio software.
- ARAlex Rampell
Mm-hmm.
- ASAngela Strange
It does scheduling for employees. It's a CRM. They also make a lot of money from financial services. But they still need a lot of people beyond... You know, you're never gonna replace a yoga instructor, but you've got your financial back office. You've got people answering the phone to answer very basic questions. Like, all of that can start to be done with AI, and I think the most bullish version of that is, all right, you then don't need to hire people to do the tasks that are not human-facing that AI can do better. You know, is that gonna increase software revenue 2X? It could potentially increase it 10X, depending on how the customer views it and how much they're willing to let their software budget bleed into their labor budget.
- DHDavid Haber
I think part of the challenge or, or the potential for disruption is that the pricing model may need to change pretty significantly, right? You talk a, a bit about this in your piece, Alex, w- where, you know, Zendesk today is charging on a per-seat basis, but if you're, if you're actually eating away at some of the labor, you can charge for the output of work, right? And, and how does that sort of create the potential both for increased ACV, but again, creates, uh, you know, potential disruption for a lot of these larger incumbent players, given their existing kind of pricing structure.
- ASAngela Strange
Can we actually talk about that example from Zendesk? Like, what is the difference between the software component and the human component?
- ARAlex Rampell
Well, so it, it's, it shows how stark the difference is. So most companies, like Salesforce charges per seat. Zendesk, at the time that I wrote my piece... They might have changed their pricing a little bit, but it was $115 per seat per month. So imagine that you have 1,000 people that work in a call center, or really more of an email-based support center, and they use Zendesk, and Zendesk then profits as you hire more people because 1,000 is better than 100. So $115,000 a month is about $1.4 million a year in spend on software for Zendesk, and Zendesk I think has about $2 billion in revenue.
- ASAngela Strange
Mm-hmm.
- ARAlex Rampell
Something on that order of magnitude of, of, you know, annual recurring revenue, uh, from all these seats that are paying every single month. And of course, they want their customers to grow seats. Now, if you assume that each seat, how much is that person paid? How much does their healthcare cost? How much does their, you know, stipend for commuting and, you know, yoga benefit-
- ASAngela Strange
[laughs]
- ARAlex Rampell
... and all these other things that the company throws in. Um, you know, maybe it's $50,000 a year per person. So what's 50,000 times 1,000? Again, 1,000 seats.
- ASAngela Strange
Mm-hmm.
- ARAlex Rampell
That's $50 million. So you're spending $50 million on people. Um, and by the way, it's very hard to hire and train these people. So I think one misnomer is like, "Oh, AI is terrible. It's gonna end all employment, and it's gonna be chaos." I always like to point out that when the United States was founded, um, 97% of people in the U.S. were farmers, and most of them were put out of jobs by things like the tractor, but that's actually fine because they moved on to other kind of productive parts of labor. And by the way, the, the average life expectancy was a little over 30 back then.
- ASAngela Strange
Right.
- ARAlex Rampell
So I, I feel like things have gotten-
- ASAngela Strange
I'll take what we have. [laughs]
- ARAlex Rampell
Things have gotten better. Like, I, I, I like, uh, I like penicillin and all the other benefits that-
- ASAngela Strange
Me too
- ARAlex Rampell
... we've gotten, and fertilizer and all these things that have
- 17:37 – 20:55
Challenges and Opportunities for Incumbent Software Companies
- ARAlex Rampell
made our lives better. But so you have $50 million a year for people, um, and then you have $1.4 million a year for software. Which one's bigger? And this is the concern, is that on the intermediate basis... And Zendesk is actually very lucky because they got... They were a public company, and they got taken private, so two big pub-
- ASAngela Strange
Mm
- ARAlex Rampell
... uh, private equity firms bought it, and they're actually working on this right now because they're like, "Uh-oh, if we make AI really good, then the customer that has 1,000 seats might cut down to 10 seats." Because, uh, there are two forms of AI tools. I mean, there, there's more than two, but the, the common example that we talk about is there's autopilot-
- ASAngela Strange
Mm-hmm
- ARAlex Rampell
... and then there's copilot. So copilot is like a productivity enhancer. So I'm trying to figure out, how do I answer Angela's query? It has all these questions. I just got hired yesterday. I don't even know where the bathroom is. What do I do?
