← Animal Spirits Podcast
Loading summary
Transcript65 lines
- [00:00]
Michael Batnik
This episode is brought to you by Vaneck. Rare earth metals are the hidden backbone of modern technology and defense, powering everything from smartphones and electric vehicles to fighter jets and wind turbines. Vaneck recognized this early launching the Rare Earth and Strategic Metals ETF ticker 15 years ago, well before supply chain security became a global priority. Today, China dominates the production and refining capacity of rare earths, creating real challenges for global supply security as as these materials are essential for technological innovation, clean energy and national security. That's why countries around the world are racing to build their own supply chains and reduce reliance on China. As this global shift continues, investment in the rare earth ecosystem is growing rapidly, from mining to advanced manufacturing. Investors can access this powerful trend through REMX. Visit van Eck.com REMX compound to learn more.
- [00:56]
Ara Kharazian
Welcome to Animal Spirits, a show about markets, life and investing. Join Michael Batnik and Ben Carlson as they talk about what they're reading, writing and watching. All opinions expressed by Michael and Ben are solely their own opinion and do not reflect the opinion of Ritholtz Wealth Management. This podcast is for informational purposes only and should not be relied upon for any investment decisions. Clients of Ritholtz Wealth Management may maintain positions in the securities discussed in this podcast.
- [01:26]
Ben Carlson
Welcome to Animal Spirits with Michael and Ben. Today we are joined by Ara Kharazian, who is an economist at Ramp. He writes a substack called Ramp Economics Lab. Fascinating stuff. They sent us some of their work, some of their charts. We said, okay, we got to talk to this guy. It's really interesting stuff.
- [01:42]
Michael Batnik
You might be familiar with Ramp and you're not sure why the Saquon Barclay is doing commercials with them, unfortunately, which is neither here nor there. They are the fastest. I think they're the fastest fintech company to reach a billion dollars in annualized revenue. And they are doing so how? Because essentially what their business is is making expense reporting, automating business and all the annoying stuff that business don't want to deal with. Receipt, upload, credit card tri, whatever it is, they do that and obviously they do it really well. So what that gives them is, is the insight and the actual data to look through to their customers on where they're spending money. And today we talk about the AI category. What are businesses spending on which businesses, which sectors, the discrepancies between government data, what they're looking at. So lots of fascinating stuff in here.
- [02:44]
Ben Carlson
Yep. So here's our talk with Ara from Ramp.
- [02:50]
Michael Batnik
Ara, welcome to the show.
- [02:53]
Ara Kharazian
Thank you. Thank you for having me.
- [02:54]
Michael Batnik
All right. All that anybody is talking about these days, economists, individual investors, everybody. Is this AI explosion. And we want to know, they want to know, is it a bubble? Is it going to crash the stock market? Is it going to take down the economy with it? And it is a fair, legitimate question. It is a new technology, a new industrial revolution. The size and scale is enormous. The growth, the adoptions. Nvidia just crossed $5 trillion in market cap today. It's about to eclipse the, the entire Japanese stock market, like all of it. And so I'm super excited to talk with you today because you say, well, actually, if you really want to know what's going on, the best indicator to look at is how much businesses are spending. So you have something that you've built called the RAMP AI index. And you break down the different companies in terms of their size, what they're using, what they're spending. What does the data say today?