- SSSteph Smith
[chuckles]
- ARAlex Rampell
And then it kinda gives me... It's like, "Hey, we think this is the right answer." It makes Angela so much more productive in her job, and that's great. Um, autopilot is like, Angela quit yesterday, and we need somebody else to go answer emails because it's, you know, Black Friday. What do we do? What do we do? Okay, now we just kind of throw the tool at the customer directly and have them answer the questions, and that's the big danger. It's like Copilot is actually a danger for revenue as well because why do I have 1,000 support reps? I have 1,000 customer support reps because they can only answer 10 questions a day.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
And I get 10,000 queries a day, so it's just basic math. If now with Copilot, each one of my reps can answer 100 questions a day, I only need 100 reps. So now Zendesk lost 90% of its revenue. And then by the way, if autopilot becomes a thing and it actually works very, very well, then I need nobody, and then therefore I sell no seats if I'm Zendesk. So it's a real, real... It's, it's kind of both defense and offense for these companies to figure out what the hell to do because if they play offense, they could maybe 10X their revenue because of the example. Like, it's like $50 million for people or $1.4 million for s- I'd rather get $50 million-
- SSSteph Smith
Yeah
- ARAlex Rampell
... if I'm Zendesk than $1.4 million. But they're probably not gonna be able to take all 50 million, right? Because ultimately, like, the cost of delivering these services is very low. The moat is not that high. It's higher for people, for companies that have the system of record, I would argue, because all of your past correspondence with all of your customers is in, uh, Zendesk. Or if I'm Salesforce, like every single communication that I've ever had with any of my customers, my pipeline, everything, it's in Salesforce. It's hard to yank that stuff out because everybody's using it, and it's not like this binary thing where like tomorrow we're all autopilot. Like we're gonna see a lot of these copilot tools. They will run on the systems of record. Um, but even as they're running on the systems of record, now I need less seats. So that's why, you know, Salesforce, it's a $200 billion-plus public company. If they don't do this right, they could lose all of their revenue or most of it. If they do it really well, they could 10X their revenue, and it's like, where, where is it gonna go?
- DHDavid Haber
A- as early-stage VCs, we're very excited about this. [chuckles]
- ARAlex Rampell
Yes, yes, I know. It's all-
- SSSteph Smith
No, no
- ARAlex Rampell
... it's all upside for us. [laughs]
- SSSteph Smith
I mean, this is, this is the question, right?
- DHDavid Haber
Yeah.
- SSSteph Smith
We're learning more about finding the next entrepreneurs-
- DHDavid Haber
Correct, yes
- SSSteph Smith
... versus the, uh, the fate of the incumbents. Yes.
- DHDavid Haber
Well, it, it's an interesting moment in time for kind of, you know, enterprising young founders to kinda reinvent the model and, and charge radically different, you know, because many of these incumbents aren't gonna evolve.
- ARAlex Rampell
Yeah.
- DHDavid Haber
You know, they're not gonna change their per-seat pricing, and they
- 20:55 – 22:01
The Messy Inbox Problem
- DHDavid Haber
risk disruption.
- SSSteph Smith
And is that the wedge, right? If, if you're a startup and you're trying to figure out, "How do I enter the market?" Especially when you have companies like Salesforce which have the system of record, they have all the data, they have all the customers. Is that the wedge where you say, "I'm gonna undercut and I'm gonna charge a tenth of the price even though I still have great margins 'cause I'm entering the labor part of the equation"?