- [03:50]
Ara Kharazian
Well, yeah, you're getting at something very important about this conversation, which is that when we're talking about whether or not something is a bubble, I feel like people are grasping for all the different data sets that they can possibly use to support their answer. But frankly, for Aria, there's just not a lot of data available. Most of these companies that develop the technology are private, so there's not a lot of data you can get from public markets in terms of what is otherwise shared publicly. It's typically shared by companies or individuals that have some stake in the game. So you're not really sure what you can trust out there. I'm an economist at ramp. It's a financial operations platform that is used by everything from small startups to Fortune 500 companies to manage their operations. So I can see everything they're spending money on, everything except for essentially payroll. So that includes AI spend. And what's really unique about this data set is that you can see not only the companies that they're spending on. So you can see if they're buying stuff from OpenAI and Anthropic, but you can see whether or not those are actually large investments or if they're just small pilot programs here. I think that's the key thing about the moment that we're in. A lot of companies are trying out AI, but are they using AI in a long term, concerted way? Because that's the real question about whether or not we're in a bubble. The real question is, is the technology that's being developed providing benefits to the potential buyers such that they'll be likely to buy more in the future and and they're actually going to see productivity gains from this. And for what it's worth, when we look at where businesses are spending, that is exactly what we're seeing. Retention. AI products is higher, 80% now in 2024, about 50% in 2022. And AI contract sizes themselves are growing. We estimate that they'll hit about $1 million next year on average.
- [05:29]
Ben Carlson
So, I mean, are you seeing the growth exploding or is this more of just a slow burn over the years? Because it seems like this, I don't know, the enterprise stuff is just sort of being rolled out now?
- [05:40]
Ara Kharazian
Well, it depends on which side of the market that you're in. For enterprise, I think growth has been a little bit slower. We talk to a lot of enterprise firms that say they're hesitant to adopt AI across their firm because they're worried they won't be able to trust the results. Especially if they scale it to across all their customers. Things even like a customer service chatbot or someone you might talk to on the phone, they're hesitant to implement AI if it causes there's a significant amount of liability at the enterprise level. That said, in 2025 as well, we saw significant run up in the actual adoption of AI by companies announcing about 40% of companies on our platform have some significant AI contract on their books. Oftentimes those contracts aren't just for the main model companies. I'm talking about OpenAI and Anthropic. They are for platform level providers, customer service agents, AI agents that are working across tech stack or for tooling that's developed specifically for a team at the company. So it might be an AI tool for a finance team or an AI tool for a software engineer. Customers aren't necessarily going to see that, but they are producing productivity gains for the businesses that implement them.
- [06:41]
Michael Batnik
All right, so going back to that RAMP AI index that we're talking about, you break it down in a really neat way. You look at the different sectors that are using it, from technology to healthcare and everything between. You look at the size of the businesses, you look at the different models that they're using. One of the things that I want to talk about is your estimate is at 44% and we're going to talk about ramp and the visibility that you have into into the companies that you're serving. Why is there such a gigantic discrepancy between what you estimate in terms of overall adoption rate and what the government is estimating? They're at 9% and you're at 44%. What is happening Great question.
- [07:18]
Ara Kharazian
So we are using actual business spend to track business adoption. Look, there's going to be differences between any different data set when you're doing these comparisons. The government estimate of AI adoption from US Businesses, I do think has one significant flaw. First of all, it's based on a survey, and it's literally based on a survey that goes out every two weeks to businesses. And the question was written a couple years ago. And after I say the question, I think you'll kind of start to understand what's so weird about it. It's literally a question that asks businesses, in the last two weeks, have you used AI to produce goods and services? Goods and services is kind of like an econ speak term, and it was written a couple years ago. At the time, I think that question maybe made sense. We're getting at whether or not using AI to produce things in your factory in a productive way. Something like it hasn't really caught up to the way that most organizations are using AI to produce goods and services. Does that include customer service automation by AI? Does that include a significant number of your software engineers using AI to automate their coding tasks? Because that's most of the way. The AI product ecosystem has developed since 2023 when they started asking this question. And yet the question is written almost in a way that implies, hey, are you using AI to produce widgets in your factory? And when we've talked to businesses, they say that, yeah, this question is a little bit confusing. So I think for that reason, the government is likely underreporting the level of AI adoption actually happening. The truth is, I think Ramp's index is also slightly underreporting AI adoption because RAMP's estimate is coming from just paid usage. And we know for a fact that there's a significant number of free options now available in the market. Google started integrating Gemini for free into all of their enterprise workspace plans. Similar ChatGPT is used by a lot of employees who aren't necessarily using their employer plan. So AI adoption is happening. You can draw lines about what significant adoption is and where you want to say, yeah, this business is fully plugged into AI. But if you look at the government estimate, they were at 3% in 2023. It's now only about 9% in 2025. That seems really low. And I think you can point to the question being the reason. So for these reasons, I'm generally a fan of government data. I'm not one of those people who's. It's weird to say you're a fan of it. I'm not one of those people who sort of criticizes it, but for this specific question, we have better data sets available and spend data sets, for example, so I prefer to answer it with this kind of question.