- DHDavid Haber
I think so, yeah. I mean, I, I wrote a piece recently that I called "The Messy Inbox Problem," which is cr- sort of my way of describing a wedge strategy that we're seeing across lots of different industries. And the idea is basically that, um, there's a, a class of founders that are start- uh, building software products to solve a lot of the, you know, what was historically judgment-intensive work. You know, i- in lots of different industries, there is some sort of human administrator's job. It is to basically extract information from a, a wave of unstructured information, whether it's emails, faxes, you know, transcribing phone calls, and then put that information into one of these downstream, you know, systems of record. Could be an EMR, could be an ERP, uh, it could be a CRM system. And historically, you know, that work lived kind of upstream of any of that software,
- 22:01 – 22:31
AI's Role in Transforming Workflows
- DHDavid Haber
right? Because it was the human's job, and software couldn't do that, as, as Alex described. Now we're seeing, you know, companies sort of wedge in and re-replace, again, that messy inbox problem with software and slowly begin to eat away at all the kind of downstream workflows. And over time, I think the, the thesis is that while that initial wedge, uh, is highly differentiated, you know, against the human, uh, it, it really is the opportunity to kind of eat away at everything else and become the kind of new AI-native, you know, system of record.
- 22:31 – 23:36
Case Study: Tennr Healthcare
- DHDavid Haber
Um, we have a company, you know, as an example, called Tennr, that is doing this i- in a healthcare context. So, you know, the problem that they're solving specifically is, uh, is around patient referrals. So you go to your general practitioner. They're referring you to a specialist. Could be a dermatologist or an imaging center. Today, they're often faxing your medical records, and it is somebody's job to go physically to the fax machine, you know, take that physical fax, reenter that information into that, to the EMR system. Tennr has trained a model against, I think, 4 million, you know, healthcare-specific documents and now can basically extract all that information about the patient programmatically and have effectively begin to solve, you know, f- this sort of patient intake problem, and they're able to reduce now about 90% of the admin costs, you know, of that patient intake before the patient's actually seeing the, the, the clinician. Um, so they, again, wedged in with the messy inbox problem, and over time they're now eating away at things like scheduling and, uh, eligibility and benefits. Um, and, you know, o- over time we'll see if they become the kinda core AI-native system of record.
- 23:36 – 26:01
Defensibility and Differentiation in AI
- SSSteph Smith
And something you're pointing to there is also the defensibility of it all, right? So you can get the wedge maybe through pricing, but how do you actually protect your customers? I think one place people jump to is, okay, you need your own models or you need some sort of proprietary data. Is that the defensibility of, you know, this future, or how do you think about that?
- DHDavid Haber
It's sort of this distinction between differentiation and, and defensibility. I think AI is an incredible catalyst for differentiation, right? Solving the mes- the messy inbox problem with software is 1,000 times better than the human doing it. It's not even on the same kind of playing field. Super differentiated way to sort of wedge in and, again, kind of own the downstreet workflow. Is that wedge product alone defensible? I would argue no, right? Today it feels like magic to the providers that they're working with, but I think that capability is gonna become commoditized over time. They may have an advantage because they've trained a model, you know, for now, but I think that is ephemeral. I think the defensibility comes from, again, owning all of the downstream workflows, deeply integrating themselves into every other system that they have, effectively owning that sort of, you know, core kinda end-to-end workflow. And I guess the hot take would be, you know, that moats still matter, and a lot of the moats in software today are, are the same that they've always been, right? So becoming a system of record, you know, having a network effect, becoming a platform, having virality baked into your product, deeply embedding yourself, you know, in, you know, into the existing system so it's hard to rip out. Like, these were all of the heuristics that we would always have looked for in software. I think that... And they're still true today.
- ARAlex Rampell
So I agree with all of that. The other way to think about this is why did software start with airlines? Well, people, everybody traveled. Not everybody, but a lot of people traveled. Airplane tickets were very expensive-
- DHDavid Haber
Mm-hmm
- ARAlex Rampell
... and this was kind of a pittance for them, and it made so much sense versus having, like, throngs of filing cabinets and gophers, and it makes sense to go pay, you know, hundreds of thousands of dollars in 1960s money to go buy some giant IBM mainframe. And this is kinda why I brought up that financial services example. Like, software for restaurants did not make sense. It just wasn't a problem to be solved, and the market wasn't big enough.
- ASAngela Strange
Mm-hmm.
- ARAlex Rampell
And you made the market big enough once, to Angela's point, you threw in, like, payment processing and insurance, all, all these other things that they were paying for anyway. So you can either try to come up with a wedge, as, as David mentioned, and then figure out how you kind of expand your wedge and make it defensible and become the system of record.
- 26:01 – 29:26
Emerging Opportunities in Compliance
- ARAlex Rampell
The other thing that you do is you just find, like, things like restaurants in 1980 that just, like, have no software and needed no software, wouldn't pay for software, but their labor budgets are enormous. And, uh, sometimes you don't know what these things are, but, like, the example that I would give here, what is the incumbent software product for compliance officers at banks and financial institutions? Like, I don't... Like, Excel? Word? Uh, Microsoft Edge browser looking for bad things? [laughing] Um, these are... Well, what does a compliance officer do? I mean, it's, it's now in the news a lot because of this de-banking thing, and I found this on the Bureau of Labor Statistics. The fourth fastest-growing job in America is compliance officer. There isn't an incumbent software product that they use. Every bank and financial services company on Earth, um, they're all hiring for compliance officers. It takes a long time to train them, and what if account openings goes down? I don't need as many. What if account openings go up? I need more. Um, it takes, like, in some cases, like, a month to open a business bank account at a bank because the compliance officer or the compliance officers are backlogged.
- ASAngela Strange
Mm.
- ARAlex Rampell
What if you deliver that via software, right? And there is no software. There is no incumbent that can now, like, add this AI module in the same way that NetSuite was an incumbent for accountants and financial officers at companies, where they can add a module for AI work of collecting money. Um, so you find these other areas where there really isn't an incumbent, or the incumbent is like, it's like Microsoft Excel. These, sometimes these are just so bizarre. Like, I wouldn't think about, like, compliance officer until I saw this, like, random report from the Bureau of Labor Statistics that showed manicurist is number one, and then, and that's a hard one to have AI do. [laughing]
- ASAngela Strange
[laughs]
- ARAlex Rampell
Um, and then number four is compliance officer, and then you kinda look and you talk to banks. They're like, "What software do you use?" And it's like, "Excel." Again, giant labor budget, not enough people that are using software. That's one of just, like, you can not have to worry about the incumbent-
- ASAngela Strange
Mm-hmm
- ARAlex Rampell
... layering in something. And it still is a wedge, but you could probably turn it into a system of record. And why, why were no venture-backed companies or even non-venture-backed companies built in this space? It's just like, well, I can't charge that much money. It's just not a big market, in the same way that, like, there was no restaurant software market in 1980. It's the exact same reason, but there's enough budget there to go fill this, like, very, very pressing need.
- ASAngela Strange
I think one of the, one of the most interesting parts of our job is every time there's a new technology shift, we have to challenge every investment thesis that we thought was not gonna work, and so many of them now are going to work. If we come back to financial services, there's a lot of pretty terrible systems of record where smart people have tried to get them ripped and replaced and just, it was just not gonna happen. And my new conclusion with AI is not that they would never do it. It's that the replacements were 2X better. They weren't 10X better. And so if we come back to compliance, lots in Excel, but if, like, for instance, you've probably read the $4 billion fine by TD in transaction monitoring, right?
- DHDavid Haber
Mm.
- ASAngela Strange
And so they said on an old transaction monitoring system, Actimize is one of them. They should probably get one that throws up fewer false alerts, but they were trying to clear a backlog of several tens of thousands alerts. They can't hire enough compliance people. So now an interesting wedge in is we'll provide you with all of these agents, and oh, by the way, we also have a much better transaction monitoring system that is actually gonna fix the problem. So this labor plus software bundle also helps the sales process and then helps the defensibility 'cause you're really solving the major problem, which is better software, and also I can't hire the people.