- [09:43]
Ben Carlson
So one of our long running bits here is that we're an anti survey podcast for that very reason. You can kind of nudge people in different directions based on how you ask the question or who you ask. So that makes a lot of sense. So I'm curious just to back up a little. You kind of talked about this a little bit, but your co founder Karim was on Patrick's podcast recently. That's like the best explaining what Ramp does, but maybe you can just talk about what RAMP does just through the lens of the types of data sets that you're able to look at as an economist. And I'm sure for you this has got to be great because you must have a ton of new and different data than you've ever had access to before.
- [10:16]
Ara Kharazian
Yeah. In short, the company's product is a financial operations platform. So it's automating work that an accounting team might have to do or finance team might have to do. But as a consumer, most of us interact with it. With the expenses you have to file at the end of every month being the worst time of the month for you. Ramp's whole product is about automating that process. So instead of having to sit down and file your expenses and write it down everywhere you spent money, you just take a picture of your receipt and the software will analyze it for you, save it, file your expenses. You don't have to think about it. That's amazing for me as a researcher because I see line item receipts, which most transaction level data sets just don't have. So that's what allows me to do most of this work. I see everything that's on a receipt of as far as where a business spends money. So who, what, when, where, what did you spend on? Where did you spend it? And then what was the line item for the AI work? That means that we're not just seeing whether or not a company has a ChatGPT subscription. It means we can track API spend, we can track whether or not the actual dollar amount, can track whether or not these contracts are renewed. We can track whether or not they're using multiple different AI companies at a time and track the rise of things like Elon Musk's X AI Grok, for example, whether or not that's getting the business adoption that people are talking about now. The whole point of all this, people always ask why would RAMP hire this kind of role? Because my entire job is to be public facing is that the whole company's ethos is around allowing you to have access to better data about where your business spends money. Because ideally that would help you make better decisions. As a CEO or cfo, I don't work on the product, but I do have some feeling that if I am able to put out important data about where businesses are spending money, that would help resolve some questions for businesses that are on RAMP and that are not on ramp. Who want to know, hey, what should I buy? If I'm looking to get into AI and I've acquired software like where should I start? What are the leading companies? What are companies like me buying? How do I make these kinds of decisions? Because they're genuinely very hard in a very fast moving software marketplace where typically a business owner, if they want to know what software to buy, they have to go to like a McKinsey or a Forrester and pay like a massive engagement fee. And they still never get a data driven take about what businesses like them are spending on. And so really when I think about my job it's how can I produce work that helps make other companies more productive by informing the public about what the most productive companies in the world are spending on and investing in. That's really my research world.
- [12:47]
Michael Batnik
Do you think that, and this is not a data question per se, but do you think that these lines are going to continue to go up and to the right such that they reach like Internet penetration where we're talking about 90 plus percent of businesses using them? Because if, if that doesn't happen, then yeah, these, these valuations have a long way down.