- 29:26 – 33:11
AI's Impact on Job Roles and Market Dynamics
- DHDavid Haber
Yeah, and I think that's such an important point because you all have pointed out different areas where, quite frankly, the labor is not there. And so as we're talking about software disrupting labor, the natural question is, okay, so what happens to all these jobs? But maybe we can talk about both that and the flip side of what new jobs are created because, you know, even if we talk about the previous arcs, we saw, what, product managers, UX designers, social media managers. Those were all remnants of the previous era. Um, how do we think this will kind of shape up in terms of new jobs and then also how existing jobs change?
- ARAlex Rampell
It's always hard to prophesy these things-
- DHDavid Haber
Yeah
- ARAlex Rampell
... because in 1789 or something, it would be hard to say, like, what, what will these farmers be doing, uh, post tractor and po- post-
- DHDavid Haber
Sitting in a room talking. [laughs]
- ARAlex Rampell
Exactly. Talk, talking with these, these electronic microphones and this, like, amazing fire.
- ASAngela Strange
Barb, if I were to podcast-
- ARAlex Rampell
Look at, look at the fire, the fire in the sky here that we have in the basement.
- DHDavid Haber
Our ancestors would be proud.
- ARAlex Rampell
Exactly. So, um, or, uh, you know, what, what, what was a nurse, right?
- DHDavid Haber
Right.
- ARAlex Rampell
It's like medicine was bloodletting, leeches, and prayer, so it, it's obviously changed a lot. So, um- On the one thing that I think AI cannot do, um, and in fact, if anything, it kind of commoditizes, like if you have an AI sales rep. Like Salesforce, why do I need seats for salespeople if AI is doing selling? But AI cannot build a relationship with somebody over golf. So I, I think the in-person, like the things that only humans can do, that, uh, that skill set might go up in value tremendously. It obviously makes sense that, I mean, like at the far extreme, I, I talked to somebody who believes that in the future, the, the distant future, there will only be two jobs. You either tell a computer what to do-
- ASAngela Strange
Mm-hmm
- ARAlex Rampell
... or you are told by a computer what to do. Um, and there's a whole set of things where people could be a lot more productive in whatever job they're doing, or kind of like part-time work when you have this little coach by your side saying, "Do this, do that." But I, I think the, the human connection thing is almost the more, most important because if I think about every other era of like a new communications tool, um, so imagine having the first telephone. You know, Alexander Graham Bell invents the telephone. Nobody has a telephone. Like, how do you scale this network? You know, you get one, and the only person that calls you is y- your, your mother saying, "Why don't you call me more often?" or something. So, um, then the first telemarketer shows up and then starts taking advantage of the fact that you have a phone and they can, rather than like go horse and buggy to your house, they can try selling you something over this like old-fashioned, you know, telephone. Um, that was a very advantageous place for the, that first telephone telemarketer to be. Or the, the history of Sears Roebuck or Sears is really fascinating because even though they, they had the Sears Tower, they had these, you know, giant stores, it really was the first, like, giant mail order catalog. So they were the ones that kind of figured out how to use the US Postal Service.
- ASAngela Strange
Mm.
- ARAlex Rampell
Faxes came out. People started sending unsolicited faxes. So the reason why I bring all this up is you can imagine a world where like all of... Like AI is selling you everything, pushing you everything, and then right now it's a novelty and it works really well. But once it becomes so mainstream that everybody's doing it, it's like this Yogi Berra expression, like it's so crowded, nobody goes here anymore. You can imagine like the need for actual human connectivity to go up dramatically.
- ASAngela Strange
Mm-hmm.
- ARAlex Rampell
It's followed this pattern of like once it gets so crowded, like the, somebody that's doing something different, in this case the old-fashioned way, like might be more valuable.
- ASAngela Strange
One of the ways we think about it is, like all of us have some percentage of our job that's rote tasks that could be automated with AI, and I think we strongly believe that at least every white collar job is gonna have a copilot. Some might be fully agentic, you know, back to our L1 compliance reviewers. And so if you imagine all of us not doing any menial tasks or anyone and focusing on the human connection, the most creative parts, and having all of our days to spend on that, like what might be enabled, and that's a pretty exciting
- 33:11 – 36:47
Metrics and Market Size
- ASAngela Strange
way to think about it.
- SSSteph Smith
And as we think about the companies that can be created in this wave, I'm so curious, because it does feel fundamentally different. As you three are assessing companies, are there a new layer of metrics that you pay attention to? Again, using a previous wave, maybe we got social media, and all of a sudden we're thinking of daily active users. That was kind of a key metric that people started to pay attention to. In this new wave, like are there new metrics? Are they the same metrics that matter? Is it too early to tell? I'm so curious.
- ARAlex Rampell
I think it's actually the exact same metrics. It's not like, "Ooh, it's AI, so therefore future profits don't matter." It's like it's the present value of future profits, and that really comes down to like how many customers do you have, do you retain those customers, and then how much gross profit do you make per customer, and then how much overhead do you have? And I don't think any of that changes. So I mean, the reason why social networks were interesting is we knew that the customers retained.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
Right? But it's like, will people pay for it? Will it make money? There was this open question, and therefore there was this, if you will, alpha of, oh wow, like it, uh, we, we call this the smile curve-
- SSSteph Smith
Yeah
- ARAlex Rampell
... which is very rare, where like more people... Obviously 100% of people use the product on day zero because day zero is when they installed it, but then people stop using it on day one, day two, day three. And normally most products, they just have exponential decay.
- SSSteph Smith
Yeah.
- ARAlex Rampell
So by day 200, you know, of the 100 people that downloaded it on day zero, zero people use it at the end. Um, what's interesting is things like Uber or Facebook, where again, 100% of people use it on day zero, then it drops off on day one, day two, and then it picks back up.
- SSSteph Smith
Yeah.
- ARAlex Rampell
And then it plateaus at maybe 50, 70, 90% of the original starting bunch, and that's so rare. But then the question was, will Facebook ever make money? Like, ah, they won't make money because it's free. But they figured out that advertising was very valuable. Um, I, I think the vast majority of things that we're seeing right now just monetize via subscription, so it's actually very clear how they make money, and the DAU thing is actually just as useful today as it was before, but it's like the, the money part is almost automatic.
- SSSteph Smith
Hmm.
- ARAlex Rampell
Like the thing that was unique about the, the internet era was it's like, oh, like get big and then monetize later, and we're not seeing as many of those, but I don't think any of the fundamental isms of evaluating a business have really changed. I mean, if... The, the only thing that's kind of more dangerous is since AI can now write software, it's just so much easier to spin these things up, whereas to build something and scale it out, like, you know, the reason why Friendster failed, like Friendster should've been the social networking winner, but their servers couldn't stay up.
- SSSteph Smith
Hmm.
- ARAlex Rampell
Um, and MySpace should've been the winner, but they couldn't hire good engineers. Like there are all these different reasons that are not relevant today because the technology stack is so different. But again, it's, you know, present value of future profits, that's unchanged.
- ASAngela Strange
I think one thing, and this is not a business metric, but that's changed is just potential market size, and we talked about how it scales in the large vertical SaaS markets. But if we look... So there's something in the, in the US called the, uh, North American Industry Classification System, the NAICS codes, and there's 600 of them, and they'll classify industries, how many companies are in there, what's their, what's their labor budget. And there's a whole host of industries, whereas if you looked at them before, you say, "Well, there's 1,000 potential buyers. Maybe they'll pay $1,000 a month for my software service. That's a $120 million market. That's really not that interesting if I'm gonna build a venture-backed business." Now if you think you can layer in AI, replace some of the labor budgets, those markets get dramatically bigger. And so I think the different pockets of where software can be built, these niche markets that weren't that interesting, are now potentially very interesting.