- [13:13]
Ara Kharazian
Short answer is yes, I do think AI adoption is going to increase to the point that we're at 100% adoption across businesses. I mean there are businesses that will never be fully using AI, like in any, you know, concerted way. Like I think most restaurants probably not going to be massive users of AI, at least in the day to day, day to day operations. But they will probably be using AI for back office tasks and marketing and finance operations. So even if you don't see it as a consumer, it's still going to be happening though growth has slowed in adoption. The actual size of the contracts and the actual sort of deepness of the adoption is increasing. So I think you're going to see as the sort of products mature, especially as we start getting more verticalized options. Right now, most companies, adoption of AI is pretty limited to just chatgpt for all of your employees. But we're really early in the process. I was talking to a group of procurement professionals about what we're seeing in RAMP data, for example, and I was talking about the main trends. Yeah, OpenAI's up. Anthropic is growing really quickly. And the first question I got was, what's anthropic? And this is from a group of procurement professionals, people who are at companies in charge of buying software, and they didn't know what the second largest player was in this kind of market. And I think it's a very telling example of the fact that we're still very early. And yeah, AI might be a bubble here and there. There might be too much capex spend, we might be building too much data centers, but we're also in our own little bubble of people who are actively following the world of business and tech. And that means that I know what anthropic is, and I've tried all these different AI tools, but a lot of people have had very minimal interaction with them because the products haven't reached them yet.
- [14:57]
Ben Carlson
Right. I mean, what would you have to see for you to say, like, from a software adoption or your AI index, what would you have to see to be like, okay, this is, this is a problem. This is not taking off. Like, what kind of numbers would you have to see to make you worried?
- [15:11]
Ara Kharazian
If the size of contracts start to go down and if retention rates start to go down, that means that companies are trying these AI products and services and they're just not working for them. That's not what we're seeing right now. What we're seeing is that when a company tries an AI product or service, even when they are otherwise, you know, mindful of, they don't know, no company wants to see, like, software budgets explode for no reason. Like, they are monitoring and evaluating these contracts over time. If those retention rates were going to start to start declining, that tells us that the products that are making it to the market are not reaching customers in an effective way. They're not showing their value, they're not showing fit. They're either too expensive or they're not valuable at all. Absent that, I can't say that we're on a bad trajectory because from the data right now, at least as far as where businesses are spending, that's the big difference between this and the Internet bubble. It's that the companies that are producing this technology are producing technology that people are buying. Sometimes they're profitable. Yeah. And they're revenue generating. That was not necessarily the case in the Internet bubble. So I'm not, you're here to say like, oh, no one should be thinking about like Nvidia valuations. I'm not in that kind of world. But I do think this is a missing part of the discourse specifically because no one has access to this data. All the companies are private, so they don't release it themselves.
- [16:38]
Michael Batnik
I was talking with Ben and Josh about this yesterday. For as much as finance people just talk about the market cap or some sort of ratio evaluation, whatever, and it's like, guys, we have to talk about what's actually happening. Like what never is brought up. And it's brought up from certainly from tech people. Absolutely. And reporters talk about it, but the financial people often miss. It's like the 4 million square foot data center that Meta is building in Louisiana. You think they're like dumb, like they're, they're, it's just, they're just lighting money on fire and they have no idea what they're doing. And person on the, on the Twitterverse knows that Mark Zuckerberg's an idiot. Now it's not said that there can't be overspending, of course there can be. But there is fundamentally things that are, that are happening here. And one of the other sides of this conversation that I'm sure you have insight to is the amount of money that's being spent on software or the lack thereof. A lot of these names, at least in the stock market, are under, are under pressure, probably rightfully so. I'm not going to put you on the hot seat and say like, is this a value or value trap? Like what do you think about Adobe for example? But is the, and we're going to hear from these companies very shortly. Are you seeing material slowdowns there that would make you feel better about the fact that a lot of that spend is migrating to AI material slowdowns in.
- [17:58]
Ara Kharazian
Software companies that are not fully AI companies.
- [18:01]
Michael Batnik
Just whether it's Salesforce, ServiceNow, Adobe Workforce, like whatever it is, generally.
- [18:09]
Ara Kharazian
No, I mean another way I'll say this is that the fastest growing segment and sub segment of RAN data is tech companies spending on other tech companies. It's actually not just tech companies spending on other tech companies, essentially all companies spending a lot on software. In part that's driven by the fact that there's now so many more AI solutions for companies. So it's oftentimes the software, the AI software themselves. But we're also seeing growth for these legacy Software solutions. So there are going to be losers from the sort of software revolution that's happening. But I think it's way too soon to say who they're going to be.