- 36:47 – 42:26
AI in Professional Services and Legal
- DHDavid Haber
I think the other dimension that we're seeing kind of pitches for is, you know, are you selling software into the incumbent industry or are you building kind of the full stack version, right? And w- we-- Alex wrote a bit about this in, in kind of Barbarians at the Gate, you know, which is sort of like the evolution of private equity kind of in an AI context. And so if you think about an area like professional services or in legal, you know, for example, you know, the challenge that a lot of these law firms have is that they're charging on a per-hour basis, right? So if AI can do what used to take three hours in three seconds, you know, where does the revenue go? And so we're seeing some people pitch the full stack kind of AI-native law firm, which might have a totally different cost structure, you know, to Carath or, you know, one of these big firms. Um, or there are s- other areas within professional services that are much more aligned, you know, to benefit from that efficiency. So, for example, we have a company that we, we haven't announced yet, so I won't, I won't mention the name, but that is solving a lot of the workflow challenges in, uh, in plaintiff law. So they operate in both employment and personal injury, where in, in that model, unlike on a per-hour basis, they're charging on a contingency model, meaning they don't get paid unless there's an outcome or a settlement of the case. And in, in, you know, personal injury, as an example, for every 100 leads that these lawyers get, they take one case. You know, and, and there's a ton of, again, that messy inbox problem of sifting through, you know, medical records or employment documents and having to essentially value, you know, or quantify the value of each case that, that they'll take on, because any, any case that they t- that they take is essentially an investment of their labor. Um, and so what this company is doing is essentially programmatically helping solve that sort of intake challenge, that messy inbox problem, to help automatically qualify the value of those cases, and then works essentially as a co-pilot, you know, for the lawyer to, you know, draft a medical chronology, to create a demand letter, to, to file, you know, a complaint, and basically walks through the entire sort of pre-litigation and, and litigation process that essentially allows that lawyer to take on, you know, three X or four X the number of cases. But again, that, that-- the value that that software is delivering to the practice isn't so much... I mean, it, it is also reducing labor costs, so one way to do it is, you know, you just have fewer law- you know, lawyers and, and the same amount of revenue. Or in this case, I think what's gonna happen is it's gonna significantly grow these practices. And, and in this case, they're actually passing the cost of that software to the end client in the form of a technology expense, which they often, you know, had done historically. And so the value that the software is delivering to each of these firms is super aligned, you know, to the impact that it's having on the business. And so I think, you know, the more clients you can take on, the more people that can pay for, for the software, and so on a per-firm basis, there's a significant kind of revenue expansion opportunity. I think that's sort of an interesting tension that you'll see across industries where, you know, does AI help, you know, by reducing cost? Is it bet- better to build a full stack version or sell the software in? And I think there'll be successes in both dimensions, but it's something we're, we're seeing more of.
- SSSteph Smith
Yeah. And one follow-up there, as you're talking about the cost being passed along to the end user or buyer, is that just net deflationary as this permeates across the system? I know it would take time, but, uh, eventually, if you see more competition and more people creating these AI-based, uh, labor products, and then people are competing on price, and all of a sudden, you know, to take on a new case, it's no longer $5,000, it's $500. You know how you said that in the previous era, the open question was, can we make money? Can we monetize? Is that an open question that, you know, this over time j- just becomes deflationary and firms can't charge as much?
- ARAlex Rampell
I think technology, if it's done right, is always deflationary, um, because you get productivity gains. So I think for sure, I think the defensibility point is the, is the most relevant one that we struggle with a lot, which is, wow, it's so easy to build one of these things because the number one use case, it's almost like a recursive thing. It's like, well, what's the best u- who-- which profession is using AI tools the most? It's probably the tech people that actually build tools, and that's where things like Cursor have gotten so popular.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
But what if there are 50 companies that end up doing the exact same thing? Um, [lip smack] that's, that's the hard part. But I think I, I can't see a scenario where prices are more expensive than humans or where prices don't just keep going down.
- SSSteph Smith
Mm-hmm.
- ARAlex Rampell
Um, because that-
- SSSteph Smith
And significantly.
- ARAlex Rampell
Significantly. And that, that's the history of, of technology in, in a nutshell. I mean, again, it's like the 100-megabyte hard drive in 1960 that weighed, like, tons, literally tons-
- SSSteph Smith
[chuckles]
- ARAlex Rampell
... uh, was probably a million dollars or something crazy, and now it's just comical. Like these little... I bought some for Cyber Monday. I bought all these, like, little micro SSDs for, like, a terabyte was, like, $10. It's just incredible. So I think that is an in- an inexorable process for technology cost in general. And then you also get new use cases where, I mean, I like this right of the supply-demand curve. This is a really interesting use case where it's like there just wasn't demand where there was supply. There's a lot of supply to do something for $2,000 an hour if I wanna, you know, file a trademark with the leading trademark attorney. So the trademark market or the patent market, like, that might be very small because it costs too much. But now if it only costs $5, wow, maybe everybody does it.
- SSSteph Smith
Mm.
- ARAlex Rampell
Um, so those... Or like translation is one that I find fascinating, where it's like it just doesn't make sense if you're a small company to go translate your introductory video into, like, 45,000 different languages that have ever existed. Like, why would I translate it into ancient Greek? But you know what? Why not? It's free.
- SSSteph Smith
Now you can.
- ARAlex Rampell
Like, so you have all these other things that just kind of expand the market because the cost has dropped so precipitously.
- 42:26 – 45:07
Future Directions and Opportunities in AI
- SSSteph Smith
Where do you guys want to see more builders applying themselves? You're obviously seeing a lot of companies, a lot of people excited. Also, the incumbents are clearly excited about getting in on this wave. Is there an area that you'd like to see more attention being put toward?
- ARAlex Rampell
Obscure is good.
- ASAngela Strange
Yeah.
- ARAlex Rampell
I mean, we, we love it when somebody walks in, has had, um, a decade or more of, like, obscurity. Uh, they, they, they served some weird job, or they were at, like, something that nobody's ever heard of, like, in, like, the farming industry, the mining industry, the whatever industry, and then they actually have an insight that somebody else doesn't, and they actually know the potential of AI. Because the other thing is that it's very important to know that the technology is not ready for autopilot for a lot of these things.
- ASAngela Strange
Mm-hmm.
- ARAlex Rampell
It's just like the, the use cases are too complicated. The integrating the different pipes is too complicated. So kind of overshooting early, like, there are gonna be a lot of failures because there inevitably are in every technology revolution, not because the idea is bad, um, but it's just like it's not good enough to be 100 times better.
- ASAngela Strange
Mm-hmm.
- ARAlex Rampell
So I, I think it's, like, obscure and then finding the ones where, like, at least for right now, it's not like it... Actually, the technology is good enough for the obscure use case at hand.
- ASAngela Strange
Yeah, I'd say also across, um, there's, there's many industries to this, but financial services and insurance have a host of old system, um, old, like, 30-plus-year-old systems of record that now can be made 10X better, incorporating labor, redoing them in a workflow. And so deep knowledge of those areas, like we have transaction monitoring in Sardine. We've got a mortgage loan origination system, Investa. We've got servicing. There's a lot. We've got a couple in insurance. And so entrepreneurs that really understand those space and can bring AI thinking there I think is a big opportunity.
- DHDavid Haber
Yeah, look, I, I think we'll continue to see lots of entrepreneurs, you know, wedge in with the messy inbox problem across lots of, you know, niche vertical industries. I think it's also we're still on the lookout for, you know, horizontal software, you know, kind of AI-native versions, you know, selling into sales teams, marketing, you know, product management, analytics, CFOs. Um, you know, in, in that, in those categories, you often do have a large incumbent software competitor, and so that's sort of the tension. You have to understand the market structure and how likely it is for that incumbent to change their pricing model and, and build kind of more AI-native features. But I think there will be generationally defining companies, you know, built in an AI-native way in, in horizontal software as well. [upbeat music]
Episode duration: 45:07
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Transcript of episode 6qQoZsfA_Iw