- [18:47]
Ben Carlson
So you obviously work with a wide range of businesses and in your index model you look at companies by size. Is it too easy to think that the smaller companies are actually going to be the biggest beneficiaries here because it'll allow them to be more efficient, or do you think that the largest players are the strong just going to get stronger and the big get bigger?
- [19:06]
Ara Kharazian
It's a good question. It depends how they're integrating it. I think the large companies that are integrating it typically have a dedicated tech team, for example. So that means they probably have tech people, engineers who are able to take advantage of the AI that's developed for software engineering. And that's one of the greatest use cases of AI available today. It's just really well developed for software engineering tasks. In addition to that, you can think about customer service operations. That's another place where AI has done very well and we've seen enterprise adoption happen. That doesn't translate often to small businesses, but it's not to say that small businesses aren't using AI in creative and productivity enhancing ways. The example I used earlier of a restaurant probably not using AI to serve people or make anything, make orders, but it's probably using AI to generate marketing copy or like make a quick social media post that they want a picture for that's engaging. Right. Heard of that happening often. Is that going to be a massive driver of gdp? Of course not. But it can help set a restaurant apart in a way that it was not able to do before if they're able to adopt effectively.
- [20:14]
Michael Batnik
The learn to code crowd has been obviously in a world of pain. There's charts that show the amount of software engineers that have been hired and it's round trip and it's ugly and painful. And do you have any visibility into the labor side of this or are you just seeing the line item spending?
- [20:29]
Ara Kharazian
There's really great research coming out. I mean the question of how AI is going to affect the labor market is. It's the question in AI and economics.
- [20:37]
Ben Carlson
Today that might be the biggest question that we see this century. Right. It's going to and just have long lasting impacts and so many unintended consequences.
- [20:46]
Ara Kharazian
I think you're right.
- [20:47]
Michael Batnik
I think the optimistic view there is that like this is going to change the world, we're going to create new jobs, we're going to be better than we ever were before. That is the history of technological innovations. And it's also true that in between now and then there can be a lot of people displaced and there can be a lot of societal change for the worst, for the people that are impacted. And how do we, how do we bridge the gap between now and everything's gonna be okay? It's, it's, it's scary.
- [21:16]
Ara Kharazian
Yeah. I mean, I think that you're on the right track. I'm not really an AI doomer and usually what I think about this is it just seems like we go through this technological cycle every time we have a new technological cycle and most things in the economy adjust. The economy is very large and dynamic. So I'll say even a lot of the automation happening today, a lot of the concerns about where automation happening is today. Software engineering tasks, white collar tasks. Most jobs in the US economy today are not exposed at all. Most jobs require some kind of physical component. One of the most common job titles in the US is just like nurse, waiter, restaurant worker, something like that, some healthcare worker. None of those jobs are going to be automated anytime soon, if ever. Now that's not all you need for a recession. You don't need 50% unemployment for a recession. You need just a couple percentage points increase.
- [22:08]
Michael Batnik
That's a depression.
- [22:11]
Ara Kharazian
But the early research is that if there is an impact on unemployment, it's happening in a specific few sectors right now on a fairly narrow segment of workers who are otherwise able to find other jobs because the unemployment rate has not increased in any significant way over the past two or three years. So so far it's remained under control and has otherwise delivered some productivity benefits to businesses. But we're still tracking that.
- [22:37]
Michael Batnik
Last question for me on the AI stuff just in terms of this index. It's publicly available like you or you can get it through Bloomberg. But people tweet this stuff like you're gonna. If there's a turn work, we're all gonna know about it. Thanks to you guys.
- [22:48]
Ara Kharazian
It's ramp.com data. It's all publicly available. Everything I do is. That's the whole point of it. I think it's important for these conversations to have a little more data and.
- [22:59]
Ben Carlson
You have a, you have a great substack called Ramp Economics Lab.
- [23:02]
Michael Batnik
Yep.
- [23:02]
Ben Carlson
And I'm curious what your process is for. For trying to answer some of these questions because you have one that Michael and I have been discussing. It's called why tariffs are so Confusing. And I think a lot of people have been left scratching their head going Wait a minute. The economic theory would say that these tariffs are supposed to be inflationary. They should have impacted growth. We're not seeing it yet. And you dug into this and tried to figure out, well, why is that the case? And it's one of those. I read your post and I kind of hit myself. I'm like, oh, duh, of course. And your point is that, listen, all of the announcements and what people are saying, that's not actually what the businesses or consumers are paying just yet. Like, it still hasn't filtered through. So why don't you tell us what you found there?
- [23:45]
Ara Kharazian
Yeah, we. So we can see in ramp data tariffs, because we see that on invoices when a business is ordering manufacturing goods and they order it from abroad and they're importing, we see the actual tariff line item or we see like a DHL receipt and it will show the import export duty. And what we found was that tariffs are increasing. Like the share of transactions that include tariffs are certainly increasing, especially in manufacturing and retail, but it's much more slower and more granular than it than you'd think. Essentially the average tariff rate was something like 1.4%. Now we're only about 3% as far as like share of invoices with a tariff transaction on them. So we're seeing that.
- [24:22]
Ben Carlson
That's way lower than I ever would have thought. Right? Yeah, it doubled from last year, but it's tiny.
- [24:28]
Ara Kharazian
The incidence of tariffs has doubled. But given that we have implemented tariffs on pretty much every trading partner, you'd expect something much more significant. And the effect is very gradual. If you look at, you track the line over time, over the past couple months, it's not even. There's no drop line happening when the tariffs get announced. And I think what people miss about the tariff announcements is, I mean, it was unprecedented. A lot of economists were very reasonably concerned when it was announced and remained concerned. But there are a lot of frictions to implementing these kinds of ideas. You need to actually figure out, okay, wait, what is actually tariffs? Because we have trade agreements that are still in place that tariff announcements were announced in this broad way, but they're not actually legal. If they're against the existing trade agreements, there's that. But there's also people at the ports who have to figure out how to assess the tariffs and be appropriately trained on this.
- [25:27]
Ben Carlson
And can the companies effectively hide them or like reclassify so they're not paying them? I'm not saying they're cheating, but companies can probably skirt the issue because there's so many different variations. Or, hey, this product is. Does have a tariff, but this one doesn't. Can't they. I mean, you can't have any sort.
- [25:44]
Ara Kharazian
Of a lot of companies, every legal path.
- [25:46]
Ben Carlson
Yeah, yeah.
- [25:47]
Ara Kharazian
And then there are also companies that are banking on the sort of. There's some. Some suggestion that, oh, maybe some of these tariffs will be rolled back. Right. So there's not a lot of commerce changes actually happening. And then there are companies that we've talked to that say that they are moving their production in response to tariffs, but they're not necessarily moving it back to the U.S. they're moving to sort of the lower tariff nations. Tariffs that were announced were broad, but they were not the same everywhere. And there are options available to companies now. It's not to say that there haven't been significant disruptions. There have been specifically these frictions that I'm driving that are making it hard to collect. Tariffs are also making it hard to do really any commerce that involves imports, exports, because the companies that take things in from abroad are seeing delayed shipments, they're seeing delayed port operations. All of this stuff takes a lot of time. And for that reason, again, there have been significant disruptions. But also for that reason, it means that the pace of tariffs making their way through the economy has been significantly slower than we think. Price increases haven't happened to nearly the same extent as we'd expect, specifically because a lot of companies haven't started paying these tariffs yet in a meaningful way. Again, depends on the sector, and there are some significantly exposed ports, but it's been much slower than most of us thought.
- [27:02]
Michael Batnik
Ara, what are you working on next and how frequently do you plan to publish your work?
- [27:07]
Ara Kharazian
I publish weekly on Ramp Economics Lab on Substack, and right now, look, I'm always looking for ideas, so people need to send me anything. Again, my business spend data set really allows us to work to identify what the latest trends are. What's just a vibe that people are talking about in the news versus what is an actual thing that's going on in our economy right now. The main focus has been AI and tariffs, of course, but, you know, we follow a lot of trends, and a lot of the way I approach my work is just trying to figure out what can I confirm or correct.
- [27:39]
Michael Batnik
Hey, how about this? What about Chipotle prices in New York City? Because anecdotally, I mean, I don't go to every Chipotle, but I feel like they peaked a while ago. I'd be curious to see the Data we asked ChatGPT and they couldn't give it to us.
- [27:49]
Ara Kharazian
Well, I need the. I wish that the receipts also included the weight of what you bought, because that's what the variability is.
- [27:56]
Ben Carlson
Wait, I got price.
- [27:57]
Ara Kharazian
I could tell you the price in New York City right now because, like, it's the block, but I can't tell you the price per ounce unless we do like a crazy.
- [28:04]
Ben Carlson
That's what I said. We got shrinkflation. They're not filling up anymore. But one of the interesting ones, you said you've been focusing on AI and tariffs. You have this one that I think is interesting. And Michael someone, one of our listeners, said that the 996 phenomenon is the new fire in terms of, like, there's going to be way more reporting on that. So you had this. You had this data that looks at San Francisco workers are working more Saturday. So the 996 phenomenon is. What is it? You work six days a week for nine hours.
- [28:29]
Michael Batnik
Nine days a week.
- [28:30]
Ara Kharazian
9Am to 9pm Six days a week. That's a subculture that I think is working culture that was originally associated with Chinese working culture.
- [28:39]
Michael Batnik
This is virgin culture. Yeah, let's be clear.
- [28:43]
Ara Kharazian
Well, one of the. Well, actually, no. If you talk to people who do996, one of the main principles is get married early. There's a lot.
- [28:51]
Ben Carlson
Oh, that's right.
- [28:52]
Ara Kharazian
There's a lot of side components of the culture of, like, working late in the subculture, where it's like, not only do you have to work late and get married early for some reason, there's a whole thing about eating a lot of meat and working out a lot. So I don't know.
- [29:08]
Ben Carlson
But you did actually look at, like, the takeout invoices, right? To show that people are at. Businesses are ordering more food on Saturdays, meaning that they're working more food.
- [29:18]
Michael Batnik
This explains the DoorDash run the 996ers.
- [29:22]
Ara Kharazian
It's true. So when we like, the number of workers, at least in the SF area, working on weekends, like Saturdays and Sundays has increased, we estimate over the entire Bay area. Maybe about 40,000 workers across the metro area are now working Saturdays and Sundays in a way that they were not last year.
- [29:40]
Michael Batnik
Is that good or bad? Huh? Okay. All right. We'll leave that for the audience to discuss. All right, so, Ara, I know you're not on the product side, but as we exit the stage, what is the pitch for people that are listening? They're like, wait, what does ramp do? And why should I care? Should I? Am I a customer? Should I be a customer? What do you guys do?
- [30:00]
Ara Kharazian
Got your finance team to use ramp? I am the only spokesperson of the company. Doesn't have to sell it, but I use Ramp, obviously, because I work here. It makes it really easy to do a lot of these finance tasks, both for the finance operations in the back office and also for the actual user. So you don't have to submit a receipt anymore. You don't have to do all that stuff. It's all automated. We often talk about the effect of AI on unemployment. And the way we see it here, the way I see it here as a researcher is I would love for AI to take over a lot of these tasks that we just don't need to do anymore. Let AI read your receipts and file your finances for you. Let AI process through what you're allowed to buy and purchase on an offsite or what you're allowed to do for doordash. Think about that stuff. Automation of all your finance tasks is really the shorthand for it.
- [30:48]
Michael Batnik
Okay. All right, Ara, this is great. Looking forward to seeing your work. Thank you very much for coming on today.
- [30:53]
Ara Kharazian
Thank you guys for having me. It's so much fun.